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Publications of year 2015

Thesis

  1. Pooja S. Mahapatra. Geodetic network design for InSAR: Application to ground deformation monitoring. PhD thesis, TU Delft, 2015. Keyword(s): SAR Processing, InSAR Persistent Scatterer Interferometry, PSI, GNSS, Transponder, Geodetic Network.
    Abstract: For the past two decades, interferometric synthetic aperture radar (InSAR) has been used to monitor ground deformation with subcentimetric precision from space. But the applicability of this technique is limited in regions with a low density of naturally-occurring phase-coherent radar targets, e.g. vegetated nonurbanized areas. Third-party end-users of InSAR survey results cannot, in a systematic way, determine a priori whether these coherent targets have adequate spatial distribution to estimate the parameters of their interest. Additionally, InSAR deformation estimates are referred to a local datum, meaning that the technique is sensitive only to the relative deformation occurring within the SAR images. This makes it difficult to compare these estimates with those from other techniques, e.g. historical levelling data or changes in the sea level. Here we propose the design of a geodetic network for InSAR, aimed at densifying the naturally-occurring measurement network and converting from a local datum to a global one. A practical solution for improving spatial sampling is to deploy coherent target devices such as corner reflectors or transponders on ground, tailored to the specific monitoring application under consideration. The proposed method (1) provides a generic description of any deformation phenomenon; (2) determines whether the naturally-occurring InSAR measurements are adequate in terms of user-defined criteria; (3) finds the minimum number of additional devices to be deployed (if required); and (4) finds their optimal ground locations. It digests, as inputs, any prior knowledge of the deformation signal, the expected locations and quality of the existing coherent targets, and the quality of the deployed devices. The method is based on comparing different covariance matrices of the final parameters of interest with a criterion matrix (i.e., the ideal desired covariance matrix) using a predefined metric. The resulting measurement network is optimized with respect to precision, reliability and economic criteria; this is demonstrated via synthetic examples and a case of subsidence in the Netherlands. As a basis for the choice and number of deployed devices, we evaluate the measurement precision of compact active transponders and demonstrate their viability as alternatives to passive corner reflectors through three field experiments, using different satellite data and geodetic validation techniques. Transponders are shown to be usable for subcentimetre-precision geodetic applications, while improving upon the drawbacks of corner reflectors in terms of size, shape, weight and conspicuousness. For transforming the spatially-relative InSAR deformation estimates (local datum) to a standard terrestrial reference frame (global datum), we introduce a new concept involving the collocation of transponders with Global Navigation Satellite System (GNSS) measurements. The displacement of such a transponder is consequently determined in the standard reference frame used by GNSS, eliminating the need for any assumptions on reference-point stability in applications where the InSAR deformation estimates are compared with results from other techniques. The considerations, results and practical lessons learnt at several permanent GNSS stations in the Netherlands are described.

    @PhdThesis{mahapatra20015PhDThesisInSARandGNSS,
    author = {Mahapatra, Pooja S.},
    title = {Geodetic network design for {InSAR}: Application to ground deformation monitoring},
    school = {TU Delft},
    year = {2015},
    abstract = {For the past two decades, interferometric synthetic aperture radar (InSAR) has been used to monitor ground deformation with subcentimetric precision from space. But the applicability of this technique is limited in regions with a low density of naturally-occurring phase-coherent radar targets, e.g. vegetated nonurbanized areas. Third-party end-users of InSAR survey results cannot, in a systematic way, determine a priori whether these coherent targets have adequate spatial distribution to estimate the parameters of their interest. Additionally, InSAR deformation estimates are referred to a local datum, meaning that the technique is sensitive only to the relative deformation occurring within the SAR images. This makes it difficult to compare these estimates with those from other techniques, e.g. historical levelling data or changes in the sea level. Here we propose the design of a geodetic network for InSAR, aimed at densifying the naturally-occurring measurement network and converting from a local datum to a global one. A practical solution for improving spatial sampling is to deploy coherent target devices such as corner reflectors or transponders on ground, tailored to the specific monitoring application under consideration. The proposed method (1) provides a generic description of any deformation phenomenon; (2) determines whether the naturally-occurring InSAR measurements are adequate in terms of user-defined criteria; (3) finds the minimum number of additional devices to be deployed (if required); and (4) finds their optimal ground locations. It digests, as inputs, any prior knowledge of the deformation signal, the expected locations and quality of the existing coherent targets, and the quality of the deployed devices. The method is based on comparing different covariance matrices of the final parameters of interest with a criterion matrix (i.e., the ideal desired covariance matrix) using a predefined metric. The resulting measurement network is optimized with respect to precision, reliability and economic criteria; this is demonstrated via synthetic examples and a case of subsidence in the Netherlands. As a basis for the choice and number of deployed devices, we evaluate the measurement precision of compact active transponders and demonstrate their viability as alternatives to passive corner reflectors through three field experiments, using different satellite data and geodetic validation techniques. Transponders are shown to be usable for subcentimetre-precision geodetic applications, while improving upon the drawbacks of corner reflectors in terms of size, shape, weight and conspicuousness. For transforming the spatially-relative InSAR deformation estimates (local datum) to a standard terrestrial reference frame (global datum), we introduce a new concept involving the collocation of transponders with Global Navigation Satellite System (GNSS) measurements. The displacement of such a transponder is consequently determined in the standard reference frame used by GNSS, eliminating the need for any assumptions on reference-point stability in applications where the InSAR deformation estimates are compared with results from other techniques. The considerations, results and practical lessons learnt at several permanent GNSS stations in the Netherlands are described.},
    doi = {10.4233/uuid:8933e2d2-fa0f-42a2-90f1-ceb2795c75c6},
    file = {:mahapatra20015PhDThesisInSARandGNSS.pdf:PDF},
    isbn = {978-94-6186-474-1},
    keywords = {SAR Processing, InSAR Persistent Scatterer Interferometry, PSI, GNSS, Transponder, Geodetic Network},
    pdf = {../../../docs/mahapatra20015PhDThesisInSARandGNSS.pdf},
    url = {https://repository.tudelft.nl/islandora/object/uuid:8933e2d2-fa0f-42a2-90f1-ceb2795c75c6/datastream/OBJ/download},
    
    }
    


Articles in journal or book chapters

  1. Tazio Strozzi, Hugo Raetzo, Urs Wegmller, Jessica Papke, Rafael Caduff, Charles L. Werner, and Andreas Wiesmann. Satellite and Terrestrial Radar Interferometry for the Measurement of Slope Deformation, chapter Satellite and Terrestrial Radar Interferometry for the Measurement of Slope Deformation, pages 161-165. Springer International Publishing, Cham, 2015.
    Abstract: Synergistic use of satellite and terrestrial radar interferometry was considered for the measurement of slope deformation in the Mattervalley (Canton of Valais, Switzerland). Highest rates of movement of more than 1 cm/day were measured only with terrestrial radar interferometry, because of the large time interval between satellite SAR observations. Summer TerraSAR-X and Cosmo-SkyMed interferograms as well as terrestrial radar interferometry campaigns repeated with a time interval of a few days were jointly considered for the study of landslides moving at rates of dm/year. Persistent scatterer interferometric analyses conducted with ERS-1/2, ENVISAT, Radarsat-2, TerraSAR-X and Cosmo-SkyMed images were finally used to detect the slowest moving landslides, with rates of movement below a few cm/yr in the line-of-sight direction.

    @InBook{strozziRaetzoWegmullerPapkeCaduffWernerWiesmannEngGeology2015Deformation,
    chapter = {Satellite and Terrestrial Radar Interferometry for the Measurement of Slope Deformation},
    pages = {161-165},
    title = {Satellite and Terrestrial Radar Interferometry for the Measurement of Slope Deformation},
    publisher = {Springer International Publishing},
    year = {2015},
    author = {Strozzi, Tazio and Raetzo, Hugo and Wegm{\"u}ller, Urs and Papke, Jessica and Caduff, Rafael and Werner, Charles L. and Wiesmann, Andreas},
    editor = {Lollino, Giorgio and Manconi, Andrea and Guzzetti, Fausto and Culshaw, Martin and Bobrowsky, Peter and Luino, Fabio},
    address = {Cham},
    isbn = {978-3-319-09048-1},
    abstract = {Synergistic use of satellite and terrestrial radar interferometry was considered for the measurement of slope deformation in the Mattervalley (Canton of Valais, Switzerland). Highest rates of movement of more than 1 cm/day were measured only with terrestrial radar interferometry, because of the large time interval between satellite SAR observations. Summer TerraSAR-X and Cosmo-SkyMed interferograms as well as terrestrial radar interferometry campaigns repeated with a time interval of a few days were jointly considered for the study of landslides moving at rates of dm/year. Persistent scatterer interferometric analyses conducted with ERS-1/2, ENVISAT, Radarsat-2, TerraSAR-X and Cosmo-SkyMed images were finally used to detect the slowest moving landslides, with rates of movement below a few cm/yr in the line-of-sight direction.},
    booktitle = {Engineering Geology for Society and Territory - Volume 5: Urban Geology, Sustainable Planning and Landscape Exploitation},
    doi = {10.1007/978-3-319-09048-1_32},
    file = {:strozziRaetzoWegmullerPapkeCaduffWernerWiesmannEngGeology2015Deformation.pdf:PDF},
    owner = {ofrey},
    pdf = {../../../docs/strozziRaetzoWegmullerPapkeCaduffWernerWiesmannEngGeology2015Deformation.pdf},
    url = {http://dx.doi.org/10.1007/978-3-319-09048-1_32},
    
    }
    


  2. Laurent Ferro-Famil, Yue Huang, and Eric Pottier. Principles and Applications of Polarimetric SAR Tomography for the Characterization of Complex Environments. In International Association of Geodesy Symposia, pages 1-13. Springer Berlin Heidelberg, Berlin, Heidelberg, 2015.
    @InCollection{ferroFamilHuangPottierSpringer2015TomoOverview,
    author = {Ferro-Famil, Laurent and Huang, Yue and Pottier, Eric},
    title = {Principles and Applications of Polarimetric {SAR} Tomography for the Characterization of Complex Environments},
    booktitle = {International Association of Geodesy Symposia},
    publisher = {Springer Berlin Heidelberg},
    year = {2015},
    pages = {1-13},
    address = {Berlin, Heidelberg},
    doi = {10.1007/1345_2015_12},
    file = {:ferroFamilHuangPottierSpringer2015TomoOverview.pdf:PDF},
    owner = {ofrey},
    pdf = {../../../docs/ferroFamilHuangPottierSpringer2015TomoOverview.pdf},
    url = {http://dx.doi.org/10.1007/1345_2015_12},
    
    }
    


  3. Fadwa Alshawaf, T. Fuhrmann, A. Knpfler, X. Luo, Michael Mayer, Stefan Hinz, and B. Heck. Accurate Estimation of Atmospheric Water Vapor Using GNSS Observations and Surface Meteorological Data. IEEE Transactions on Geoscience and Remote Sensing, 53(7):3764-3771, July 2015. Keyword(s): atmospheric humidity, atmospheric temperature, remote sensing, satellite navigation, time series, remote sensing data, temporal variation, spatial variation, Global Navigation Satellite System, time series, precipitable water vapor content, precise point positioning, absolute precipitable water vapor, GNSS observations, GNSS site, surface temperature measurements, GNSS-based delay, MEdium Resolution Imaging Spectrometer sensor, mean RMS value, GNSS-based total precipitable water vapor, Weather Research and Forecasting Modeling System, WRF model simulations, atmospheric water vapor estimation, surface meteorological data, Global Positioning System, Delays, Temperature measurement, Atmospheric modeling, Atmospheric measurements, Satellites, Atmospheric sounding, Global Navigation Satellite System(s) (GNSS), MEdium Resolution Imaging Spectrometer (MERIS), precipitable water vapor (PWV), Weather Research and Forecasting (WRF), Atmospheric sounding, Global Navigation Satellite System(s) (GNSS), MEdium Resolution Imaging Spectrometer (MERIS), precipitable water vapor (PWV), Weather Research and Forecasting (WRF).
    Abstract: Remote sensing data have been increasingly used to measure the content of water vapor in the atmosphere and to characterize its temporal and spatial variations. In this paper, we use observations from Global Navigation Satellite System(s) (GNSS) to estimate time series of precipitable water vapor (PWV) by applying the technique of precise point positioning. For an accurate quantification of the absolute PWV, it is necessary to combine the GNSS observations with meteorological data measured directly or inferred at the GNSS site. In addition, measurements of the surface temperature are used to calculate the empirical constant required to convert the GNSS-based delay into water vapor. Our results show strong agreement between the total precipitable water estimated based on GNSS observations and that measured by the sensor MEdium Resolution Imaging Spectrometer with a mean RMS value of 0.98 mm. In a similar way, we compared the GNSS-based total PWV estimates with those produced by the Weather Research and Forecasting (WRF) Modeling System. We found that the WRF model simulations agree well with the GNSS estimates with a mean RMS value of 0.97 mm.

    @Article{7035082,
    author = {Fadwa Alshawaf and T. Fuhrmann and A. Kn{\"o}pfler and X. Luo and Michael Mayer and Stefan Hinz and B. Heck},
    title = {Accurate Estimation of Atmospheric Water Vapor Using GNSS Observations and Surface Meteorological Data},
    journal = {IEEE Transactions on Geoscience and Remote Sensing},
    year = {2015},
    volume = {53},
    number = {7},
    pages = {3764-3771},
    month = jul,
    issn = {0196-2892},
    abstract = {Remote sensing data have been increasingly used to measure the content of water vapor in the atmosphere and to characterize its temporal and spatial variations. In this paper, we use observations from Global Navigation Satellite System(s) (GNSS) to estimate time series of precipitable water vapor (PWV) by applying the technique of precise point positioning. For an accurate quantification of the absolute PWV, it is necessary to combine the GNSS observations with meteorological data measured directly or inferred at the GNSS site. In addition, measurements of the surface temperature are used to calculate the empirical constant required to convert the GNSS-based delay into water vapor. Our results show strong agreement between the total precipitable water estimated based on GNSS observations and that measured by the sensor MEdium Resolution Imaging Spectrometer with a mean RMS value of 0.98 mm. In a similar way, we compared the GNSS-based total PWV estimates with those produced by the Weather Research and Forecasting (WRF) Modeling System. We found that the WRF model simulations agree well with the GNSS estimates with a mean RMS value of 0.97 mm.},
    doi = {10.1109/TGRS.2014.2382713},
    keywords = {atmospheric humidity;atmospheric temperature;remote sensing;satellite navigation;time series;remote sensing data;temporal variation;spatial variation;Global Navigation Satellite System;time series;precipitable water vapor content;precise point positioning;absolute precipitable water vapor;GNSS observations;GNSS site;surface temperature measurements;GNSS-based delay;MEdium Resolution Imaging Spectrometer sensor;mean RMS value;GNSS-based total precipitable water vapor;Weather Research and Forecasting Modeling System;WRF model simulations;atmospheric water vapor estimation;surface meteorological data;Global Positioning System;Delays;Temperature measurement;Atmospheric modeling;Atmospheric measurements;Satellites;Atmospheric sounding;Global Navigation Satellite System(s) (GNSS);MEdium Resolution Imaging Spectrometer (MERIS);precipitable water vapor (PWV);Weather Research and Forecasting (WRF);Atmospheric sounding;Global Navigation Satellite System(s) (GNSS);MEdium Resolution Imaging Spectrometer (MERIS);precipitable water vapor (PWV);Weather Research and Forecasting (WRF)},
    owner = {ofrey},
    
    }
    


  4. Fadwa Alshawaf, Stefan Hinz, Michael Mayer, and Franz J. Meyer. Constructing accurate maps of atmospheric water vapor by combining interferometric synthetic aperture radar and GNSS observations. Journal of Geophysical Research: Atmospheres, 120(4):1391-1403, 2015. Keyword(s): SAR Processing, atmospheric water vapor, InSAR, GNSS, SAR Processing, Tropospheric Path Delay, Synthetic Aperture Radar, Atmospheric Modelling, Atmospheric modeling, Meteorology, radar clutter, radar imaging, radar interferometry, synthetic aperture radar (SAR).
    Abstract: AbstractOver the past 20years, repeat-pass spaceborne interferometric synthetic aperture radar (InSAR) has been widely used as a geodetic technique to generate maps of the Earth's topography and to measure the Earth's surface deformation. In this paper, we present a new approach to exploit microwave data from InSAR, particularly Persistent Scatterer InSAR (PSI), and Global Navigation Satellite Systems (GNSS) to derive maps of the absolute water vapor content in the Earth's atmosphere. Atmospheric water vapor results in a phase shift in the InSAR interferogram, which if successfully separated from other phase components provides valuable information about its distribution. PSI produces precipitable water vapor (PWV) difference maps of a high spatial density, which can be inverted using the least squares method to retrieve PWV maps at each SAR acquisition time. These maps do not contain the absolute (total) PWV along the signal path but only a part of it. The components eliminated by forming interferograms or phase filtering during PSI data processing are reconstructed using GNSS phase observations. The approach is applied to build maps of absolute PWV by combining data from InSAR and GNSS over the region of Upper Rhine Graben in Germany and France. For validation, we compared the derived PWV maps with PWV maps measured by the optical sensor MEdium-Resolution Imaging Spectrometer. The results show strong spatial correlation with values of uncertainty of less than 1.5mm. Continuous grids of PWV are then produced by applying the kriging geostatistical interpolation technique that exploits the spatial correlations between the PWV observations.

    @Article{alshawafHinzMayerMeyerJGR2015AtmosphericWaterVaporFromInSARandGNSS,
    author = {Alshawaf, Fadwa and Hinz, Stefan and Mayer, Michael and Meyer, Franz J.},
    title = {Constructing accurate maps of atmospheric water vapor by combining interferometric synthetic aperture radar and GNSS observations},
    journal = {Journal of Geophysical Research: Atmospheres},
    year = {2015},
    volume = {120},
    number = {4},
    pages = {1391-1403},
    abstract = {AbstractOver the past 20years, repeat-pass spaceborne interferometric synthetic aperture radar (InSAR) has been widely used as a geodetic technique to generate maps of the Earth's topography and to measure the Earth's surface deformation. In this paper, we present a new approach to exploit microwave data from InSAR, particularly Persistent Scatterer InSAR (PSI), and Global Navigation Satellite Systems (GNSS) to derive maps of the absolute water vapor content in the Earth's atmosphere. Atmospheric water vapor results in a phase shift in the InSAR interferogram, which if successfully separated from other phase components provides valuable information about its distribution. PSI produces precipitable water vapor (PWV) difference maps of a high spatial density, which can be inverted using the least squares method to retrieve PWV maps at each SAR acquisition time. These maps do not contain the absolute (total) PWV along the signal path but only a part of it. The components eliminated by forming interferograms or phase filtering during PSI data processing are reconstructed using GNSS phase observations. The approach is applied to build maps of absolute PWV by combining data from InSAR and GNSS over the region of Upper Rhine Graben in Germany and France. For validation, we compared the derived PWV maps with PWV maps measured by the optical sensor MEdium-Resolution Imaging Spectrometer. The results show strong spatial correlation with values of uncertainty of less than 1.5mm. Continuous grids of PWV are then produced by applying the kriging geostatistical interpolation technique that exploits the spatial correlations between the PWV observations.},
    doi = {10.1002/2014JD022419},
    eprint = {https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1002/2014JD022419},
    file = {:alshawafHinzMayerMeyerJGR2015AtmosphericWaterVaporFromInSARandGNSS.pdf:PDF},
    keywords = {SAR Processing, atmospheric water vapor, InSAR, GNSS, SAR Processing, Tropospheric Path Delay, Synthetic Aperture Radar, Atmospheric Modelling, Atmospheric modeling; Meteorology;radar clutter;radar imaging;radar interferometry;synthetic aperture radar (SAR)},
    owner = {ofrey},
    url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1002/2014JD022419},
    
    }
    


  5. Francesco Banda and Stefano Tebaldini. Texture-Free Absolute DEM Retrieval From Opposite-Side Multibaseline InSAR Data. IEEE Geosci. Remote Sens. Lett., PP(99):1-5, 2015. Keyword(s): SAR Processing, Multibaseline InSAR, Accuracy, Azimuth, Estimation, Laser radar, Radar tracking, Synthetic aperture radar, Tomography, Digital elevation model (DEM), radargrammetry, synthetic aperture radar interferometry (InSAR).
    Abstract: In this letter, we propose a new methodology to estimate the absolute digital elevation model (DEM) of an area by radargammetric-like processing of interferometric multibaseline synthetic aperture radar (SAR) data from two opposite-side surveys. Two DEMs of the imaged area obtained from two opposite-side tomographic SAR views are coregistered, correcting residual baseline errors. This methodology combines the great accuracy of multibaseline interferometric processing with precise stereo plotting typical of opposite-side radargrammetry, requires no texture matching and no control points, and is applicable also in the case of few a priori information about the site topography.

    @Article{bandaTebaldiniGRSL2015DEMRetrievalInSAR,
    author = {Banda, Francesco and Tebaldini, Stefano},
    journal = {IEEE Geosci. Remote Sens. Lett.},
    title = {Texture-Free Absolute {DEM} Retrieval From Opposite-Side Multibaseline InSAR Data},
    year = {2015},
    issn = {1545-598X},
    number = {99},
    pages = {1-5},
    volume = {PP},
    abstract = {In this letter, we propose a new methodology to estimate the absolute digital elevation model (DEM) of an area by radargammetric-like processing of interferometric multibaseline synthetic aperture radar (SAR) data from two opposite-side surveys. Two DEMs of the imaged area obtained from two opposite-side tomographic SAR views are coregistered, correcting residual baseline errors. This methodology combines the great accuracy of multibaseline interferometric processing with precise stereo plotting typical of opposite-side radargrammetry, requires no texture matching and no control points, and is applicable also in the case of few a priori information about the site topography.},
    doi = {10.1109/LGRS.2015.2494684},
    file = {:bandaTebaldiniGRSL2015DEMRetrievalInSAR.pdf:PDF},
    keywords = {SAR Processing, Multibaseline InSAR, Accuracy;Azimuth;Estimation;Laser radar;Radar tracking;Synthetic aperture radar;Tomography;Digital elevation model (DEM);radargrammetry;synthetic aperture radar interferometry (InSAR)},
    pdf = {../../../docs/bandaTebaldiniGRSL2015DEMRetrievalInSAR.pdf},
    
    }
    


  6. D. P. S. Bekaert, A. Hooper, and T. J. Wright. A spatially variable power law tropospheric correction technique for InSAR data. Journal of Geophysical Research: Solid Earth, 120(2):1345-1356, February 2015. Keyword(s): SAR Interferometry, Spatially-variable Correction, Power law model, Troposphere, APS, Estimation of APS, Atmospheric Phase Screen, Interferometry, Tropospheric Path Delay.
    @Article{bekaertHooperWrightAGUJGR2015SpatiallyVariablePowerLawTroposphericCorrINSAR,
    author = {D. P. S. Bekaert and A. Hooper and T. J. Wright},
    journal = {Journal of Geophysical Research: Solid Earth},
    title = {A spatially variable power law tropospheric correction technique for {InSAR} data},
    year = {2015},
    month = {feb},
    number = {2},
    pages = {1345--1356},
    volume = {120},
    doi = {10.1002/2014jb011558},
    file = {:bekaertHooperWrightAGUJGR2015SpatiallyVariablePowerLawTroposphericCorrINSAR.pdf:PDF},
    keywords = {SAR Interferometry, Spatially-variable Correction, Power law model, Troposphere, APS, Estimation of APS, Atmospheric Phase Screen, Interferometry, Tropospheric Path Delay},
    owner = {ofrey},
    publisher = {American Geophysical Union ({AGU})},
    
    }
    


  7. David P.S. Bekaert, R.J. Walters, Tim J. Wright, Andrew J. Hooper, and D.J. Parker. Statistical comparison of InSAR tropospheric correction techniques. Remote Sensing of Environment, 170:40-47, December 2015. Keyword(s): SAR Interferometry, Atmosphere, Tropospheric Corrections, Phase-based Spectrometers, Weather models, InSAR, Interferometry.
    @Article{bekaertWaltersWrightHooperParkerRSE2015StatisticalComparisonOfTroposphericCorrectionTechniques,
    author = {David P.S. Bekaert and R.J. Walters and Tim J. Wright and Andrew J. Hooper and D.J. Parker},
    journal = {Remote Sensing of Environment},
    title = {Statistical comparison of {InSAR} tropospheric correction techniques},
    year = {2015},
    month = {dec},
    pages = {40--47},
    volume = {170},
    doi = {10.1016/j.rse.2015.08.035},
    file = {:bekaertWaltersWrightHooperParkerRSE2015StatisticalComparisonOfTroposphericCorrectionTechniques.pdf:PDF},
    keywords = {SAR Interferometry, Atmosphere, Tropospheric Corrections, Phase-based Spectrometers, Weather models, InSAR, Interferometry},
    owner = {ofrey},
    publisher = {Elsevier {BV}},
    
    }
    


  8. Silvia Bianchini, Andrea Ciampalini, Federico Raspini, Federica Bardi, Federico Di Traglia, Sandro Moretti, and Nicola Casagli. Multi-temporal evaluation of landslide movements and impacts on buildings in San Fratello (Italy) by means of C-band and X-band PSI data. Pure and Applied Geophysics, 172(11):3043-3065, 2015.
    @Article{bianchiniCiampaliniRaspiniBardiDiTragliaMorettiCasagli2015,
    author = {Bianchini, Silvia and Ciampalini, Andrea and Raspini, Federico and Bardi, Federica and Di Traglia, Federico and Moretti, Sandro and Casagli, Nicola},
    title = {Multi-temporal evaluation of landslide movements and impacts on buildings in {S}an {F}ratello ({I}taly) by means of {C}-band and {X}-band {PSI} data},
    journal = {Pure and Applied Geophysics},
    year = {2015},
    volume = {172},
    number = {11},
    pages = {3043--3065},
    owner = {ofrey},
    publisher = {Springer},
    
    }
    


  9. Rafael Caduff, Fritz Schlunegger, Andrew Kos, and Andreas Wiesmann. A review of terrestrial radar interferometry for measuring surface change in the geosciences. Earth Surface Processes and Landforms, 40(2):208-228, 2015. Keyword(s): SAR Processing, Gamma Portable Radar Interferometer, GPRI, Review, GBSAR, InSAR, Ground-based radar, Ground-based SAR, deformation measurement, displacement, subsidence, terrestrial radar interferometry, mass movements, surface deformation.
    Abstract: This paper presents a review of the current state of the art in the use of terrestrial radar interferometry for the detection of surface changes related to mass movement. Different hardware-types and acquisition concepts are described, which use either real or synthetic aperture for radar image formation. We present approaches for data processing procedures, paying special attention to the separation of high resolution displacement information from atmospheric phase variations. Recent case studies are used to illustrate applications in terrestrial radar interferometry for change detection. Applications range from detection and quantification of very slow moving (millimeters to centimeters per year) displacements in rock walls from repeat monitoring, to rapid processes resulting in fast displacements (~ 50 m/yr) acquired during single measurement campaigns with durations of only a few hours. Fast and episodic acting processes such as rockfall and snow avalanches can be assessed qualitatively in the spatial domain by mapping decorrelation caused by those processes. A concluding guide to best practice outlines the necessary preconditions that have to be fulfilled for successful application of the technique, as well as in areas characterized by rapid decorrelation. Empirical data from a Ku-band sensor show the range of temporal decorrelation of different surfaces after more than two years for rock-surfaces and after a few seconds to minutes in vegetated areas during windy conditions. The examples show that the displacement field can be measured for landslides in dense grassland, ice surfaces on flowing glaciers and snowpack creep. Copyright 2014 John Wiley and Sons, Ltd.

    @Article{caduffSchluneggerKosWiesmannESPL2014ReviewGBSARRADAR,
    author = {Caduff, Rafael and Schlunegger, Fritz and Kos, Andrew and Wiesmann, Andreas},
    title = {A review of terrestrial radar interferometry for measuring surface change in the geosciences},
    journal = {Earth Surface Processes and Landforms},
    year = {2015},
    volume = {40},
    number = {2},
    pages = {208-228},
    issn = {1096-9837},
    abstract = {This paper presents a review of the current state of the art in the use of terrestrial radar interferometry for the detection of surface changes related to mass movement. Different hardware-types and acquisition concepts are described, which use either real or synthetic aperture for radar image formation. We present approaches for data processing procedures, paying special attention to the separation of high resolution displacement information from atmospheric phase variations. Recent case studies are used to illustrate applications in terrestrial radar interferometry for change detection. Applications range from detection and quantification of very slow moving (millimeters to centimeters per year) displacements in rock walls from repeat monitoring, to rapid processes resulting in fast displacements (~ 50 m/yr) acquired during single measurement campaigns with durations of only a few hours. Fast and episodic acting processes such as rockfall and snow avalanches can be assessed qualitatively in the spatial domain by mapping decorrelation caused by those processes. A concluding guide to best practice outlines the necessary preconditions that have to be fulfilled for successful application of the technique, as well as in areas characterized by rapid decorrelation. Empirical data from a Ku-band sensor show the range of temporal decorrelation of different surfaces after more than two years for rock-surfaces and after a few seconds to minutes in vegetated areas during windy conditions. The examples show that the displacement field can be measured for landslides in dense grassland, ice surfaces on flowing glaciers and snowpack creep. Copyright 2014 John Wiley and Sons, Ltd.},
    doi = {10.1002/esp.3656},
    file = {:caduffSchluneggerKosWiesmannESPL2014ReviewGBSARRADAR.pdf:PDF},
    keywords = {SAR Processing, Gamma Portable Radar Interferometer, GPRI, Review, GBSAR, InSAR, Ground-based radar, Ground-based SAR, deformation measurement, displacement, subsidence, terrestrial radar interferometry, mass movements, surface deformation},
    pdf = {../../../docs/caduffSchluneggerKosWiesmannESPL2014ReviewGBSARRADAR.pdf},
    url = {http://dx.doi.org/10.1002/esp.3656},
    
    }
    


  10. Rafael Caduff, Andreas Wiesmann, Yves Bhler, and Christine Pielmeier. Continuous monitoring of snowpack displacement at high spatial and temporal resolution with terrestrial radar interferometry. Geophysical Research Letters, 42(3):813-820, 2015. Note: 2014GL062442. Keyword(s): GPRI-II, Remote sensing, Dynamics, Instruments and techniques, Monitoring, forecasting, prediction, Methods, terrestrial radar interferometry, remote sensing of snow, snowpack displacement monitoring, full-depth snow glide avalanche.
    @Article{caduffWiesmannBuehlerPielmeierGRL2015SnowGPRI,
    author = {Caduff, Rafael and Wiesmann, Andreas and B\"uhler, Yves and Pielmeier, Christine},
    title = {Continuous monitoring of snowpack displacement at high spatial and temporal resolution with terrestrial radar interferometry},
    journal = {Geophysical Research Letters},
    year = {2015},
    volume = {42},
    number = {3},
    pages = {813--820},
    issn = {1944-8007},
    note = {2014GL062442},
    doi = {10.1002/2014GL062442},
    file = {:caduffWiesmannBuehlerPielmeierGRL2015SnowGPRI.pdf:PDF},
    keywords = {GPRI-II, Remote sensing, Dynamics, Instruments and techniques, Monitoring, forecasting, prediction, Methods, terrestrial radar interferometry, remote sensing of snow, snowpack displacement monitoring, full-depth snow glide avalanche},
    pdf = {../../../docs/caduffWiesmannBuehlerPielmeierGRL2015SnowGPRI.pdf},
    url = {http://dx.doi.org/10.1002/2014GL062442},
    
    }
    


  11. Astor T. Caicoya, Matteo Pardini, Irena Hajnsek, and Konstantinos P. Papathanassiou. Forest Above-Ground Biomass Estimation From Vertical Reflectivity Profiles at L-Band. IEEE Geosci. Remote Sens. Lett., 12(12):2379-2383, December 2015. Keyword(s): SAR Processing, SAR Tomography, L-band, Capon, forestry, vegetation mapping, L-band reflectivity profiles, SAR tomography, forest above-ground biomass estimation, forest stand densities, height measurements, root-mean-square error, vertical forest structure information, vertical radar reflectivity profiles, vertical reflectivity profiles, Biomass, Estimation, Image color analysis, L-band, Remote sensing, Synthetic aperture radar, Forest allometry, L-band, forest biomass, synthetic aperture radar (SAR) tomography, vertical forest structure, vertical reflectivity profiles.
    Abstract: Forest height is an important parameter for the allometric estimation of above-ground forest biomass (AGB). However, variable forest stand densities limit the performance of the allometric estimation of AGB from height measurements alone. Recently, the use of vertical forest structure information as an indicator for the variation of stand density has been proposed and used to improve the allometric estimation of AGB from height measurements. In this letter, the use of vertical radar reflectivity profiles at L-band obtained from SAR tomography, as a proxy for vertical forest structure for the allometric estimation of AGB, is investigated. L-band reflectivity profiles, which are reconstructed from data at different polarizations (HH and HV) and acquired under moist and dry weather conditions, are investigated. The proposed allometric AGB estimator increases the correlation factor from 0.60 to 0.81 and reduces the root-mean-square error from 50.25 to 36.30 Mg/ha when compared with the AGB estimation from forest height alone. The effect of polarization and weather conditions on the AGB estimation performance is discussed.

    @Article{caicoyaPardiniHajnsekPapathanassiouGRSL2015TomoLBandBiomass,
    author = {Caicoya, Astor T. and Pardini, Matteo and Hajnsek, Irena and Papathanassiou, Konstantinos P.},
    title = {Forest Above-Ground Biomass Estimation From Vertical Reflectivity Profiles at {L-}Band},
    journal = {IEEE Geosci. Remote Sens. Lett.},
    year = {2015},
    volume = {12},
    number = {12},
    pages = {2379-2383},
    month = dec,
    issn = {1545-598X},
    abstract = {Forest height is an important parameter for the allometric estimation of above-ground forest biomass (AGB). However, variable forest stand densities limit the performance of the allometric estimation of AGB from height measurements alone. Recently, the use of vertical forest structure information as an indicator for the variation of stand density has been proposed and used to improve the allometric estimation of AGB from height measurements. In this letter, the use of vertical radar reflectivity profiles at L-band obtained from SAR tomography, as a proxy for vertical forest structure for the allometric estimation of AGB, is investigated. L-band reflectivity profiles, which are reconstructed from data at different polarizations (HH and HV) and acquired under moist and dry weather conditions, are investigated. The proposed allometric AGB estimator increases the correlation factor from 0.60 to 0.81 and reduces the root-mean-square error from 50.25 to 36.30 Mg/ha when compared with the AGB estimation from forest height alone. The effect of polarization and weather conditions on the AGB estimation performance is discussed.},
    doi = {10.1109/LGRS.2015.2477858},
    file = {:caicoyaPardiniHajnsekPapathanassiouGRSL2015TomoLBandBiomass.pdf:PDF},
    keywords = {SAR Processing, SAR Tomography, L-band, Capon, forestry;vegetation mapping;L-band reflectivity profiles;SAR tomography;forest above-ground biomass estimation;forest stand densities;height measurements;root-mean-square error;vertical forest structure information;vertical radar reflectivity profiles;vertical reflectivity profiles;Biomass;Estimation;Image color analysis;L-band;Remote sensing;Synthetic aperture radar;Forest allometry;L-band;forest biomass;synthetic aperture radar (SAR) tomography;vertical forest structure;vertical reflectivity profiles},
    owner = {ofrey},
    pdf = {../../../docs/caicoyaPardiniHajnsekPapathanassiouGRSL2015TomoLBandBiomass},
    
    }
    


  12. Ning Cao, Hyongki Lee, and H. C. Jung. Mathematical Framework for Phase-Triangulation Algorithms in Distributed-Scatterer Interferometry. IEEE Geoscience and Remote Sensing Letters, 12(9):1838-1842, Sept 2015. Keyword(s): geophysical techniques, mathematical analysis, maximum likelihood estimation, phase estimation, radar interferometry, DS interferometry procedure, coherence-weighted PT, distributed-scatterer interferometry, eigendecomposition-based phase estimator, equal-weighted PT, estimation procedure weight value, least square estimator, mathematical framework, mathematical relation analysis, maximum-likelihood phase estimator, modified PT algorithm, persistent-scatterer interferometry measurement point, phase-triangulation algorithm, published PT method, Coherence, Covariance matrices, Interferometry, Maximum likelihood estimation, Remote sensing, Synthetic aperture radar, Differential interferometric synthetic aperture radar (DInSAR), distributed scatterer (DS) interferometry, persistent scatterer (PS) interferometry (PSI), phase triangulation (PT), synthetic aperture radar (SAR).
    Abstract: To improve the spatial density of measurement points of persistent-scatterer interferometry, distributed scatterer (DS) should be considered and processed. An important procedure in DS interferometry is the phase triangulation (PT). This letter introduces two modified PT algorithms (i.e., equal-weighted PT and coherence-weighted PT) and analyzes the mathematical relations between different published PT methods (i.e., the maximum-likelihood phase estimator, least squares estimator, and eigendecomposition-based phase estimators). The analysis shows that the above five PT methods share very similar mathematical forms with different weight values in the estimation procedure.

    @Article{caoLeeJungGRSL2015FrameworkForPhaseTriangulationDSInSAR,
    author = {Ning Cao and Hyongki Lee and H. C. Jung},
    title = {Mathematical Framework for Phase-Triangulation Algorithms in Distributed-Scatterer Interferometry},
    journal = {IEEE Geoscience and Remote Sensing Letters},
    year = {2015},
    volume = {12},
    number = {9},
    month = {Sept},
    pages = {1838-1842},
    issn = {1545-598X},
    doi = {10.1109/LGRS.2015.2430752},
    abstract = {To improve the spatial density of measurement points of persistent-scatterer interferometry, distributed scatterer (DS) should be considered and processed. An important procedure in DS interferometry is the phase triangulation (PT). This letter introduces two modified PT algorithms (i.e., equal-weighted PT and coherence-weighted PT) and analyzes the mathematical relations between different published PT methods (i.e., the maximum-likelihood phase estimator, least squares estimator, and eigendecomposition-based phase estimators). The analysis shows that the above five PT methods share very similar mathematical forms with different weight values in the estimation procedure.},
    keywords = {geophysical techniques;mathematical analysis;maximum likelihood estimation;phase estimation;radar interferometry;DS interferometry procedure;coherence-weighted PT;distributed-scatterer interferometry;eigendecomposition-based phase estimator;equal-weighted PT;estimation procedure weight value;least square estimator;mathematical framework;mathematical relation analysis;maximum-likelihood phase estimator;modified PT algorithm;persistent-scatterer interferometry measurement point;phase-triangulation algorithm;published PT method;Coherence;Covariance matrices;Interferometry;Maximum likelihood estimation;Remote sensing;Synthetic aperture radar;Differential interferometric synthetic aperture radar (DInSAR);distributed scatterer (DS) interferometry;persistent scatterer (PS) interferometry (PSI);phase triangulation (PT);synthetic aperture radar (SAR)},
    owner = {ofrey},
    
    }
    


  13. F. De Zan, P. Prats-Iraola, and M. Rodriguez-Cassola. On the Dependence of Delta-k Efficiency on Multilooking. IEEE Geoscience and Remote Sensing Letters, 12(8):1745-1749, August 2015. Keyword(s): estimation theory, radar imaging, radar interferometry, synthetic aperture radar, delta-k method, synthetic aperture radar imaging, differential interferogram, multilooking, interferometric fringe, incoherent cross-correlation, Synthetic aperture radar, Bandwidth, Correlation, Estimation, Coherence, Remote sensing, Interferometry, Delay estimation, Delta-k, synthetic aperture radar (SAR), synthetic aperture radar interferometry, Delay estimation, Delta-k, synthetic aperture radar (SAR), synthetic aperture radar interferometry.
    Abstract: This letter discusses some aspects of the implementation of Delta-k methods for shift estimation with synthetic aperture radar images. In particular, it shows that a common Delta-k algorithm, which postpones the multilooking to the differential interferogram and is therefore robust to the presence of interferometric fringes in the averaging window, does not reach the maximum possible performance and should be better considered as a variant of incoherent cross-correlation. A small adaptation, retaining some multilooking at interferogram level, can significantly improve the efficiency.

    @Article{7102710,
    author = {F. {De Zan} and P. {Prats-Iraola} and M. {Rodriguez-Cassola}},
    title = {On the Dependence of Delta-k Efficiency on Multilooking},
    journal = {IEEE Geoscience and Remote Sensing Letters},
    year = {2015},
    volume = {12},
    number = {8},
    pages = {1745-1749},
    month = {Aug},
    issn = {1558-0571},
    abstract = {This letter discusses some aspects of the implementation of Delta-k methods for shift estimation with synthetic aperture radar images. In particular, it shows that a common Delta-k algorithm, which postpones the multilooking to the differential interferogram and is therefore robust to the presence of interferometric fringes in the averaging window, does not reach the maximum possible performance and should be better considered as a variant of incoherent cross-correlation. A small adaptation, retaining some multilooking at interferogram level, can significantly improve the efficiency.},
    doi = {10.1109/LGRS.2015.2424272},
    keywords = {estimation theory;radar imaging;radar interferometry;synthetic aperture radar;delta-k method;synthetic aperture radar imaging;differential interferogram;multilooking;interferometric fringe;incoherent cross-correlation;Synthetic aperture radar;Bandwidth;Correlation;Estimation;Coherence;Remote sensing;Interferometry;Delay estimation;Delta-k;synthetic aperture radar (SAR);synthetic aperture radar interferometry;Delay estimation;Delta-k;synthetic aperture radar (SAR);synthetic aperture radar interferometry},
    owner = {ofrey},
    
    }
    


  14. Michael I. Duersch and David G. Long. Analysis of Multistatic Pixel Correlation in SAR. IEEE Transactions on Geoscience and Remote Sensing, 53(1):362-374, January 2015. Keyword(s): MIMO radar, correlation methods, image resolution, radar imaging, radar receivers, radar transmitters, synthetic aperture radar, MIMO technique, SAR, collocated array category, distributed array category, geometric correlation calculation, ground-plane image formation, multiple-input multiple-output technique, multistatic pixel correlation analysis, pixel image resolution, receiver-transmitter pair, synthetic aperture radar, wireless communication, Correlation, MIMO, Receiving antennas, Synthetic aperture radar, Backprojection, multiple-input multiple-output (MIMO), multistatic radar, synthetic aperture radar (SAR).
    Abstract: The field of wireless communications has benefited from multiple-input and multiple-output (MIMO) techniques. As researchers seek to apply MIMO (multistatic) techniques to radar and specifically to synthetic aperture radar (SAR), a key factor in determining MIMO application and performance is the level of correlation of signals from different receiver/transmitter pairs. The level of correlation determines whether a MIMO array falls into the category of a collocated array or a distributed array. The type of array dramatically affects which MIMO techniques may be performed and what advantages MIMO offers from conventional techniques. This paper presents models for calculating geometric correlation of multistatic SAR pixels using a ground-plane image formation. The models' results are compared to previous correlation models found in literature. A key result is that correlation depends on pixel resolution and not the number of individual scatterers. This paper concludes that most MIMO arrays operating on a single platform operate in the collocated regime.

    @Article{duerschLongTGARS2015MultistaticPixelCorrelation,
    author = {Michael I. Duersch and David G. Long},
    title = {Analysis of Multistatic Pixel Correlation in SAR},
    journal = {IEEE Transactions on Geoscience and Remote Sensing},
    year = {2015},
    volume = {53},
    number = {1},
    pages = {362-374},
    month = jan,
    issn = {0196-2892},
    abstract = {The field of wireless communications has benefited from multiple-input and multiple-output (MIMO) techniques. As researchers seek to apply MIMO (multistatic) techniques to radar and specifically to synthetic aperture radar (SAR), a key factor in determining MIMO application and performance is the level of correlation of signals from different receiver/transmitter pairs. The level of correlation determines whether a MIMO array falls into the category of a collocated array or a distributed array. The type of array dramatically affects which MIMO techniques may be performed and what advantages MIMO offers from conventional techniques. This paper presents models for calculating geometric correlation of multistatic SAR pixels using a ground-plane image formation. The models' results are compared to previous correlation models found in literature. A key result is that correlation depends on pixel resolution and not the number of individual scatterers. This paper concludes that most MIMO arrays operating on a single platform operate in the collocated regime.},
    doi = {10.1109/TGRS.2014.2322611},
    file = {:duerschLongTGARS2015MultistaticPixelCorrelation.pdf:PDF},
    keywords = {MIMO radar;correlation methods;image resolution;radar imaging;radar receivers;radar transmitters;synthetic aperture radar;MIMO technique;SAR;collocated array category;distributed array category;geometric correlation calculation;ground-plane image formation;multiple-input multiple-output technique;multistatic pixel correlation analysis;pixel image resolution;receiver-transmitter pair;synthetic aperture radar;wireless communication;Correlation;MIMO;Receiving antennas;Synthetic aperture radar;Backprojection;multiple-input multiple-output (MIMO);multistatic radar;synthetic aperture radar (SAR)},
    owner = {ofrey},
    
    }
    


  15. Michael I. Duersch and David G. Long. Analysis of time-domain back-projection for stripmap SAR. International Journal of Remote Sensing, 36(8):2010-2036, 2015. Keyword(s): SAR Processing, FMCW, Time-Domain Back-Projection, TDBP, LFMCW, Azimuth Focusing, Motion Compensation, Interferometry, SAR Interferometry, Airborne SAR.
    Abstract: This article explores the SAR back-projection algorithm for stripmap image formationand its characteristics. The article provides a derivation of generalized time-domain back-projection from first principles. It shows that back-projection may be considered an ideal matched filter for SAR. The article presents an analysis of the sensitivity of back-projection to its geometric parameters as well as several performance considerations: azimuth beam width, residual phase error, digital elevation map accuracy, and antenna position estimation accuracy.

    @Article{duerschLongIJRS2015TDBPforStripmapSAR,
    author = {Duersch, Michael I. and Long, David G.},
    title = {Analysis of time-domain back-projection for stripmap {SAR}},
    journal = {International Journal of Remote Sensing},
    year = {2015},
    volume = {36},
    number = {8},
    pages = {2010-2036},
    abstract = {This article explores the SAR back-projection algorithm for stripmap image formationand its characteristics. The article provides a derivation of generalized time-domain back-projection from first principles. It shows that back-projection may be considered an ideal matched filter for SAR. The article presents an analysis of the sensitivity of back-projection to its geometric parameters as well as several performance considerations: azimuth beam width, residual phase error, digital elevation map accuracy, and antenna position estimation accuracy.},
    doi = {10.1080/01431161.2015.1030044},
    file = {:duerschLongIJRS2015TDBPforStripmapSAR.pdf:PDF},
    keywords = {SAR Processing, FMCW, Time-Domain Back-Projection, TDBP, LFMCW, Azimuth Focusing, Motion Compensation, Interferometry, SAR Interferometry, Airborne SAR},
    owner = {ofrey},
    publisher = {Taylor Francis},
    url = {https://doi.org/10.1080/01431161.2015.1030044},
    
    }
    


  16. Michael I. Duersch and David G. Long. Backprojection SAR interferometry. International Journal of Remote Sensing, 36(4):979-999, 2015. Keyword(s): SAR Processing, FMCW, Time-Domain Back-Projection, TDBP, LFMCW, Azimuth Focusing, Motion Compensation, Interferometry, SAR Interferometry, Airborne SAR.
    Abstract: Synthetic aperture radar (SAR) interferometry uses the phase difference between two SAR antennas to obtain an elevation estimate of the imaged terrain. Using an initial digital elevation model (DEM), the time-domain backprojection algorithm implicitly removes the terrain height phase from images during image formation. The use of a DEM during image formation adds additional information to the process of interferometry, resulting in different sensitivities to conventional interferometry. This article presents a novel method of SAR interferometry using backprojected imagery. It is shown that the sensitivity and performance of backprojection interferometry is significantly different to that of conventional methods. Specifically, it is shown that backprojection interferometry is much less sensitive to errors in measurement of the interferometric baseline length and angle. This comes at the expense of higher sensitivity to phase errors. We conclude that backprojection interferometry is best suited for airborne operation.

    @Article{duerschLongIJRS2015BackprojectionSARInterferometry,
    author = {Duersch, Michael I. and Long, David G.},
    title = {Backprojection SAR interferometry},
    journal = {International Journal of Remote Sensing},
    year = {2015},
    volume = {36},
    number = {4},
    pages = {979-999},
    abstract = {Synthetic aperture radar (SAR) interferometry uses the phase difference between two SAR antennas to obtain an elevation estimate of the imaged terrain. Using an initial digital elevation model (DEM), the time-domain backprojection algorithm implicitly removes the terrain height phase from images during image formation. The use of a DEM during image formation adds additional information to the process of interferometry, resulting in different sensitivities to conventional interferometry. This article presents a novel method of SAR interferometry using backprojected imagery. It is shown that the sensitivity and performance of backprojection interferometry is significantly different to that of conventional methods. Specifically, it is shown that backprojection interferometry is much less sensitive to errors in measurement of the interferometric baseline length and angle. This comes at the expense of higher sensitivity to phase errors. We conclude that backprojection interferometry is best suited for airborne operation.},
    doi = {10.1080/01431161.2014.1001087},
    file = {:duerschLongIJRS2015BackprojectionSARInterferometry.pdf:PDF},
    keywords = {SAR Processing, FMCW, Time-Domain Back-Projection, TDBP, LFMCW, Azimuth Focusing, Motion Compensation, Interferometry, SAR Interferometry, Airborne SAR},
    owner = {ofrey},
    publisher = {Taylor \& Francis},
    url = {http://www.tandfonline.com/doi/abs/10.1080/01431161.2014.1001087},
    
    }
    


  17. Alexander G. Fore, Bruce D. Chapman, Brian P. Hawkins, Scott Hensley, Cathleen E. Jones, Thierry R. Michel, and Ronald J. Muellerschoen. UAVSAR Polarimetric Calibration. IEEE Trans. Geosci. Remote Sens., 53(6):3481-3491, June 2015. Keyword(s): SAR Processing, UAVSAR, Airborne SAR, Polarimetry, Polarimetric Calibration, calibration, radar polarimetry, remote sensing by radar, synthetic aperture radar, UAVSAR polarimetric calibration, UAVSAR radar performance, airborne repeat-track SAR data, interferometric measurements, quadpolarization mode, radiometric calibration, reconfigurable polarimetric L-band SAR, residual RMS errors, root-mean-square, stable crosstalk estimates, uninhabited aerial vehicle synthetic aperture radar, Azimuth, Calibration, Crosstalk, Image resolution, Radiometry, Synthetic aperture radar, Airborne radar, polarimetric SAR, radar cross-sections, radar imaging, radar measurements, radar polarimetry, radar remote sensing, synthetic aperture radar (SAR).
    Abstract: Uninhabited aerial vehicle synthetic aperture radar (UAVSAR) is a reconfigurable polarimetric L-band SAR that operates in quad-polarization mode and is specifically designed to acquire airborne repeat-track SAR data for interferometric measurements. In this paper, we present details of the UAVSAR radar performance, the radiometric calibration, and the polarimetric calibration. For the radiometric calibration, we employ an array of trihedral corner reflectors, as well as distributed targets. We show that UAVSAR is a well-calibrated SAR system for polarimetric applications, with absolute radiometric calibration bias better than 1 dB, residual root-mean-square (RMS) errors of ~0.7 dB, and RMS phase errors ~5.3 deg. For the polarimetric calibration, we have evaluated the methods of Quegan and Ainsworth et al. for crosstalk calibration and find that the method of Quegan gives crosstalk estimates that depend on target type, whereas the method of Ainsworth et al. gives more stable crosstalk estimates. We find that both methods estimate leakage of the copolarizations into the cross-polarizations to be on the order of -30 dB.

    @Article{foreChapmanHawkinsHensleyJonesMichelMuellerschoenTGRS2015UAVSARPolCalibration,
    author = {Fore, Alexander G. and Chapman, Bruce D. and Hawkins, Brian P. and Hensley, Scott and Jones, Cathleen E. and Michel, Thierry R. and Muellerschoen, Ronald J.},
    title = {{UAVSAR} Polarimetric Calibration},
    journal = {IEEE Trans. Geosci. Remote Sens.},
    year = {2015},
    volume = {53},
    number = {6},
    pages = {3481-3491},
    month = jun,
    issn = {0196-2892},
    abstract = {Uninhabited aerial vehicle synthetic aperture radar (UAVSAR) is a reconfigurable polarimetric L-band SAR that operates in quad-polarization mode and is specifically designed to acquire airborne repeat-track SAR data for interferometric measurements. In this paper, we present details of the UAVSAR radar performance, the radiometric calibration, and the polarimetric calibration. For the radiometric calibration, we employ an array of trihedral corner reflectors, as well as distributed targets. We show that UAVSAR is a well-calibrated SAR system for polarimetric applications, with absolute radiometric calibration bias better than 1 dB, residual root-mean-square (RMS) errors of ~0.7 dB, and RMS phase errors ~5.3 deg. For the polarimetric calibration, we have evaluated the methods of Quegan and Ainsworth et al. for crosstalk calibration and find that the method of Quegan gives crosstalk estimates that depend on target type, whereas the method of Ainsworth et al. gives more stable crosstalk estimates. We find that both methods estimate leakage of the copolarizations into the cross-polarizations to be on the order of -30 dB.},
    doi = {10.1109/TGRS.2014.2377637},
    file = {:foreChapmanHawkinsHensleyJonesMichelMuellerschoenTGRS2015UAVSARPolCalibration.pdf:PDF},
    keywords = {SAR Processing, UAVSAR, Airborne SAR, Polarimetry, Polarimetric Calibration, calibration;radar polarimetry;remote sensing by radar;synthetic aperture radar;UAVSAR polarimetric calibration;UAVSAR radar performance;airborne repeat-track SAR data;interferometric measurements;quadpolarization mode;radiometric calibration;reconfigurable polarimetric L-band SAR;residual RMS errors;root-mean-square;stable crosstalk estimates;uninhabited aerial vehicle synthetic aperture radar;Azimuth;Calibration;Crosstalk;Image resolution;Radiometry;Synthetic aperture radar;Airborne radar;polarimetric SAR;radar cross-sections;radar imaging;radar measurements;radar polarimetry;radar remote sensing;synthetic aperture radar (SAR)},
    pdf = {../../../docs/foreChapmanHawkinsHensleyJonesMichelMuellerschoenTGRS2015UAVSARPolCalibration.pdf},
    
    }
    


  18. Gianfranco Fornaro, Simona Verde, Diego Reale, and Antonio Pauciullo. CAESAR: An Approach Based on Covariance Matrix Decomposition to Improve Multibaseline - Multitemporal Interferometric SAR Processing. IEEE Trans. Geosci. Remote Sens., 53(4):2050-2065, April 2015. Keyword(s): SAR Processing, SAR Tomography, Component Extraction And selection SAR, CEASAR, Spaceborne SAR, multilook SAR tomography, X-Band, Urban, Persistent Scatterer Interferometry, PSI, covariance matrices, geophysical signal processing, matrix decomposition, principal component analysis, radar interferometry, radar signal processing, remote sensing by radar, synthetic aperture radar, tomography, CAESAR, Component Extraction and Selection SAR algorithm, SAR tomography, SqueeSAR, classical interferometric processing, coherence losses, covariance matrix analysis, covariance matrix decomposition, data covariance matrix, equivalent scattering mechanisms, ground deformation monitoring, high resolution Cosmo-SkyMed data, high resolution interferometric SAR sensors, interferometic stac filtering, multibaseline-multitemporal interferometric SAR processing, multilook operation, multiple scatterers, principal component analysis, synthetic aperture radar, Covariance matrices, Interferometry, Monitoring, Scattering, Spatial resolution, Synthetic aperture radar, Tomography, 3-D, 4-D and multidimensional (Multi-D) SAR imaging, Covariance matrix decomposition, SAR interferometry (InSAR), SAR tomography.
    Abstract: Synthetic aperture radar (SAR) tomography has been strongly developed in the last years for the analysis at fine scale of data acquired by high-resolution interferometric SAR sensors as a technique alternative to classical persistent scatterer interferometry and able to resolve also multiple scatterers. SqueeSAR is a recently proposed solution which, in the context of SAR interferometry at the coarse scale analysis stage, allows taking advantage of the multilook operation to filter interferometic stacks by extracting, pixel by pixel, equivalent scattering mechanisms from the set of all available interferometric measurement collected in the data covariance matrix. In this paper, we investigate the possibilities to extend SqueeSAR by allowing the identification of multiple scattering mechanisms from the analysis of the covariance matrix. In particular, we present a new approach, named Component extrAction and sElection SAR algorithm, that allows taking advantage of the principal component analysis to filter interferograms relevant to the decorrelating scatterer, i.e., scatterers that may exhibit coherence losses depending on the spatial and temporal baseline distributions, and to detect and separate scattering mechanisms possibly interfering in the same pixel due to layover directly at the interferogram generation stage. The proposed module allows providing options useful for classical interferometric processing to monitor ground deformations at lower resolution (coarse scale), as well as for possibly aiding the data calibration preliminary for the subsequent full-resolution interferometric/tomographic (fine scale) analysis. Results achieved by processing high-resolution Cosmo-SkyMed data, characterized by the favorable features of a large baseline span, are presented to explain the advantages and validate this new interferometric processing solution.

    @Article{fornaroVerdeRealePauciulloTGRS2014TomoCAESAR,
    author = {Fornaro, Gianfranco and Verde, Simona and Reale, Diego and Pauciullo, Antonio},
    title = {{CAESAR}: An Approach Based on Covariance Matrix Decomposition to Improve Multibaseline - Multitemporal Interferometric {SAR} Processing},
    journal = {IEEE Trans. Geosci. Remote Sens.},
    year = {2015},
    volume = {53},
    number = {4},
    pages = {2050-2065},
    month = apr,
    issn = {0196-2892},
    abstract = {Synthetic aperture radar (SAR) tomography has been strongly developed in the last years for the analysis at fine scale of data acquired by high-resolution interferometric SAR sensors as a technique alternative to classical persistent scatterer interferometry and able to resolve also multiple scatterers. SqueeSAR is a recently proposed solution which, in the context of SAR interferometry at the coarse scale analysis stage, allows taking advantage of the multilook operation to filter interferometic stacks by extracting, pixel by pixel, equivalent scattering mechanisms from the set of all available interferometric measurement collected in the data covariance matrix. In this paper, we investigate the possibilities to extend SqueeSAR by allowing the identification of multiple scattering mechanisms from the analysis of the covariance matrix. In particular, we present a new approach, named Component extrAction and sElection SAR algorithm, that allows taking advantage of the principal component analysis to filter interferograms relevant to the decorrelating scatterer, i.e., scatterers that may exhibit coherence losses depending on the spatial and temporal baseline distributions, and to detect and separate scattering mechanisms possibly interfering in the same pixel due to layover directly at the interferogram generation stage. The proposed module allows providing options useful for classical interferometric processing to monitor ground deformations at lower resolution (coarse scale), as well as for possibly aiding the data calibration preliminary for the subsequent full-resolution interferometric/tomographic (fine scale) analysis. Results achieved by processing high-resolution Cosmo-SkyMed data, characterized by the favorable features of a large baseline span, are presented to explain the advantages and validate this new interferometric processing solution.},
    doi = {10.1109/TGRS.2014.2352853},
    file = {:fornaroVerdeRealePauciulloTGRS2014TomoCAESAR.pdf:PDF},
    keywords = {SAR Processing, SAR Tomography, Component Extraction And selection SAR, CEASAR, Spaceborne SAR, multilook SAR tomography, X-Band, Urban, Persistent Scatterer Interferometry, PSI,covariance matrices;geophysical signal processing;matrix decomposition;principal component analysis;radar interferometry;radar signal processing;remote sensing by radar;synthetic aperture radar;tomography;CAESAR;Component Extraction and Selection SAR algorithm;SAR tomography;SqueeSAR;classical interferometric processing;coherence losses;covariance matrix analysis;covariance matrix decomposition;data covariance matrix;equivalent scattering mechanisms;ground deformation monitoring;high resolution Cosmo-SkyMed data;high resolution interferometric SAR sensors;interferometic stac filtering;multibaseline-multitemporal interferometric SAR processing;multilook operation;multiple scatterers;principal component analysis;synthetic aperture radar;Covariance matrices;Interferometry;Monitoring;Scattering;Spatial resolution;Synthetic aperture radar;Tomography;3-D;4-D and multidimensional (Multi-D) SAR imaging;Covariance matrix decomposition;SAR interferometry (InSAR);SAR tomography;differential SAR tomography;differential synthetic aperture radar (SAR) interferometry (DInSAR);principal component analysis (PCA)},
    pdf = {../../../docs/fornaroVerdeRealePauciulloTGRS2014TomoCAESAR.pdf},
    
    }
    


  19. Roy E. Hansen, A. P. Lyons, T. O. S�b�, H. J. Callow, and D. A. Cook. The Effect of Internal Wave-Related Features on Synthetic Aperture Sonar. IEEE Journal of Oceanic Engineering, 40(3):621-631, July 2015. Keyword(s): Synthetic Aperture Sonar, SAS, autonomous underwater vehicles, bathymetry, oceanographic techniques, sonar imaging, synthetic aperture sonar, (AUV), CMRE, Centre for Maritime Research and Experimentation, Elba Island Italy, FFI, HUGIN autonomous underwater vehicle, Kjeller Norway, La Spezia Italy, NATO research vessel, Norwegian Defence Research Establishment, RV, SAS bathymetry, SAS imaging, acoustical ray model, bolus, interferometric synthetic aperture sonar, internal wave-related feature effect, moving target analysis, multiaperture processing, multilook processing, repeat pass imaging, seabed topography, sound-speed structure, water column, Geometry, Imaging, Interferometry, Shape, Surfaces, Synthetic aperture sonar, Internal waves, refraction effects, synthetic aperture sonar.
    Abstract: In October 2012, the Centre for Maritime Research and Experimentation (CMRE, La Spezia, Italy) conducted trials from the NATO research vessel (RV) Alliance, off Elba Island, Italy. During this trial, data were collected by the Norwegian Defence Research Establishment (FFI, Kjeller, Norway) using a HUGIN autonomous underwater vehicle (AUV) with interferometric synthetic aperture sonar (SAS) in repeated passes. Large linear structures (tens of meters by several meters) observed in both the SAS images and SAS bathymetry during the initial pass were absent in data taken on a repeated pass the following day. We suggest that these phenomena were not true seafloor features, but were caused by features in the water column, known as boluses, which can form after breaking internal wave events. The changes observed in acoustical intensity and phase appear to be caused by the interaction of the acoustical field with the lower average sound-speed structure of the bolus, constructing features in both SAS imagery and SAS bathymetry that looked like seabed topography. In this paper, we present examples and give an interpretation of the results based on an acoustical ray model. We discuss different techniques for recognizing these phenomena: repeat pass imaging and interferometry, multilook and multiaperture processing, and moving target analysis.

    @Article{hansenLyonsSaeboCallowCookJOE2015EffectOfInternalWavesOnSAS,
    author = {Roy E. Hansen and A. P. Lyons and T. O. S�b� and H. J. Callow and D. A. Cook},
    title = {The Effect of Internal Wave-Related Features on Synthetic Aperture Sonar},
    journal = {IEEE Journal of Oceanic Engineering},
    year = {2015},
    volume = {40},
    number = {3},
    pages = {621-631},
    month = {July},
    issn = {0364-9059},
    abstract = {In October 2012, the Centre for Maritime Research and Experimentation (CMRE, La Spezia, Italy) conducted trials from the NATO research vessel (RV) Alliance, off Elba Island, Italy. During this trial, data were collected by the Norwegian Defence Research Establishment (FFI, Kjeller, Norway) using a HUGIN autonomous underwater vehicle (AUV) with interferometric synthetic aperture sonar (SAS) in repeated passes. Large linear structures (tens of meters by several meters) observed in both the SAS images and SAS bathymetry during the initial pass were absent in data taken on a repeated pass the following day. We suggest that these phenomena were not true seafloor features, but were caused by features in the water column, known as boluses, which can form after breaking internal wave events. The changes observed in acoustical intensity and phase appear to be caused by the interaction of the acoustical field with the lower average sound-speed structure of the bolus, constructing features in both SAS imagery and SAS bathymetry that looked like seabed topography. In this paper, we present examples and give an interpretation of the results based on an acoustical ray model. We discuss different techniques for recognizing these phenomena: repeat pass imaging and interferometry, multilook and multiaperture processing, and moving target analysis.},
    doi = {10.1109/JOE.2014.2340351},
    file = {:hansenLyonsSaeboCallowCookJOE2015EffectOfInternalWavesOnSAS.pdf:PDF},
    keywords = {Synthetic Aperture Sonar, SAS,autonomous underwater vehicles;bathymetry;oceanographic techniques;sonar imaging;synthetic aperture sonar;(AUV);CMRE;Centre for Maritime Research and Experimentation;Elba Island Italy;FFI;HUGIN autonomous underwater vehicle;Kjeller Norway;La Spezia Italy;NATO research vessel;Norwegian Defence Research Establishment;RV;SAS bathymetry;SAS imaging;acoustical ray model;bolus;interferometric synthetic aperture sonar;internal wave-related feature effect;moving target analysis;multiaperture processing;multilook processing;repeat pass imaging;seabed topography;sound-speed structure;water column;Geometry;Imaging;Interferometry;Shape;Surfaces;Synthetic aperture sonar;Internal waves;refraction effects;synthetic aperture sonar},
    
    }
    


  20. R. Iglesias, A. Aguasca, X. Fabregas, J. J. Mallorqui, D. Monells, C. Lopez-Martinez, and L. Pipia. Ground-Based Polarimetric SAR Interferometry for the Monitoring of Terrain Displacement Phenomena - Part I: Theoretical Description. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8(3):980-993, March 2015. Keyword(s): geomorphology, radar interferometry, remote sensing by radar, synthetic aperture radar, terrain mapping, GB-InSAR techniques, GB-SAR sensors, PSI processing chains, PSI techniques, PolInSAR algorithms, PolSAR measurements, SLFMCW GB-SAR system, SLFMCW signals, Universitat Politecnica de Catalunya, acquisition time, classical single-polarimetric performances, coherent pixels technique, ground displacement episodes, ground displacement phenomena, ground-based SAR interferometry, ground-based polarimetric SAR interferometry, ground-based synthetic aperture radar, persistent scatterer interferomerty, polarimetric RiskSAR sensor, polarimetric SAR measurements, stepped linear frequency modulated continuous wave, terrain displacement phenomena monitoring, troposphere medium decorrelation, troposphere temporal homogeneity, vector network analyzers, Atmospheric measurements, Interferometry, Monitoring, Sensor phenomena and characterization, Synthetic aperture radar, Differential synthetic aperture radar (SAR) interferometry (DInSAR), GB-SAR interferometry (GB-InSAR), frequency modulated continuous wave (FMCW) radar, ground-based SAR (GB-SAR), persistent scatterer interferomerty (PSI), polarimetric SAR interferometry (PolInSAR), stepped linear FMCW (SLFMCW) radar.
    Abstract: Ground-based synthetic aperture radar (SAR) (GB-SAR) sensors represent an effective solution for the monitoring of ground displacement episodes. Initially, the most GB-SAR sensors were based on vector network analyzers (VNA). This type of solution, characterized by a slow scanning time comparable to the decorrelation of the troposphere medium, compromised in many cases the quality of final products for the application of persistent scatterer interferomerty (PSI) techniques. The development of GB-SAR sensors based on the use of stepped linear frequency modulated continuous wave (SLFMCW) signals has led to significant improvements during the last years. They have allowed fulfilling the need of temporal homogeneity of the troposphere during the acquisition time and, moreover, they have favored the acquisition of reliable polarimetric SAR (PolSAR) measurements without drastically increasing the scanning time. This fact has boosted the inclusion of polarimetric SAR interferometry (PolInSAR) algorithms in PSI processing chains, which are demonstrating to outperform classical single-polarimetric performances. The objective of this paper is twofold. On the one hand, a general overview of the polarimetric RiskSAR sensor, developed by the Universitat Polit�cnica de Catalunya (UPC), is put forward as an example of SLFMCW GB-SAR system implementation. On the other hand, a complete theoretical description of ground-based SAR (GB-SAR) interferometry (GB-InSAR) techniques for PSI purposes is widely discussed. The adaptation of the Coherent Pixels Technique to obtain the linear and nonlinear components of ground displacement phenomena is proposed. In the second part of this paper, the displacement maps and time series over two very different scenarios are presented in order to show the feasibility of GB-SAR sensors for terrain displacement monitoring applications.

    @Article{iglesiasEtAlJSTARS2015GBSARDisplacementPart1Theory,
    author = {R. Iglesias and A. Aguasca and X. Fabregas and J. J. Mallorqui and D. Monells and C. Lopez-Martinez and L. Pipia},
    journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
    title = {Ground-Based Polarimetric SAR Interferometry for the Monitoring of Terrain Displacement Phenomena - Part I: Theoretical Description},
    year = {2015},
    issn = {1939-1404},
    month = mar,
    number = {3},
    pages = {980-993},
    volume = {8},
    abstract = {Ground-based synthetic aperture radar (SAR) (GB-SAR) sensors represent an effective solution for the monitoring of ground displacement episodes. Initially, the most GB-SAR sensors were based on vector network analyzers (VNA). This type of solution, characterized by a slow scanning time comparable to the decorrelation of the troposphere medium, compromised in many cases the quality of final products for the application of persistent scatterer interferomerty (PSI) techniques. The development of GB-SAR sensors based on the use of stepped linear frequency modulated continuous wave (SLFMCW) signals has led to significant improvements during the last years. They have allowed fulfilling the need of temporal homogeneity of the troposphere during the acquisition time and, moreover, they have favored the acquisition of reliable polarimetric SAR (PolSAR) measurements without drastically increasing the scanning time. This fact has boosted the inclusion of polarimetric SAR interferometry (PolInSAR) algorithms in PSI processing chains, which are demonstrating to outperform classical single-polarimetric performances. The objective of this paper is twofold. On the one hand, a general overview of the polarimetric RiskSAR sensor, developed by the Universitat Polit�cnica de Catalunya (UPC), is put forward as an example of SLFMCW GB-SAR system implementation. On the other hand, a complete theoretical description of ground-based SAR (GB-SAR) interferometry (GB-InSAR) techniques for PSI purposes is widely discussed. The adaptation of the Coherent Pixels Technique to obtain the linear and nonlinear components of ground displacement phenomena is proposed. In the second part of this paper, the displacement maps and time series over two very different scenarios are presented in order to show the feasibility of GB-SAR sensors for terrain displacement monitoring applications.},
    doi = {10.1109/JSTARS.2014.2360040},
    file = {:iglesiasEtAlJSTARS2015GBSARDisplacementPart1Theory.pdf:PDF},
    keywords = {geomorphology;radar interferometry;remote sensing by radar;synthetic aperture radar;terrain mapping;GB-InSAR techniques;GB-SAR sensors;PSI processing chains;PSI techniques;PolInSAR algorithms;PolSAR measurements;SLFMCW GB-SAR system;SLFMCW signals;Universitat Politecnica de Catalunya;acquisition time;classical single-polarimetric performances;coherent pixels technique;ground displacement episodes;ground displacement phenomena;ground-based SAR interferometry;ground-based polarimetric SAR interferometry;ground-based synthetic aperture radar;persistent scatterer interferomerty;polarimetric RiskSAR sensor;polarimetric SAR measurements;stepped linear frequency modulated continuous wave;terrain displacement phenomena monitoring;troposphere medium decorrelation;troposphere temporal homogeneity;vector network analyzers;Atmospheric measurements;Interferometry;Monitoring;Sensor phenomena and characterization;Synthetic aperture radar;Differential synthetic aperture radar (SAR) interferometry (DInSAR);GB-SAR interferometry (GB-InSAR);frequency modulated continuous wave (FMCW) radar;ground-based SAR (GB-SAR);persistent scatterer interferomerty (PSI);polarimetric SAR interferometry (PolInSAR);stepped linear FMCW (SLFMCW) radar},
    owner = {ofrey},
    
    }
    


  21. R. Iglesias, A. Aguasca, X. Fabregas, J. J. Mallorqui, D. Monells, C. Lpez-Martnez, and L. Pipia. Ground-Based Polarimetric SAR Interferometry for the Monitoring of Terrain Displacement Phenomena --Part II: Applications. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8(3):994-1007, March 2015. Keyword(s): geomorphology, geophysical techniques, radar interferometry, remote sensing by radar, synthetic aperture radar, Andorran Pyrenees, El Forn de Canillo, GB-InSAR techniques, GB-SAR sensors, Remote Sensing Laboratory, RiskSAR sensor, Spain, Universitat Politecnica de Catalunya, X-band, cost-effective solution, ground displacement phenomena, ground-based polarimetric SAR interferometry, ground-based synthetic aperture radar interferometry, in-field data, infrastructure safety, landslide monitoring, people safety, terrain displacement phenomena monitoring, urban landslides, urban subsidence, urban subsidence monitoring, zero-baseline configuration, Coherence, Interferometry, Monitoring, Sensitivity, Synthetic aperture radar, Terrain factors, Vectors, Differential synthetic aperture radar (SAR) interferometry (DInSAR), displacement monitoring, frequency modulated continuous wave (FMCW) radar, ground-based SAR (GB-SAR), ground-based SAR interferometry (GBInSAR), persistent scatterer interferometry (PSI), polarimetric SAR interferometry (PolInSAR), steepest linear frequency modulated continuous wave (SLFMCW) radar.
    @Article{iglesiasEtAlJSTARS2015GBSARDisplacementPart2Applications,
    author = {R. Iglesias and A. Aguasca and X. Fabregas and J. J. Mallorqui and D. Monells and C. L{\'o}pez-Mart{\'i}nez and L. Pipia},
    journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
    title = {Ground-Based Polarimetric {SAR} Interferometry for the Monitoring of Terrain Displacement Phenomena --Part II: Applications},
    year = {2015},
    issn = {1939-1404},
    month = mar,
    number = {3},
    pages = {994--1007},
    volume = {8},
    doi = {10.1109/JSTARS.2014.2366711},
    file = {:iglesiasEtAlJSTARS2015GBSARDisplacementPart2Applications.pdf:PDF},
    keywords = {geomorphology, geophysical techniques, radar interferometry, remote sensing by radar, synthetic aperture radar, Andorran Pyrenees, El Forn de Canillo, GB-InSAR techniques, GB-SAR sensors, Remote Sensing Laboratory, RiskSAR sensor, Spain, Universitat Politecnica de Catalunya, X-band, cost-effective solution, ground displacement phenomena, ground-based polarimetric SAR interferometry, ground-based synthetic aperture radar interferometry, in-field data, infrastructure safety, landslide monitoring, people safety, terrain displacement phenomena monitoring, urban landslides, urban subsidence, urban subsidence monitoring, zero-baseline configuration, Coherence, Interferometry, Monitoring, Sensitivity, Synthetic aperture radar, Terrain factors, Vectors, Differential synthetic aperture radar (SAR) interferometry (DInSAR), displacement monitoring, frequency modulated continuous wave (FMCW) radar, ground-based SAR (GB-SAR), ground-based SAR interferometry (GBInSAR), persistent scatterer interferometry (PSI), polarimetric SAR interferometry (PolInSAR), steepest linear frequency modulated continuous wave (SLFMCW) radar},
    owner = {ofrey},
    
    }
    


  22. Marko Komac, Rachel Holley, Pooja Mahapatra, Hans van der Marel, and Milos Bavec. Coupling of GPS/GNSS and radar interferometric data for a 3D surface displacement monitoring of landslides. Landslides, 12(2):241-257, April 2015.
    Abstract: Persistent scatterer interferometry (PSI) is capable of millimetric measurements of ground deformation phenomena occurring at radar signal reflectors (persistent scatterers, PS) that are phase coherent over a period of time. However, there are also limitations to PSI; significant phase decorrelation can occur between subsequent interferometric radar (InSAR) acquisitions in vegetated and low-density PS areas. Here, artificial amplitude- and phase-stable radar scatterers may have to be introduced. I2GPS was a Galileo project (02/2010--09/2011) that aimed to develop a novel device consisting of a compact active transponder (CAT) with an integrated global positioning system (GPS) antenna to ensure millimetric co-registration and a coherent cross-reference. The advantages are: (1) all advantages of CATs such as small size, light weight, unobtrusiveness and usability with multiple satellites and tracks; (2) absolute calibration for PSI data; (3) high sampling rate of GPS enables detection of abrupt ground motion in 3D; and (4) vertical components of the local velocity field can be derived from single-track InSAR line-of-sight displacements. A field trial was set to test the approach at a potential landslide site in Poto{\v{s}}ka planina, Slovenia to evaluate the applicability for operational monitoring of natural hazards. Preliminary results from the trial highlight some of the key considerations for operational deployments in the field. Ground motion measurements also allowed an assessment of landslide hazard at the site and demonstrated the synergies between InSAR and GPS measurements for landslide applications. InSAR and GPS measurements were compared to assess the consistency between the methods from the slope mass movement detection aspect.

    @Article{komacHolleyMahapatraMarelBavecLandslides2015GNSSandInSARforLandslides,
    author = {Komac, Marko and Holley, Rachel and Mahapatra, Pooja and van der Marel, Hans and Bavec, Milo{\v{s}}},
    title = {Coupling of {GPS/GNSS} and radar interferometric data for a {3D} surface displacement monitoring of landslides},
    journal = {Landslides},
    year = {2015},
    volume = {12},
    number = {2},
    pages = {241-257},
    month = apr,
    issn = {1612-5118},
    abstract = {Persistent scatterer interferometry (PSI) is capable of millimetric measurements of ground deformation phenomena occurring at radar signal reflectors (persistent scatterers, PS) that are phase coherent over a period of time. However, there are also limitations to PSI; significant phase decorrelation can occur between subsequent interferometric radar (InSAR) acquisitions in vegetated and low-density PS areas. Here, artificial amplitude- and phase-stable radar scatterers may have to be introduced. I2GPS was a Galileo project (02/2010--09/2011) that aimed to develop a novel device consisting of a compact active transponder (CAT) with an integrated global positioning system (GPS) antenna to ensure millimetric co-registration and a coherent cross-reference. The advantages are: (1) all advantages of CATs such as small size, light weight, unobtrusiveness and usability with multiple satellites and tracks; (2) absolute calibration for PSI data; (3) high sampling rate of GPS enables detection of abrupt ground motion in 3D; and (4) vertical components of the local velocity field can be derived from single-track InSAR line-of-sight displacements. A field trial was set to test the approach at a potential landslide site in Poto{\v{s}}ka planina, Slovenia to evaluate the applicability for operational monitoring of natural hazards. Preliminary results from the trial highlight some of the key considerations for operational deployments in the field. Ground motion measurements also allowed an assessment of landslide hazard at the site and demonstrated the synergies between InSAR and GPS measurements for landslide applications. InSAR and GPS measurements were compared to assess the consistency between the methods from the slope mass movement detection aspect.},
    day = {01},
    doi = {10.1007/s10346-014-0482-0},
    file = {:komacHolleyMahapatraMarelBavecLandslides2015GNSSandInSARforLandslides.pdf:PDF},
    owner = {ofrey},
    pdf = {../../../docs/komacHolleyMahapatraMarelBavecLandslides2015GNSSandInSARforLandslides.pdf},
    url = {https://doi.org/10.1007/s10346-014-0482-0},
    
    }
    


  23. K. Landmark, A. H. Schistad Solberg, F. Albregtsen, A. Austeng, and Roy E. Hansen. A Radon-Transform-Based Image Noise Filter With Applications to Multibeam Bathymetry. IEEE Transactions on Geoscience and Remote Sensing, 53(11):6252-6273, November 2015. Keyword(s): Synthetic Aperture Sonar, SAS, Radon transforms, bathymetry, geophysical image processing, image denoising, image restoration, radar imaging, remote sensing by radar, synthetic aperture radar, Chebyshev approximation, Laplacian point spread function, denoised image, fast discrete Radon transform, geomorphological type statistical classification, image transform, invariant terrain features, invertible edge detection operator, linear-image-transform-based algorithm, motion-induced errors, motion-induced noise, multibeam bathymetry, original image, processed test images, radon-transform-based image noise filter, remote sensing data, second noise signature, standard low-pass filters, synthetic aperture radar images, track line artifacts, Approximation algorithms, Image edge detection, Noise, Noise reduction, Presses, Radio frequency, Transforms, Discrete transforms, image denoising, image restoration, iterative methods, remote sensing, sonar, terrain mapping.
    Abstract: This paper describes a linear-image-transform-based algorithm for reducing stripe noise, track line artifacts, and motion-induced errors in remote sensing data. Developed for multibeam bathymetry (MB), the method has also been used for removing scalloping in synthetic aperture radar images. The proposed image transform is the composition of an invertible edge detection operator and a fast discrete Radon transform (DRT) due to G�tz, Druckm�ller, and Brady. The inverse DRT is computed by using an iterative method and exploiting an approximate inverse algorithm due to Press. The edge operator is implemented by circular convolution with a Laplacian point spread function modified to render the operator invertible. In the transformed image, linear discontinuities appear as high-intensity spots, which may be reset to zero. In MB data, a second noise signature is linked to motion-induced errors. A Chebyshev approximation of the original image is subtracted before applying the transform, and added back to the denoised image; this is necessary to avoid boundary effects. It is possible to process data faster and suppress motion-induced noise further by filtering images in nonoverlapping blocks using a matrix representation for the inverse DRT. Processed test images from several MB data sets had less noise and distortion compared with those obtained with standard low-pass filters. Denoising also improved the accuracy in statistical classification of geomorphological type by 10-28% for two sets of invariant terrain features.

    @Article{landmarkSchistadSolbergAlbregtsenAustengHansenTGRS2015RadonTransformImageNoiseFilter,
    author = {K. Landmark and A. H. Schistad Solberg and F. Albregtsen and A. Austeng and Roy E. Hansen},
    title = {A Radon-Transform-Based Image Noise Filter With Applications to Multibeam Bathymetry},
    journal = {IEEE Transactions on Geoscience and Remote Sensing},
    year = {2015},
    volume = {53},
    number = {11},
    pages = {6252-6273},
    month = nov,
    issn = {0196-2892},
    abstract = {This paper describes a linear-image-transform-based algorithm for reducing stripe noise, track line artifacts, and motion-induced errors in remote sensing data. Developed for multibeam bathymetry (MB), the method has also been used for removing scalloping in synthetic aperture radar images. The proposed image transform is the composition of an invertible edge detection operator and a fast discrete Radon transform (DRT) due to G�tz, Druckm�ller, and Brady. The inverse DRT is computed by using an iterative method and exploiting an approximate inverse algorithm due to Press. The edge operator is implemented by circular convolution with a Laplacian point spread function modified to render the operator invertible. In the transformed image, linear discontinuities appear as high-intensity spots, which may be reset to zero. In MB data, a second noise signature is linked to motion-induced errors. A Chebyshev approximation of the original image is subtracted before applying the transform, and added back to the denoised image; this is necessary to avoid boundary effects. It is possible to process data faster and suppress motion-induced noise further by filtering images in nonoverlapping blocks using a matrix representation for the inverse DRT. Processed test images from several MB data sets had less noise and distortion compared with those obtained with standard low-pass filters. Denoising also improved the accuracy in statistical classification of geomorphological type by 10-28% for two sets of invariant terrain features.},
    doi = {10.1109/TGRS.2015.2436380},
    file = {:landmarkSchistadSolbergAlbregtsenAustengHansenTGRS2015RadonTransformImageNoiseFilter.pdf:PDF},
    keywords = {Synthetic Aperture Sonar, SAS,Radon transforms;bathymetry;geophysical image processing;image denoising;image restoration;radar imaging;remote sensing by radar;synthetic aperture radar;Chebyshev approximation;Laplacian point spread function;denoised image;fast discrete Radon transform;geomorphological type statistical classification;image transform;invariant terrain features;invertible edge detection operator;linear-image-transform-based algorithm;motion-induced errors;motion-induced noise;multibeam bathymetry;original image;processed test images;radon-transform-based image noise filter;remote sensing data;second noise signature;standard low-pass filters;synthetic aperture radar images;track line artifacts;Approximation algorithms;Image edge detection;Noise;Noise reduction;Presses;Radio frequency;Transforms;Discrete transforms;image denoising;image restoration;iterative methods;remote sensing;sonar;terrain mapping},
    
    }
    


  24. Marco Lavalle and Scott Hensley. Extraction of Structural and Dynamic Properties of Forests From Polarimetric-Interferometric SAR Data Affected by Temporal Decorrelation. IEEE Trans. Geosci. Remote Sens., 53(9):4752-4767, September 2015. Keyword(s): SAR Processing, Decorrelation, Temporal Decorrelation, Gaussian processes, optical radar, radar imaging, radar interferometry, radar polarimetry, synthetic aperture radar, vegetation mapping, Gaussian-statistic motion model, Harvard Forest, L-band NASA Uninhabited Aerial Vehicle Synthetic Aperture Radar, Laser Vegetation and Ice Sensor, Massachussetts, NASA lidar, RMoG model, RVoG model, USA, canopy elements, canopy motion, forest biomass estimation, forest dynamic property, forest property estimation, forest structural property, forest vertical structure, least square distance minimization, lidar-derived height, multiplicative factors, polarimetric channels, polarimetric-interferometric SAR data, polarimetric-interferometric coherence, polarimetric-interferometric radar image, random-motion-over-ground model, random-volume-over-ground model, temporal coherence, temporal decorrelation effect, tree height, volumetric coherence, volumetric decorrelation effect, wave polarization, Biomass, Coherence, Data models, Decorrelation, Radar, Vegetation, Decorrelation, interferometry, polarimetry.
    Abstract: This paper addresses the important yet unresolved problem of estimating forest properties from polarimetric-interferometric radar images affected by temporal decorrelation. We approach the problem by formulating a physical model of the polarimetric-interferometric coherence that incorporates both volumetric and temporal decorrelation effects. The model is termed random-motion-over-ground (RMoG) model, as it combines the random-volume-over-ground (RVoG) model with a Gaussian-statistic motion model of the canopy elements. Key features of the RMoG model are: 1) temporal decorrelation depends on the vertical structure of forests; 2) volumetric and temporal coherences are not separable as simple multiplicative factors; and 3) temporal decorrelation is complex-valued and changes with wave polarization. This third feature is particularly important as it allows compensating for unknown levels of temporal decorrelation using multiple polarimetric channels. To estimate model parameters such as tree height and canopy motion, we propose an algorithm that minimizes the least square distance between model predictions and complex coherence observations. The algorithm was applied to L-band NASA's Uninhabited Aerial Vehicle Synthetic Aperture Radar data acquired over the Harvard Forest (Massachussetts, USA). We found that the RMS difference at stand level between estimated RMoG-model tree height and NASA's lidar Laser Vegetation and Ice Sensor tree height was within 12% of the lidar-derived height, which improved significantly the RMS difference of 37% obtained using the RVoG model and ignoring temporal decorrelation. This result contributes to our ability of estimating forest biomass using in-orbit and forthcoming polarimetric-interferometric radar missions.

    @Article{lavalleHensleyTGARS2015TempDecorrelation,
    author = {Lavalle, Marco and Hensley, Scott},
    title = {Extraction of Structural and Dynamic Properties of Forests From Polarimetric-Interferometric SAR Data Affected by Temporal Decorrelation},
    journal = {IEEE Trans. Geosci. Remote Sens.},
    year = {2015},
    volume = {53},
    number = {9},
    pages = {4752-4767},
    month = sep,
    issn = {0196-2892},
    abstract = {This paper addresses the important yet unresolved problem of estimating forest properties from polarimetric-interferometric radar images affected by temporal decorrelation. We approach the problem by formulating a physical model of the polarimetric-interferometric coherence that incorporates both volumetric and temporal decorrelation effects. The model is termed random-motion-over-ground (RMoG) model, as it combines the random-volume-over-ground (RVoG) model with a Gaussian-statistic motion model of the canopy elements. Key features of the RMoG model are: 1) temporal decorrelation depends on the vertical structure of forests; 2) volumetric and temporal coherences are not separable as simple multiplicative factors; and 3) temporal decorrelation is complex-valued and changes with wave polarization. This third feature is particularly important as it allows compensating for unknown levels of temporal decorrelation using multiple polarimetric channels. To estimate model parameters such as tree height and canopy motion, we propose an algorithm that minimizes the least square distance between model predictions and complex coherence observations. The algorithm was applied to L-band NASA's Uninhabited Aerial Vehicle Synthetic Aperture Radar data acquired over the Harvard Forest (Massachussetts, USA). We found that the RMS difference at stand level between estimated RMoG-model tree height and NASA's lidar Laser Vegetation and Ice Sensor tree height was within 12% of the lidar-derived height, which improved significantly the RMS difference of 37% obtained using the RVoG model and ignoring temporal decorrelation. This result contributes to our ability of estimating forest biomass using in-orbit and forthcoming polarimetric-interferometric radar missions.},
    doi = {10.1109/TGRS.2015.2409066},
    file = {:lavalleHensleyTGARS2015TempDecorrelation.pdf:PDF},
    keywords = {SAR Processing, Decorrelation, Temporal Decorrelation, Gaussian processes;optical radar;radar imaging;radar interferometry;radar polarimetry;synthetic aperture radar;vegetation mapping;Gaussian-statistic motion model;Harvard Forest;L-band NASA Uninhabited Aerial Vehicle Synthetic Aperture Radar;Laser Vegetation and Ice Sensor;Massachussetts;NASA lidar;RMoG model;RVoG model;USA;canopy elements;canopy motion;forest biomass estimation;forest dynamic property;forest property estimation;forest structural property;forest vertical structure;least square distance minimization;lidar-derived height;multiplicative factors;polarimetric channels;polarimetric-interferometric SAR data;polarimetric-interferometric coherence;polarimetric-interferometric radar image;random-motion-over-ground model;random-volume-over-ground model;temporal coherence;temporal decorrelation effect;tree height;volumetric coherence;volumetric decorrelation effect;wave polarization;Biomass;Coherence;Data models;Decorrelation;Radar;Vegetation;Decorrelation;interferometry;polarimetry;synthetic aperture radar (SAR)},
    pdf = {../../../docs/lavalleHensleyTGARS2015TempDecorrelation.pdf},
    
    }
    


  25. S. Leinss, H. Lwe, M. Proksch, J. Lemmetyinen, A. Wiesmann, and I. Hajnsek. Anisotropy of seasonal snow measured by polarimetric phase differences in radar time series. The Cryosphere Discussions, 9:6061-6123, 2015.
    @Article{LeinssLoweProkschLemmetyinenWiesmannHajnsek2015,
    Title = {Anisotropy of seasonal snow measured by polarimetric phase differences in radar time series},
    Author = {Leinss, S. and L\"owe, H. and Proksch, M. and Lemmetyinen, J. and Wiesmann, A. and Hajnsek, I.},
    Doi = {10.5194/tcd-9-6061-2015},
    Pages = {6061--6123},
    Url = {http://www.the-cryosphere-discuss.net/9/6061/2015/},
    Volume = {9},
    Year = {2015},
    Journal = {The Cryosphere Discussions} 
    }
    


  26. Silvan Leinss, Andreas Wiesmann, J. Lemmetyinen, and I. Hajnsek. Snow Water Equivalent of Dry Snow Measured by Differential Interferometry. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8(8):3773-3790, August 2015. Keyword(s): radar interferometry, remote sensing by radar, snow, Finland, SnowScat instrument, Sodankyla town, Xand Ku-band, active microwave remote sensing method, differential interferogram time series, differential radar interferometry, dry snow measurement, frequency 10 GHz, frequency 16 GHz, frequency 20 GHz, passive microwave remote sensing method, phase wrapping error, reference instrument, signal delay, snow density, snow pack spatial inhomogeneity, snow volume, snow water equivalent mapping, stratigraphy, temporal decorrelation, time 30 day, Backscatter, Ice, Instruments, Interferometry, Snow, Synthetic aperture radar, Coherence loss, SnowScat, dielectric constant of snow, differential interferometry (D-InSAR), dry snow, microwave penetration of snow, real aperture radar, snow water equivalent (SWE), synthetic aperture radar (SAR).
    Abstract: Large scale mapping of snow water equivalent (SWE) is a long-lasting request in many scientific and economical fields. Active and passive microwave remote sensing methods are explored, as local methods cannot be generalized due to the spatial inhomogeneity of the snow pack. Microwaves interact with snow by absorption, scattering, and refraction. For dry snow of a few meters depth and frequencies below 20 GHz, absorption and scattering in the snow volume are negligible compared with the backscattered energy from the underlying ground. The signal delay caused by refraction can be measured with differential radar interferometry, but phase wrapping errors and temporal decorrelation must be considered. We demonstrate that large delta SWE can be accurately determined from dense time series of differential interferograms at X- and Ku-band by temporal integration. Lost phase cycles are reconstructed with a two-frequency approach. Temporal decorrelation is minimized by a temporal resolution of 4 h. A linear function between delta SWE and phase difference is derived, which deviates only a few percent from the exact solution and which depends negligibly on snow density and stratigraphy. delta SWE retrieved from observations of the SnowScat instrument (SSI) were validated against observed SWE from different reference instruments, installed at a test site near the town of Sodankyl{\"a}, Finland. An accuracy below +/- 6 mm SWE was achieved at frequencies of 10 and 16 GHz for up to 200 mm of delta SWE. An exceptionally high temporal coherence was observed for up to 30 days for dry snow, whereas for wet snow it decayed within hours.

    @Article{leinssWiesmannLemmetyinenHajnsek2015,
    author = {Leinss, Silvan and Wiesmann, Andreas and Lemmetyinen, J. and Hajnsek, I.},
    title = {Snow Water Equivalent of Dry Snow Measured by Differential Interferometry},
    journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
    year = {2015},
    volume = {8},
    number = {8},
    month = {Aug},
    pages = {3773-3790},
    issn = {1939-1404},
    doi = {10.1109/JSTARS.2015.2432031},
    abstract = {Large scale mapping of snow water equivalent (SWE) is a long-lasting request in many scientific and economical fields. Active and passive microwave remote sensing methods are explored, as local methods cannot be generalized due to the spatial inhomogeneity of the snow pack. Microwaves interact with snow by absorption, scattering, and refraction. For dry snow of a few meters depth and frequencies below 20 GHz, absorption and scattering in the snow volume are negligible compared with the backscattered energy from the underlying ground. The signal delay caused by refraction can be measured with differential radar interferometry, but phase wrapping errors and temporal decorrelation must be considered. We demonstrate that large delta SWE can be accurately determined from dense time series of differential interferograms at X- and Ku-band by temporal integration. Lost phase cycles are reconstructed with a two-frequency approach. Temporal decorrelation is minimized by a temporal resolution of 4 h. A linear function between delta SWE and phase difference is derived, which deviates only a few percent from the exact solution and which depends negligibly on snow density and stratigraphy. delta SWE retrieved from observations of the SnowScat instrument (SSI) were validated against observed SWE from different reference instruments, installed at a test site near the town of Sodankyl{\"a}, Finland. An accuracy below +/- 6 mm SWE was achieved at frequencies of 10 and 16 GHz for up to 200 mm of delta SWE. An exceptionally high temporal coherence was observed for up to 30 days for dry snow, whereas for wet snow it decayed within hours.},
    keywords = {radar interferometry;remote sensing by radar;snow;Finland;SnowScat instrument;Sodankyla town;Xand Ku-band;active microwave remote sensing method;differential interferogram time series;differential radar interferometry;dry snow measurement;frequency 10 GHz;frequency 16 GHz;frequency 20 GHz;passive microwave remote sensing method;phase wrapping error;reference instrument;signal delay;snow density;snow pack spatial inhomogeneity;snow volume;snow water equivalent mapping;stratigraphy;temporal decorrelation;time 30 day;Backscatter;Ice;Instruments;Interferometry;Snow;Synthetic aperture radar;Coherence loss;SnowScat;dielectric constant of snow;differential interferometry (D-InSAR);dry snow;microwave penetration of snow;real aperture radar;snow water equivalent (SWE);synthetic aperture radar (SAR)},
    
    }
    


  27. Jun Maeda and Kosuke Heki. Morphology and dynamics of daytime mid-latitude sporadic-E patches revealed by GPS total electron content observations in Japan. Earth, Planets and Space, 67(1):89, June 2015. Keyword(s): sporadic E, ionosphere, GPS, Global Positioning System, GNSS, Global Navigation Satellite System, GEONET, TEC, Total Electron Content.
    Abstract: Morphological characteristics of daytime mid-latitude sporadic-E (Es) patches are studied by two-dimensional total electron content (TEC) maps drawn using the Japanese dense network of Global Positioning System (GPS) receivers. By analyzing over 70 cases, we found that their horizontal shapes are characterized by frontal structure typically elongated in east-west by { extasciitilde}100 km. They are observed to migrate mainly northward in the morning and southward in the afternoon with speeds of 30-100 m/s. This may reflect the velocities of neutral winds controlled by the atmospheric tides. Such frontal structures are often found to include smaller scale structures.

    @Article{maedaHekiEPS2015IonosphereGNSSSporadicEThroughTEC,
    author = {Maeda, Jun and Heki, Kosuke},
    title = {Morphology and dynamics of daytime mid-latitude sporadic{-E} patches revealed by {GPS} total electron content observations in {Japan}},
    journal = {Earth, Planets and Space},
    year = {2015},
    volume = {67},
    number = {1},
    pages = {89},
    month = {Jun},
    issn = {1880-5981},
    abstract = {Morphological characteristics of daytime mid-latitude sporadic-E (Es) patches are studied by two-dimensional total electron content (TEC) maps drawn using the Japanese dense network of Global Positioning System (GPS) receivers. By analyzing over 70 cases, we found that their horizontal shapes are characterized by frontal structure typically elongated in east-west by {	extasciitilde}100 km. They are observed to migrate mainly northward in the morning and southward in the afternoon with speeds of 30-100 m/s. This may reflect the velocities of neutral winds controlled by the atmospheric tides. Such frontal structures are often found to include smaller scale structures.},
    day = {11},
    doi = {10.1186/s40623-015-0257-4},
    file = {:maedaHekiEPS2015IonosphereGNSSSporadicEThroughTEC.pdf:PDF},
    keywords = {sporadic E, ionosphere, GPS, Global Positioning System, GNSS, Global Navigation Satellite System, GEONET, TEC, Total Electron Content},
    owner = {ofrey},
    url = {https://doi.org/10.1186/s40623-015-0257-4},
    
    }
    


  28. Pooja S. Mahapatra, Sami Samie Esfahany, and Ramon F. Hanssen. Geodetic Network Design for InSAR. IEEE Trans. Geosci. Remote Sens., 53(7):3669-3680, July 2015. Keyword(s): SAR Processing, InSAR, GNSS, persistent scatterer interferometry, covariance matrices, deformation, geodesy, geomorphology, geophysical techniques, network theory (graphs), radar interferometry, remote sensing by radar, synthetic aperture radar, InSAR measurement, coherent target device deployment, covariance matrices, criterion matrix, deformation signal, densification measurement, geodesic network design methodology, ground deformation measurement, interferometric synthetic aperture radar, network optimization, optimal ground location, Covariance matrices, Deformable models, Geophysical measurements, Redundancy, Synthetic aperture radar, Coherent target, compact active transponder, corner reflector, criterion matrix, economy, geodesy, interferometric synthetic aperture radar (InSAR), network design, precision, reliability.
    Abstract: Ground deformation can be monitored with subcentimetric precision from space, using interferometric synthetic aperture radar (InSAR). This technique can sometimes be limited by a low density of naturally occurring phase-coherent radar targets. Measurement densification may be achieved through improvements in processing algorithms and new satellites with better revisit times, but there can still exist areas where very few coherent targets are detected, e.g., in vegetated nonurbanized areas. For third-party end users of InSAR survey results, there is currently no systematic method to determine a priori whether these coherent targets have adequate spatial distribution to estimate the parameters of their interest. We propose such a method, along with a practical solution for measurement densification, i.e., deployment of coherent target devices such as corner reflectors or transponders. We propose a generic network design methodology that does the following: 1) determines whether the naturally occurring InSAR measurements are adequate; 2) finds the minimum number of additional devices (if required); and 3) finds their optimal ground locations. The method digests, as inputs, the expected locations and quality of existing coherent targets, the quality of the devices being deployed, and, if available, any prior knowledge of the deformation signal. At the core of the method is a comparison of different covariance matrices of the final parameters of interest with a criterion matrix (i.e., the desired idealized covariance matrix), using a predefined metric. The resulting network is optimized with respect to precision, reliability, and cost criteria. Simulated data sets and a subsidence case study in the Netherlands are used to demonstrate this method.

    @Article{mahapatraSamieiEsfahanyHanssenTGARS2015GeodeticNetworkDesignForInSAR,
    author = {Mahapatra, Pooja S. and Samie Esfahany, Sami and Hanssen, Ramon F.},
    journal = {IEEE Trans. Geosci. Remote Sens.},
    title = {Geodetic Network Design for {InSAR}},
    year = {2015},
    issn = {0196-2892},
    month = jul,
    number = {7},
    pages = {3669-3680},
    volume = {53},
    abstract = {Ground deformation can be monitored with subcentimetric precision from space, using interferometric synthetic aperture radar (InSAR). This technique can sometimes be limited by a low density of naturally occurring phase-coherent radar targets. Measurement densification may be achieved through improvements in processing algorithms and new satellites with better revisit times, but there can still exist areas where very few coherent targets are detected, e.g., in vegetated nonurbanized areas. For third-party end users of InSAR survey results, there is currently no systematic method to determine a priori whether these coherent targets have adequate spatial distribution to estimate the parameters of their interest. We propose such a method, along with a practical solution for measurement densification, i.e., deployment of coherent target devices such as corner reflectors or transponders. We propose a generic network design methodology that does the following: 1) determines whether the naturally occurring InSAR measurements are adequate; 2) finds the minimum number of additional devices (if required); and 3) finds their optimal ground locations. The method digests, as inputs, the expected locations and quality of existing coherent targets, the quality of the devices being deployed, and, if available, any prior knowledge of the deformation signal. At the core of the method is a comparison of different covariance matrices of the final parameters of interest with a criterion matrix (i.e., the desired idealized covariance matrix), using a predefined metric. The resulting network is optimized with respect to precision, reliability, and cost criteria. Simulated data sets and a subsidence case study in the Netherlands are used to demonstrate this method.},
    doi = {10.1109/TGRS.2014.2381598},
    file = {:mahapatraSamieiEsfahanyHanssenTGARS2015GeodeticNetworkDesignForInSAR.pdf:PDF},
    keywords = {SAR Processing, InSAR, GNSS, persistent scatterer interferometry, covariance matrices;deformation;geodesy;geomorphology;geophysical techniques;network theory (graphs);radar interferometry;remote sensing by radar;synthetic aperture radar;InSAR measurement;coherent target device deployment;covariance matrices;criterion matrix;deformation signal;densification measurement;geodesic network design methodology;ground deformation measurement;interferometric synthetic aperture radar;network optimization;optimal ground location;Covariance matrices;Deformable models;Geophysical measurements;Redundancy;Synthetic aperture radar;Coherent target;compact active transponder;corner reflector;criterion matrix;economy;geodesy;interferometric synthetic aperture radar (InSAR);network design;precision;reliability},
    pdf = {../../../docs/mahapatraSamieiEsfahanyHanssenTGARS2015GeodeticNetworkDesignForInSAR.pdf},
    
    }
    


  29. Timothy M. Marston and Daniel S. Plotnick. Semiparametric Statistical Stripmap Synthetic Aperture Autofocusing. IEEE Transactions on Geoscience and Remote Sensing, 53(4):2086-2095, April 2015. Keyword(s): SAR Processing, Autofocus, Motion Compensation, MoComp, geophysical image processing, remote sensing by radar, synthetic aperture radar, synthetic aperture sonar, SAR literature, artificially injected crabbing error, artificially injected sway error, corrupting phase function, cost function gradient, metric-maximizing solutions, semiparametric statistical stripmap synthetic aperture autofocusing, spotlight-mode SAR applications, stripmap error model, stripmap gradient expression, stripmap imagery, synthetic aperture sonar literature, to statistical quality metric, unmanned-underwater-vehicle-mounted sonar system, widebeam wideband rail-based system, Apertures, Arrays, Computational modeling, Focusing, Measurement, Synthetic aperture sonar, Synthetic aperture sonar (SAS) radar autofocus stripmap.
    Abstract: Autofocusing synthetic aperture imagery by maximizing a statistical quality metric such as contrast or sharpness is a well-documented approach in both synthetic aperture radar (SAR) literature and synthetic aperture sonar literature. It is most successfully applied in spotlight-mode SAR applications, where the assumption of spatial invariance of the corrupting phase function is strong and expressions for the gradients of various quality metrics with respect to standard error models have been calculated. Examples of application to stripmap imagery often involve sectioning images into small blocks, allowing spotlight algorithms to be patchwise applied. This paper formulates the gradient of the cost function in a manner that is consistent with the stripmap error model, inherently providing solutions that compensate for the spatial variance while simultaneously bypassing the need for subdividing an image or aperture. This paper formulates the stripmap gradient expression in conjunction with a computationally efficient imaging approach to rapidly achieve metric-maximizing solutions. Demonstrations are shown on a widebeam wideband rail-based system experiencing random jitter and on an unmanned-underwater-vehicle-mounted sonar system exhibiting artificially injected crabbing and sway errors. Results indicate that the algorithm is particularly effective at compensating for random and rapidly oscillating navigation and jitter errors, as well as sidelobes introduced by crabbing in arrayed systems.

    @Article{marstonPlotnickTGRS2015AutofocusStripmap,
    author = {Timothy M. Marston and Daniel S. Plotnick},
    title = {Semiparametric Statistical Stripmap Synthetic Aperture Autofocusing},
    journal = {IEEE Transactions on Geoscience and Remote Sensing},
    year = {2015},
    volume = {53},
    number = {4},
    pages = {2086-2095},
    month = apr,
    issn = {0196-2892},
    abstract = {Autofocusing synthetic aperture imagery by maximizing a statistical quality metric such as contrast or sharpness is a well-documented approach in both synthetic aperture radar (SAR) literature and synthetic aperture sonar literature. It is most successfully applied in spotlight-mode SAR applications, where the assumption of spatial invariance of the corrupting phase function is strong and expressions for the gradients of various quality metrics with respect to standard error models have been calculated. Examples of application to stripmap imagery often involve sectioning images into small blocks, allowing spotlight algorithms to be patchwise applied. This paper formulates the gradient of the cost function in a manner that is consistent with the stripmap error model, inherently providing solutions that compensate for the spatial variance while simultaneously bypassing the need for subdividing an image or aperture. This paper formulates the stripmap gradient expression in conjunction with a computationally efficient imaging approach to rapidly achieve metric-maximizing solutions. Demonstrations are shown on a widebeam wideband rail-based system experiencing random jitter and on an unmanned-underwater-vehicle-mounted sonar system exhibiting artificially injected crabbing and sway errors. Results indicate that the algorithm is particularly effective at compensating for random and rapidly oscillating navigation and jitter errors, as well as sidelobes introduced by crabbing in arrayed systems.},
    doi = {10.1109/TGRS.2014.2353515},
    file = {:marstonPlotnickTGRS2015AutofocusStripmap.pdf:PDF},
    keywords = {SAR Processing, Autofocus, Motion Compensation, MoComp, geophysical image processing;remote sensing by radar;synthetic aperture radar;synthetic aperture sonar;SAR literature;artificially injected crabbing error;artificially injected sway error;corrupting phase function;cost function gradient;metric-maximizing solutions;semiparametric statistical stripmap synthetic aperture autofocusing;spotlight-mode SAR applications;stripmap error model;stripmap gradient expression;stripmap imagery;synthetic aperture sonar literature;to statistical quality metric;unmanned-underwater-vehicle-mounted sonar system;widebeam wideband rail-based system;Apertures;Arrays;Computational modeling;Focusing;Measurement;Synthetic aperture sonar;Synthetic aperture sonar (SAS) radar autofocus stripmap},
    owner = {ofrey},
    
    }
    


  30. Yu Morishita and Ramon F. Hanssen. Deformation Parameter Estimation in Low Coherence Areas Using a Multisatellite InSAR Approach. IEEE Trans. Geosci. Remote Sens., 53(8):4275-4283, August 2015. Keyword(s): SAR Processing, persistent scatterer interferometry, PSI, InSAR, DInSAR, Interferometry, Differential Interferometry, decorrelation, deformation, geophysical techniques, least mean squares methods, radar interferometry, remote sensing by radar, soil, synthetic aperture radar, time series, The Netherlands, drained peat soils, least squares method, local subsidence rates, low coherence areas, multisatellite InSAR, pasture periodic signal, peat periodic signal, persistent scatterer interferometry, satellite data, small baseline subset algorithms, statistically homogeneous pixels, surface deformation parameter estimation, Coherence, Decorrelation, Deformable models, Estimation, Satellites, Soil, Synthetic aperture radar, Decorrelation, radar interferometry, synthetic aperture radar (SAR).
    Abstract: Persistent scatterer (PS) interferometry and small baseline subset algorithms can be used to estimate time series of surface deformation with high precision. In areas with low coherence, and in the absence of sufficient PS, the estimation of reliable phase information can be cumbersome. Here, we report a successful approach for estimating deformation at pasture on drained peat soils using the integrated use of data from several satellite missions, a parametric deformation model with a generalized least squares method, and spatial averaging over statistically homogeneous pixels. The developed methodology is analyzed and applied on a test site in The Netherlands, where we report local subsidence rates and periodic signal over the peat and pasture areas.

    @Article{morishitaHanssenTGRS2015DInSARMultiSat,
    author = {Morishita, Yu and Hanssen, Ramon F.},
    title = {Deformation Parameter Estimation in Low Coherence Areas Using a Multisatellite {InSAR} Approach},
    journal = {IEEE Trans. Geosci. Remote Sens.},
    year = {2015},
    volume = {53},
    number = {8},
    pages = {4275-4283},
    month = aug,
    issn = {0196-2892},
    abstract = {Persistent scatterer (PS) interferometry and small baseline subset algorithms can be used to estimate time series of surface deformation with high precision. In areas with low coherence, and in the absence of sufficient PS, the estimation of reliable phase information can be cumbersome. Here, we report a successful approach for estimating deformation at pasture on drained peat soils using the integrated use of data from several satellite missions, a parametric deformation model with a generalized least squares method, and spatial averaging over statistically homogeneous pixels. The developed methodology is analyzed and applied on a test site in The Netherlands, where we report local subsidence rates and periodic signal over the peat and pasture areas.},
    doi = {10.1109/TGRS.2015.2394394},
    file = {:morishitaHanssenTGRS2015DInSARMultiSat.pdf:PDF},
    keywords = {SAR Processing, persistent scatterer interferometry, PSI, InSAR, DInSAR, Interferometry, Differential Interferometry, decorrelation;deformation;geophysical techniques;least mean squares methods;radar interferometry;remote sensing by radar;soil;synthetic aperture radar;time series;The Netherlands;drained peat soils;least squares method;local subsidence rates;low coherence areas;multisatellite InSAR;pasture periodic signal;peat periodic signal;persistent scatterer interferometry;satellite data;small baseline subset algorithms;statistically homogeneous pixels;surface deformation parameter estimation;Coherence;Decorrelation;Deformable models;Estimation;Satellites;Soil;Synthetic aperture radar;Decorrelation;radar interferometry;synthetic aperture radar (SAR)},
    pdf = {../../../docs/morishitaHanssenTGRS2015DInSARMultiSat.pdf},
    
    }
    


  31. Yu Morishita and Ramon F. Hanssen. Temporal Decorrelation in L-, C-, and X-band Satellite Radar Interferometry for Pasture on Drained Peat Soils. IEEE Trans. Geosci. Remote Sens., 53(2):1096-1104, February 2015. Keyword(s): SAR Processing, Decorrelation, Temporal Decorrelation, geophysical signal processing, land use, radar interferometry, remote sensing by radar, soil, synthetic aperture radar, terrain mapping, vegetation, vegetation mapping, ALOS-2 satellite, Advanced Land Observation Satellite mission, C-band SAR observations, C-band satellite radar interferometry, Envisat mission, European Remote Sensing Satellite mission, L-band SAR observations, L-band satellite radar interferometry, RADARSAT-2 mission, Sentinel-1 satellite, TerraSAR-X mission, X-band SAR observations, X-band satellite radar interferometry, a priori assessment, actual land use, climatological circumstances, coherence estimation window sizes, coherence levels, coherent information, coherent signal, drained peat soils, frequency function, generic models, interferograms, interferometric applications, nonurban areas, optimal data sets, pasture, repeat intervals, repeat orbits, satellite missions, soil types, synthetic aperture radar interferometry, temporal decorrelation model, temporal dynamics, vegetation types, Coherence, Decorrelation.
    Abstract: Temporal decorrelation is one of the main limitations of synthetic aperture radar (SAR) interferometry. For nonurban areas, its mechanism is very complex, as it is very dependent of vegetation types and their temporal dynamics, actual land use, soil types, and climatological circumstances. Yet, an a priori assessment and comprehension of the expected coherence levels of interferograms are required for designing new satellite missions (in terms of frequency, resolution, and repeat orbits), for choosing the optimal data sets for a specific application, and for feasibility studies for new interferometric applications. Although generic models for temporal decorrelation have been proposed, their parameters depend heavily on the land use in the area of interest. Here, we report the behavior of temporal decorrelation for a specific class of land use: pasture on drained peat soils. We use L-, C-, and X-band SAR observations from the Advanced Land Observation Satellite (ALOS), European Remote Sensing Satellite, Envisat, RADARSAT-2, and TerraSAR-X missions. We present a dedicated temporal decorrelation model using three parameters and demonstrate how coherent information can be retrieved as a function of frequency, repeat intervals, and coherence estimation window sizes. New satellites such as Sentinel-1 and ALOS-2, with shorter repeat intervals than their predecessors, would enhance the possibility to obtain a coherent signal over pasture.

    @Article{morishitaHanssenTGRS2015TempDecorrelation,
    author = {Morishita, Yu and Hanssen, Ramon F.},
    title = {Temporal Decorrelation in {L-}, {C-}, and {X-}band Satellite Radar Interferometry for Pasture on Drained Peat Soils},
    journal = {IEEE Trans. Geosci. Remote Sens.},
    year = {2015},
    volume = {53},
    number = {2},
    pages = {1096-1104},
    month = feb,
    issn = {0196-2892},
    abstract = {Temporal decorrelation is one of the main limitations of synthetic aperture radar (SAR) interferometry. For nonurban areas, its mechanism is very complex, as it is very dependent of vegetation types and their temporal dynamics, actual land use, soil types, and climatological circumstances. Yet, an a priori assessment and comprehension of the expected coherence levels of interferograms are required for designing new satellite missions (in terms of frequency, resolution, and repeat orbits), for choosing the optimal data sets for a specific application, and for feasibility studies for new interferometric applications. Although generic models for temporal decorrelation have been proposed, their parameters depend heavily on the land use in the area of interest. Here, we report the behavior of temporal decorrelation for a specific class of land use: pasture on drained peat soils. We use L-, C-, and X-band SAR observations from the Advanced Land Observation Satellite (ALOS), European Remote Sensing Satellite, Envisat, RADARSAT-2, and TerraSAR-X missions. We present a dedicated temporal decorrelation model using three parameters and demonstrate how coherent information can be retrieved as a function of frequency, repeat intervals, and coherence estimation window sizes. New satellites such as Sentinel-1 and ALOS-2, with shorter repeat intervals than their predecessors, would enhance the possibility to obtain a coherent signal over pasture.},
    doi = {10.1109/TGRS.2014.2333814},
    file = {:morishitaHanssenTGRS2015TempDecorrelation.pdf:PDF},
    keywords = {SAR Processing, Decorrelation, Temporal Decorrelation, geophysical signal processing;land use;radar interferometry;remote sensing by radar;soil;synthetic aperture radar;terrain mapping;vegetation;vegetation mapping;ALOS-2 satellite;Advanced Land Observation Satellite mission;C-band SAR observations;C-band satellite radar interferometry;Envisat mission;European Remote Sensing Satellite mission;L-band SAR observations;L-band satellite radar interferometry;RADARSAT-2 mission;Sentinel-1 satellite;TerraSAR-X mission;X-band SAR observations;X-band satellite radar interferometry;a priori assessment;actual land use;climatological circumstances;coherence estimation window sizes;coherence levels;coherent information;coherent signal;drained peat soils;frequency function;generic models;interferograms;interferometric applications;nonurban areas;optimal data sets;pasture;repeat intervals;repeat orbits;satellite missions;soil types;synthetic aperture radar interferometry;temporal decorrelation model;temporal dynamics;vegetation types;Coherence;Decorrelation;Satellites;Sensors;Soil;Synthetic aperture radar;Vegetation mapping;Decorrelation;radar interferometry;synthetic aperture radar (SAR)},
    pdf = {../../../docs/morishitaHanssenTGRS2015TempDecorrelation.pdf},
    
    }
    


  32. M. Pieraccini, F. Papi, and S. Rocchio. Interferometric RotoSAR. Electron Lett, 51(18):1451-1453, 2015. Keyword(s): GB-SAR, ground-based SAR, terrestrial SAR, radar antennas, radar imaging, radar interferometry, synthetic aperture radar, SAR images, displacement vectors, field of view, interferometric RotoSAR, plane of rotation, radar antenna.
    @Article{PieracciniEL2015RotoSAR,
    author = {M. Pieraccini and F. Papi and S. Rocchio},
    title = {Interferometric RotoSAR},
    journal = {Electron Lett},
    year = {2015},
    volume = {51},
    number = {18},
    pages = {1451--1453},
    issn = {0013-5194},
    doi = {10.1049/el.2015.1785},
    keywords = {GB-SAR,ground-based SAR, terrestrial SAR,radar antennas, radar imaging, radar interferometry, synthetic aperture radar, SAR images, displacement vectors, field of view, interferometric RotoSAR, plane of rotation, radar antenna},
    owner = {ofrey},
    
    }
    


  33. M. Pinheiro, M. Rodriguez-Cassola, P. Prats-Iraola, A. Reigber, G. Krieger, and A. Moreira. Reconstruction of Coherent Pairs of Synthetic Aperture Radar Data Acquired in Interrupted Mode. IEEE Transactions on Geoscience and Remote Sensing, 53(4):1876-1893, April 2015. Keyword(s): calibration, image reconstruction, radar imaging, radar interferometry, synchronisation, synthetic aperture radar, coherent pairs, synthetic aperture radar, cooperative bistatic SAR systems, SAR imaging, multistatic systems, spectral estimation based interpolators, distributed scatterers, image reconstruction, TanDEM-X mission, Synthetic aperture radar, Image reconstruction, Interrupters, Azimuth, Synchronization, Apertures, Coherence, Bistatic synthetic aperture radar (SAR), cross-reconstruction, reconstruction of missing data, SAR, SAR interferometry, spectral estimators, Bistatic synthetic aperture radar (SAR), cross-reconstruction, reconstruction of missing data, SAR, SAR interferometry, spectral estimators.
    Abstract: A number of synthetic aperture radar (SAR) systems might work in interrupted operation for different purposes. Examples are cooperative bistatic SAR systems with a synchronization link between the transmitter and receiver or multistatic systems operating in receive-only mode, among others. As a direct consequence, the acquired raw data contain missing echoes presented in a periodical or random pattern. Since the missing raw data introduce artifacts in the processed images, recovery methods have to be applied. Usually, spectral-estimation-based interpolators can be used to recover data. Although such algorithms show good performance for pointlike targets, their efficiency is decreased for distributed scatterers. In this paper, we propose, for a coherent pair of SAR images, the use of the common information in one image to reconstruct the other and vice versa. The conditions required for the proper use of the approach are discussed, and the method is verified using simulated data. One special case of study is the TanDEM-X mission, where the cooperative nature of the bistatic operation requires the periodic exchange of information between the satellites in order to gather information for calibration and synchronization, creating a periodic missing data pattern in the raw data. For this case of study, the reconstruction methods based on spectral estimation are analyzed, and the proposed reconstruction using cross-information is validated.

    @Article{6891190,
    author = {M. {Pinheiro} and M. {Rodriguez-Cassola} and P. {Prats-Iraola} and A. {Reigber} and G. {Krieger} and A. {Moreira}},
    title = {Reconstruction of Coherent Pairs of Synthetic Aperture Radar Data Acquired in Interrupted Mode},
    journal = {IEEE Transactions on Geoscience and Remote Sensing},
    year = {2015},
    volume = {53},
    number = {4},
    pages = {1876-1893},
    month = {April},
    issn = {1558-0644},
    abstract = {A number of synthetic aperture radar (SAR) systems might work in interrupted operation for different purposes. Examples are cooperative bistatic SAR systems with a synchronization link between the transmitter and receiver or multistatic systems operating in receive-only mode, among others. As a direct consequence, the acquired raw data contain missing echoes presented in a periodical or random pattern. Since the missing raw data introduce artifacts in the processed images, recovery methods have to be applied. Usually, spectral-estimation-based interpolators can be used to recover data. Although such algorithms show good performance for pointlike targets, their efficiency is decreased for distributed scatterers. In this paper, we propose, for a coherent pair of SAR images, the use of the common information in one image to reconstruct the other and vice versa. The conditions required for the proper use of the approach are discussed, and the method is verified using simulated data. One special case of study is the TanDEM-X mission, where the cooperative nature of the bistatic operation requires the periodic exchange of information between the satellites in order to gather information for calibration and synchronization, creating a periodic missing data pattern in the raw data. For this case of study, the reconstruction methods based on spectral estimation are analyzed, and the proposed reconstruction using cross-information is validated.},
    doi = {10.1109/TGRS.2014.2350255},
    keywords = {calibration;image reconstruction;radar imaging;radar interferometry;synchronisation;synthetic aperture radar;coherent pairs;synthetic aperture radar;cooperative bistatic SAR systems;SAR imaging;multistatic systems;spectral estimation based interpolators;distributed scatterers;image reconstruction;TanDEM-X mission;Synthetic aperture radar;Image reconstruction;Interrupters;Azimuth;Synchronization;Apertures;Coherence;Bistatic synthetic aperture radar (SAR);cross-reconstruction;reconstruction of missing data;SAR;SAR interferometry;spectral estimators;Bistatic synthetic aperture radar (SAR);cross-reconstruction;reconstruction of missing data;SAR;SAR interferometry;spectral estimators},
    owner = {ofrey},
    
    }
    


  34. P. Prats-Iraola, M. Rodriguez-Cassola, F. De Zan, R. Scheiber, P. L�pez-Dekker, I. Barat, and D. Geudtner. Role of the Orbital Tube in Interferometric Spaceborne SAR Missions. IEEE Geoscience and Remote Sensing Letters, 12(7):1486-1490, July 2015. Keyword(s): decorrelation, Earth orbit, radar interferometry, spaceborne radar, synthetic aperture radar, interferometric spaceborne SAR mission, Earth observation satellite synthetic aperture radar mission, Earthfixed orbital tube, ground-track coverage repeatability, repeat-pass interferometric compatibility, azimuth spectral decorrelation, azimuth coregistration accuracy, ScanSAR, TOPS, terrain observation by progressive scan, Sentinel-1 mission, Orbits, Electron tubes, Azimuth, Doppler effect, Satellites, Synthetic aperture radar, Remote sensing, Coregistration, interferometric SAR (InSAR), orbital tube, ScanSAR, spectral decorrelation, synthetic aperture radar (SAR), Terrain Observation by Progressive Scans (TOPS), Coregistration, interferometric SAR (InSAR), orbital tube, ScanSAR, spectral decorrelation, synthetic aperture radar (SAR), Terrain Observation by Progressive Scans (TOPS).
    Abstract: The orbit for Earth observation satellite synthetic aperture radar (SAR) missions is maintained within an Earth-fixed orbital tube to ensure ground-track coverage repeatability and, consequently, to enable repeat-pass interferometric compatibility between data takes. In this letter, it is shown that the size of the orbital tube may affect the interferometric performance in terms of azimuth spectral decorrelation and azimuth coregistration accuracy under the presence of squint. These effects require special consideration for SAR burst modes, such as ScanSAR or TOPS (i.e., Terrain Observation by Progressive Scans). This letter presents and analyzes these aspects in the frame of the Sentinel-1 mission.

    @Article{7065218,
    author = {P. {Prats-Iraola} and M. {Rodriguez-Cassola} and F. {De Zan} and R. {Scheiber} and P. {L�pez-Dekker} and I. {Barat} and D. {Geudtner}},
    title = {Role of the Orbital Tube in Interferometric Spaceborne SAR Missions},
    journal = {IEEE Geoscience and Remote Sensing Letters},
    year = {2015},
    volume = {12},
    number = {7},
    pages = {1486-1490},
    month = {July},
    issn = {1558-0571},
    abstract = {The orbit for Earth observation satellite synthetic aperture radar (SAR) missions is maintained within an Earth-fixed orbital tube to ensure ground-track coverage repeatability and, consequently, to enable repeat-pass interferometric compatibility between data takes. In this letter, it is shown that the size of the orbital tube may affect the interferometric performance in terms of azimuth spectral decorrelation and azimuth coregistration accuracy under the presence of squint. These effects require special consideration for SAR burst modes, such as ScanSAR or TOPS (i.e., Terrain Observation by Progressive Scans). This letter presents and analyzes these aspects in the frame of the Sentinel-1 mission.},
    doi = {10.1109/LGRS.2015.2409885},
    keywords = {decorrelation;Earth orbit;radar interferometry;spaceborne radar;synthetic aperture radar;interferometric spaceborne SAR mission;Earth observation satellite synthetic aperture radar mission;Earthfixed orbital tube;ground-track coverage repeatability;repeat-pass interferometric compatibility;azimuth spectral decorrelation;azimuth coregistration accuracy;ScanSAR;TOPS;terrain observation by progressive scan;Sentinel-1 mission;Orbits;Electron tubes;Azimuth;Doppler effect;Satellites;Synthetic aperture radar;Remote sensing;Coregistration;interferometric SAR (InSAR);orbital tube;ScanSAR;spectral decorrelation;synthetic aperture radar (SAR);Terrain Observation by Progressive Scans (TOPS);Coregistration;interferometric SAR (InSAR);orbital tube;ScanSAR;spectral decorrelation;synthetic aperture radar (SAR);Terrain Observation by Progressive Scans (TOPS)},
    owner = {ofrey},
    
    }
    


  35. Martin Proksch, Henning Lwe, and Martin Schneebeli. Density, specific surface area, and correlation length of snow measured by high-resolution penetrometry. J. Geophys. Res. Earth Surf., pp 346-362, 2015. Keyword(s): Snow characterisation, correlation length, snow density, specific surface area, SSA, Snow Micro Pen, SMP, micro-CT, Statistical model, Statistical model relating micro-CT structure to SMP force for many snow data, snow density retrieval, correlation length, and SSA in the field, Efficient retrieval of spatial variability and 2-D stratigraphy of snow, 2-D stratigraphy of snow.
    Abstract: Precise measurements of snow structural parameters are crucial to understand the formation of snowpacks by deposition and metamorphism and to characterize the stratigraphy for many applications and remote sensing in particular. The area-wide acquisition of structural parameters at high spatial resolution from state-of-the-art methods is, however, still cumbersome, since the time required for a single profile is a serious practical limitation. As a remedy we have developed a statistical model to extract three major snow structural parameters: density, correlation length, and specific surface area (SSA) solely from the SnowMicroPen (SMP), a high-resolution penetrometer, which allows a meter profile to be measured with millimeter resolution in less than 1 min. The model was calibrated by combining SMP data with 3-D microstructural data from microcomputed tomography which was used to reconstruct full-depth snow profiles from different snow climates (Alpine, Arctic, and Antarctic). Density, correlation length, and SSA were derived from the SMP with a mean relative error of 10.6%, 16.4%, and 23.1%, respectively. For validation, we compared the density and SSA derived from the SMP to traditional measurements and near-infrared profiles. We demonstrate the potential of our method by the retrieval of a two-dimensional stratigraphy at Kohnen Station, Antarctica, from a 46 m long SMP transect. The result clearly reveals past depositional and metamorphic events, and our findings show that the SMP can be used as an objective, high-resolution tool to retrieve essential snow structural parameters efficiently in the field.

    @Article{prokschLoeweSchneebeliJGR2015SnowParametersFromSnowMicroPenAndMicroCT,
    author = {Proksch, Martin and L\"owe, Henning and Schneebeli, Martin},
    title = {Density, specific surface area, and correlation length of snow measured by high-resolution penetrometry},
    journal = {J. Geophys. Res. Earth Surf.},
    year = {2015},
    pages = {346-362},
    abstract = {Precise measurements of snow structural parameters are crucial to understand the formation of snowpacks by deposition and metamorphism and to characterize the stratigraphy for many applications and remote sensing in particular. The area-wide acquisition of structural parameters at high spatial resolution from state-of-the-art methods is, however, still cumbersome, since the time required for a single profile is a serious practical limitation. As a remedy we have developed a statistical model to extract three major snow structural parameters: density, correlation length, and specific surface area (SSA) solely from the SnowMicroPen (SMP), a high-resolution penetrometer, which allows a meter profile to be measured with millimeter resolution in less than 1 min. The model was calibrated by combining SMP data with 3-D microstructural data from microcomputed tomography which was used to reconstruct full-depth snow profiles from different snow climates (Alpine, Arctic, and Antarctic). Density, correlation length, and SSA were derived from the SMP with a mean relative error of 10.6%, 16.4%, and 23.1%, respectively. For validation, we compared the density and SSA derived from the SMP to traditional measurements and near-infrared profiles. We demonstrate the potential of our method by the retrieval of a two-dimensional stratigraphy at Kohnen Station, Antarctica, from a 46 m long SMP transect. The result clearly reveals past depositional and metamorphic events, and our findings show that the SMP can be used as an objective, high-resolution tool to retrieve essential snow structural parameters efficiently in the field.},
    doi = {10.1002/2014JF003266},
    file = {:prokschLoeweSchneebeliJGR2015SnowParametersFromSnowMicroPenAndMicroCT.pdf.pdf:PDF},
    issue = {120},
    keywords = {Snow characterisation, correlation length, snow density, specific surface area, SSA, Snow Micro Pen, SMP, micro-CT, Statistical model, Statistical model relating micro-CT structure to SMP force for many snow data, snow density retrieval, correlation length, and SSA in the field, Efficient retrieval of spatial variability and 2-D stratigraphy of snow, 2-D stratigraphy of snow},
    owner = {ofrey},
    pdf = {../../../docs/prokschLoeweSchneebeliJGR2015SnowParametersFromSnowMicroPenAndMicroCT.pdf},
    
    }
    


  36. Shaun Quegan and M.R. Lomas. The Interaction Between Faraday Rotation and System Effects in Synthetic Aperture Radar Measurements of Backscatter and Biomass. Geoscience and Remote Sensing, IEEE Transactions on, 53(8):4299-4312, August 2015. Keyword(s): Faraday effect, backscatter, geophysical techniques, synthetic aperture radar, European space agency BIOMASS mission, P-band radar, backscatter synthetic aperture radar measurement, biomass estimation error, biomass synthetic aperture radar measurement, channel imbalance deviation magnitude, distortion term amplitude, distortion term phase, faraday rotation, first-order analysis, long-wavelength space-based radar, polarimetric backscattering coefficient, polarimetric scattering matrix measurement, power-law relation, signal-to-noise ratio, stringent condition, system distortion, Backscatter, Biomass, Crosstalk, Distortion measurement, Faraday effect, Noise, Scattering, Biomass, Faraday rotation, calibration, long-wavelength radar, polarimetric measurements, system distortion.
    Abstract: For long-wavelength space-based radars, such as the P-band radar on the recently selected European Space Agency BIOMASS mission, system distortions (crosstalk and channel imbalance), Faraday rotation, and system noise all combine to degrade the measurements. A first-order analysis of these effects on the measurements of the polarimetric scattering matrix is used to derive differentiable expressions for the errors in the polarimetric backscattering coefficients in the presence of Faraday rotation. Both the amplitudes and phases of the distortion terms are shown to be important in determining the errors and their maximum values. Exact simulations confirm the accuracy and predictions of the first-order analysis. Under an assumed power-law relation between hv and the biomass, the system distortions and noise are converted into biomass estimation errors, and it is shown that the magnitude of the deviation of the channel imbalance from unity must be 4-5 dB less than the crosstalk, or it will dominate the error in the biomass. For uncalibrated data and midrange values of biomass, the crosstalk must be less than -24 dB if the maximum possible error in the biomass is to be within 20% of its true value. A less stringent condition applies if the amplitudes and phases of the distortion terms are considered random since errors near the maximum possible are very unlikely. For lower values of the biomass, the noise becomes increasingly important because the hv signal-to-noise ratio is smaller.

    @Article{queganLomasTGRS2015FaradayRotEffectSARData,
    author = {Shaun Quegan and Lomas, M.R.},
    title = {The Interaction Between Faraday Rotation and System Effects in Synthetic Aperture Radar Measurements of Backscatter and Biomass},
    journal = {Geoscience and Remote Sensing, IEEE Transactions on},
    year = {2015},
    volume = {53},
    number = {8},
    pages = {4299-4312},
    month = {Aug},
    issn = {0196-2892},
    abstract = {For long-wavelength space-based radars, such as the P-band radar on the recently selected European Space Agency BIOMASS mission, system distortions (crosstalk and channel imbalance), Faraday rotation, and system noise all combine to degrade the measurements. A first-order analysis of these effects on the measurements of the polarimetric scattering matrix is used to derive differentiable expressions for the errors in the polarimetric backscattering coefficients in the presence of Faraday rotation. Both the amplitudes and phases of the distortion terms are shown to be important in determining the errors and their maximum values. Exact simulations confirm the accuracy and predictions of the first-order analysis. Under an assumed power-law relation between hv and the biomass, the system distortions and noise are converted into biomass estimation errors, and it is shown that the magnitude of the deviation of the channel imbalance from unity must be 4-5 dB less than the crosstalk, or it will dominate the error in the biomass. For uncalibrated data and midrange values of biomass, the crosstalk must be less than -24 dB if the maximum possible error in the biomass is to be within 20% of its true value. A less stringent condition applies if the amplitudes and phases of the distortion terms are considered random since errors near the maximum possible are very unlikely. For lower values of the biomass, the noise becomes increasingly important because the hv signal-to-noise ratio is smaller.},
    doi = {10.1109/TGRS.2015.2395138},
    file = {:queganLomasTGRS2015FaradayRotEffectSARData.pdf:PDF},
    keywords = {Faraday effect;backscatter;geophysical techniques;synthetic aperture radar;European space agency BIOMASS mission;P-band radar;backscatter synthetic aperture radar measurement;biomass estimation error;biomass synthetic aperture radar measurement;channel imbalance deviation magnitude;distortion term amplitude;distortion term phase;faraday rotation;first-order analysis;long-wavelength space-based radar;polarimetric backscattering coefficient;polarimetric scattering matrix measurement;power-law relation;signal-to-noise ratio;stringent condition;system distortion;Backscatter;Biomass;Crosstalk;Distortion measurement;Faraday effect;Noise;Scattering;Biomass;Faraday rotation;calibration;long-wavelength radar;polarimetric measurements;system distortion},
    pdf = {../../../docs/queganLomasTGRS2015FaradayRotEffectSARData.pdf},
    
    }
    


  37. M. Rodriguez-Cassola, P. Prats-Iraola, F. De Zan, R. Scheiber, A. Reigber, D. Geudtner, and A. Moreira. Doppler-Related Distortions in TOPS SAR Images. IEEE Trans. Geosci. Remote Sens., 53(1):25-35, January 2015. Keyword(s): SAR Processing, SAR Focusing, Azimuth Focusing, TOPS, Doppler radar, approximation theory, beam steering, compensation, distortion, geophysical image processing, radar antennas, radar imaging, radar interferometry, remote sensing by radar, synthetic aperture radar, terrain mapping, SAR image formation scheme, Sentinel-1 interferometric extra wide swath mode, Sentinel-1 interferometric wide swath mode, TOPS SAR image, TerraSAR-X TOPS, azimuth distortion, burst mode acquisition, compensation strategy, focused SAR image, intrapulse motion, low Earth orbit SAR, radar antenna, range distortion, steering, stop-and-go approximation, terrain observation with progressive scan, time-varying Doppler centroid, Azimuth, Doppler effect, Geometry, Orbits, Spaceborne radar, Surfaces, Synthetic aperture radar, Burst-mode acquisitions, Sentinel-1, TerraSAR-X (TerraSAR-X), Terrain Observation with Progressive Scans (TOPS), spaceborne SAR missions, synthetic aperture radar (SAR), wide-swath SAR modes.
    Abstract: A direct consequence of the TOPS acquisition geometry and the steering in azimuth of the antenna is the time-varying Doppler centroid within bursts. If this fact is not properly accommodated during SAR image formation, undesired distortions in both azimuth and range dimensions of the focused SAR images may appear. Azimuth distortions are caused by the local mismatch of both squint and topography. Range distortions arise from the inaccurate accommodation of the intrapulse motion of the platform, usually known as the stop-and-go approximation. Conventional spaceborne SAR image formation schemes will be, in general, unable to provide accurate TOPS SAR images. These distortions are discussed and evaluated for exemplary low-Earth-orbit SAR scenarios. Compensation strategies are presented and validated with TerraSAR-X TOPS data. A discussion of the potential impact on the Sentinel-1 interferometric-wide-swath and extra-wide-swath modes (i.e, TOPS) is also given.

    @Article{rodriguezCassolaPratsDeZanScheiberReigberGeudtnerMoreiraTGRS2015TOPSDopplerRelDistorsion,
    author = {Rodriguez-Cassola, M. and Prats-Iraola, P. and De Zan, F. and Scheiber, R. and Reigber, A. and Geudtner, D. and Moreira, A.},
    title = {Doppler-Related Distortions in {TOPS} {SAR} Images},
    journal = {IEEE Trans. Geosci. Remote Sens.},
    year = {2015},
    volume = {53},
    number = {1},
    pages = {25-35},
    month = jan,
    issn = {0196-2892},
    abstract = {A direct consequence of the TOPS acquisition geometry and the steering in azimuth of the antenna is the time-varying Doppler centroid within bursts. If this fact is not properly accommodated during SAR image formation, undesired distortions in both azimuth and range dimensions of the focused SAR images may appear. Azimuth distortions are caused by the local mismatch of both squint and topography. Range distortions arise from the inaccurate accommodation of the intrapulse motion of the platform, usually known as the stop-and-go approximation. Conventional spaceborne SAR image formation schemes will be, in general, unable to provide accurate TOPS SAR images. These distortions are discussed and evaluated for exemplary low-Earth-orbit SAR scenarios. Compensation strategies are presented and validated with TerraSAR-X TOPS data. A discussion of the potential impact on the Sentinel-1 interferometric-wide-swath and extra-wide-swath modes (i.e, TOPS) is also given.},
    doi = {10.1109/TGRS.2014.2313068},
    file = {:rodriguezCassolaPratsDeZanScheiberReigberGeudtnerMoreiraTGRS2015TOPSDopplerRelDistorsion.pdf:PDF},
    keywords = {SAR Processing, SAR Focusing, Azimuth Focusing, TOPS, Doppler radar;approximation theory;beam steering;compensation;distortion;geophysical image processing;radar antennas;radar imaging;radar interferometry;remote sensing by radar;synthetic aperture radar;terrain mapping;SAR image formation scheme;Sentinel-1 interferometric extra wide swath mode;Sentinel-1 interferometric wide swath mode;TOPS SAR image;TerraSAR-X TOPS;azimuth distortion;burst mode acquisition;compensation strategy;focused SAR image;intrapulse motion;low Earth orbit SAR;radar antenna;range distortion;steering;stop-and-go approximation;terrain observation with progressive scan;time-varying Doppler centroid;Azimuth;Doppler effect;Geometry;Orbits;Spaceborne radar;Surfaces;Synthetic aperture radar;Burst-mode acquisitions;Sentinel-1;TerraSAR-X (TerraSAR-X);Terrain Observation with Progressive Scans (TOPS);spaceborne SAR missions;synthetic aperture radar (SAR);wide-swath SAR modes},
    pdf = {../../../docs/rodriguezCassolaPratsDeZanScheiberReigberGeudtnerMoreiraTGRS2015TOPSDopplerRelDistorsion.pdf},
    
    }
    


  38. M. Rodriguez-Cassola, P. Prats-Iraola, F. De Zan, R. Scheiber, A. Reigber, D. Geudtner, and A. Moreira. Doppler-Related Distortions in TOPS SAR Images. IEEE Transactions on Geoscience and Remote Sensing, 53(1):25-35, January 2015. Keyword(s): approximation theory, beam steering, compensation, distortion, Doppler radar, geophysical image processing, radar antennas, radar imaging, radar interferometry, remote sensing by radar, synthetic aperture radar, terrain mapping, TOPS SAR image, steering, radar antenna, time-varying Doppler centroid, focused SAR image, azimuth distortion, range distortion, intrapulse motion, stop-and-go approximation, SAR image formation scheme, low Earth orbit SAR, compensation strategy, TerraSAR-X TOPS, Sentinel-1 interferometric wide swath mode, Sentinel-1 interferometric extra wide swath mode, burst mode acquisition, terrain observation with progressive scan, Azimuth, Synthetic aperture radar, Doppler effect, Surfaces, Orbits, Spaceborne radar, Geometry, Burst-mode acquisitions, Sentinel-1, spaceborne SAR missions, synthetic aperture radar (SAR), Terrain Observation with Progressive Scans (TOPS), TerraSAR-X (TerraSAR-X), wide-swath SAR modes, Burst-mode acquisitions, Sentinel-1, spaceborne SAR missions, synthetic aperture radar (SAR), Terrain Observation with Progressive Scans (TOPS), TerraSAR-X (TerraSAR-X), wide-swath SAR modes.
    Abstract: A direct consequence of the TOPS acquisition geometry and the steering in azimuth of the antenna is the time-varying Doppler centroid within bursts. If this fact is not properly accommodated during SAR image formation, undesired distortions in both azimuth and range dimensions of the focused SAR images may appear. Azimuth distortions are caused by the local mismatch of both squint and topography. Range distortions arise from the inaccurate accommodation of the intrapulse motion of the platform, usually known as the stop-and-go approximation. Conventional spaceborne SAR image formation schemes will be, in general, unable to provide accurate TOPS SAR images. These distortions are discussed and evaluated for exemplary low-Earth-orbit SAR scenarios. Compensation strategies are presented and validated with TerraSAR-X TOPS data. A discussion of the potential impact on the Sentinel-1 interferometric-wide-swath and extra-wide-swath modes (i.e, TOPS) is also given.

    @Article{rodriguezPratsDeZanScheiberReigberGeudtnerMoreiraTGRS2015DopplerRelatedDistortionsTOPSSARImages,
    author = {M. {Rodriguez-Cassola} and P. {Prats-Iraola} and F. {De Zan} and R. {Scheiber} and A. {Reigber} and D. {Geudtner} and A. {Moreira}},
    title = {Doppler-Related Distortions in TOPS SAR Images},
    journal = {IEEE Transactions on Geoscience and Remote Sensing},
    year = {2015},
    volume = {53},
    number = {1},
    pages = {25-35},
    month = {Jan},
    issn = {1558-0644},
    abstract = {A direct consequence of the TOPS acquisition geometry and the steering in azimuth of the antenna is the time-varying Doppler centroid within bursts. If this fact is not properly accommodated during SAR image formation, undesired distortions in both azimuth and range dimensions of the focused SAR images may appear. Azimuth distortions are caused by the local mismatch of both squint and topography. Range distortions arise from the inaccurate accommodation of the intrapulse motion of the platform, usually known as the stop-and-go approximation. Conventional spaceborne SAR image formation schemes will be, in general, unable to provide accurate TOPS SAR images. These distortions are discussed and evaluated for exemplary low-Earth-orbit SAR scenarios. Compensation strategies are presented and validated with TerraSAR-X TOPS data. A discussion of the potential impact on the Sentinel-1 interferometric-wide-swath and extra-wide-swath modes (i.e, TOPS) is also given.},
    doi = {10.1109/TGRS.2014.2313068},
    keywords = {approximation theory;beam steering;compensation;distortion;Doppler radar;geophysical image processing;radar antennas;radar imaging;radar interferometry;remote sensing by radar;synthetic aperture radar;terrain mapping;TOPS SAR image;steering;radar antenna;time-varying Doppler centroid;focused SAR image;azimuth distortion;range distortion;intrapulse motion;stop-and-go approximation;SAR image formation scheme;low Earth orbit SAR;compensation strategy;TerraSAR-X TOPS;Sentinel-1 interferometric wide swath mode;Sentinel-1 interferometric extra wide swath mode;burst mode acquisition;terrain observation with progressive scan;Azimuth;Synthetic aperture radar;Doppler effect;Surfaces;Orbits;Spaceborne radar;Geometry;Burst-mode acquisitions;Sentinel-1;spaceborne SAR missions;synthetic aperture radar (SAR);Terrain Observation with Progressive Scans (TOPS);TerraSAR-X (TerraSAR-X);wide-swath SAR modes;Burst-mode acquisitions;Sentinel-1;spaceborne SAR missions;synthetic aperture radar (SAR);Terrain Observation with Progressive Scans (TOPS);TerraSAR-X (TerraSAR-X);wide-swath SAR modes},
    owner = {ofrey},
    
    }
    


  39. Maria J. Sanjuan-Ferrer, Irena Hajnsek, K. P. Papathanassiou, and Alberto Moreira. A New Detection Algorithm for Coherent Scatterers in SAR Data. IEEE Transactions on Geoscience and Remote Sensing, 53(11):6293-6307, November 2015. Keyword(s): SAR Processing, Interferometry, SAR Interferometry, Persistent Scatterer Interferometry, PSI, Detector, Candidate Selection, Coherent Scatterer, remote sensing by radar, synthetic aperture radar, SAR data, TerraSAR-X acquisitions, coherent scatterers, detection algorithm, generalized likelihood ratio test approach, natural environments, natural scenarios, permanent-scatterer interferometry techniques, point-like scatterers, scattering temporal stability, single SAR image, spectral diversity techniques, sublook coherence approach, sublook entropy approach, synthetic aperture radar, urban environments, Bandwidth, Clutter, Coherence, Spatial resolution, Speckle, Synthetic aperture radar, Coherent scatterers (CSs), likelihood ratio test, signal processing, synthetic aperture radar (SAR), target detection.
    Abstract: In contrast to the random nature of synthetic aperture radar (SAR) data, it is also possible to identify bright targets whose scattering properties scarcely vary within imaging and time. These targets are commonly named point-like scatterers and can be found in both urban and natural environments. Permanent-scatterer interferometry techniques single out stable scatterers in a stack of SAR images, which preserve their backscattering stability along time. However, this methodology may not be optimum in natural scenarios, where the temporal stability of the scattering is rather reduced, or when the number of available SAR acquisitions is significantly small. Consequently, alternative methods have come out to detect stable scatters in a single SAR image, thus reducing all constraints related to their temporal behavior. Particularly, spectral diversity techniques are exploited to detect the so-called coherent scatterers. In this paper, a new detection scheme based on the generalized likelihood ratio test approach (GLRTA) is proposed, and its performance is extensively evaluated compared with three of the traditional methods, namely, the sublook coherence approach, the sublook entropy approach, and the phase variance approach. Remarkably, the GLRTA exploits both amplitude and phase information and does not need any further averaging (apart from sublooking processing with reduced signal bandwidth). The presented analysis is conducted both theoretically and with simulated data. For all scenarios, the new detector outperforms the other methods. The obtained results are validated also on real data. Finally, the proposed GLRTA is tested over different scattering scenarios, considering three TerraSAR-X acquisitions.

    @Article{sanjuanFerrerHajnsekPapathanassiouMoreiraTGRS2015CoherentScattererDetector,
    author = {Sanjuan-Ferrer, Maria J. and Hajnsek, Irena and Papathanassiou, K. P. and Moreira, Alberto},
    title = {A New Detection Algorithm for Coherent Scatterers in {SAR} Data},
    journal = {IEEE Transactions on Geoscience and Remote Sensing},
    year = {2015},
    volume = {53},
    number = {11},
    pages = {6293-6307},
    month = nov,
    issn = {0196-2892},
    abstract = {In contrast to the random nature of synthetic aperture radar (SAR) data, it is also possible to identify bright targets whose scattering properties scarcely vary within imaging and time. These targets are commonly named point-like scatterers and can be found in both urban and natural environments. Permanent-scatterer interferometry techniques single out stable scatterers in a stack of SAR images, which preserve their backscattering stability along time. However, this methodology may not be optimum in natural scenarios, where the temporal stability of the scattering is rather reduced, or when the number of available SAR acquisitions is significantly small. Consequently, alternative methods have come out to detect stable scatters in a single SAR image, thus reducing all constraints related to their temporal behavior. Particularly, spectral diversity techniques are exploited to detect the so-called coherent scatterers. In this paper, a new detection scheme based on the generalized likelihood ratio test approach (GLRTA) is proposed, and its performance is extensively evaluated compared with three of the traditional methods, namely, the sublook coherence approach, the sublook entropy approach, and the phase variance approach. Remarkably, the GLRTA exploits both amplitude and phase information and does not need any further averaging (apart from sublooking processing with reduced signal bandwidth). The presented analysis is conducted both theoretically and with simulated data. For all scenarios, the new detector outperforms the other methods. The obtained results are validated also on real data. Finally, the proposed GLRTA is tested over different scattering scenarios, considering three TerraSAR-X acquisitions.},
    doi = {10.1109/TGRS.2015.2438173},
    file = {:sanjuanFerrerHajnsekPapathanassiouMoreiraTGRS2015CoherentScattererDetector.pdf:PDF},
    keywords = {SAR Processing, Interferometry, SAR Interferometry, Persistent Scatterer Interferometry, PSI, Detector, Candidate Selection, Coherent Scatterer, remote sensing by radar;synthetic aperture radar;SAR data;TerraSAR-X acquisitions;coherent scatterers;detection algorithm;generalized likelihood ratio test approach;natural environments;natural scenarios;permanent-scatterer interferometry techniques;point-like scatterers;scattering temporal stability;single SAR image;spectral diversity techniques;sublook coherence approach;sublook entropy approach;synthetic aperture radar;urban environments;Bandwidth;Clutter;Coherence;Spatial resolution;Speckle;Synthetic aperture radar;Coherent scatterers (CSs);likelihood ratio test;signal processing;synthetic aperture radar (SAR);target detection},
    owner = {ofrey},
    
    }
    


  40. Eugenio Sansosti, Michele Manunta, Francesco Casu, Manuela Bonano, Chandrakanta Ojha, Maria Marsella, and Riccardo Lanari. Radar remote sensing from space for surface deformation analysis: present and future opportunities from the new SAR sensor generation. Rendiconti Lincei, 26(1):75-84, 2015. Keyword(s): SAR Processing, Persistent Scatterer Interferometry, PSI, DINSAR, Differential SAR Interferometry, Ground deformation, Remote Sensing, Synthetic Aperture Radar (SAR), DInSAR, Urban monitoring, Wide area monitoring, Sentinel-1, ENVISAT, ASAR, COSMO-SkyMed, X-band, C-band, Spaceborne SAR.
    Abstract: This paper discusses, through two selected case studies based on real data, how the availability of the new generation of Synthetic Aperture Radar (SAR) sensors, characterized by reduced revisiting time and improved spatial resolution or coverage, is impacting the exploitation of Differential SAR Interferometry (DInSAR) techniques for the detection and monitoring of deformation phenomena. The presented analysis is carried out using X-band data of the COSMO-SkyMed constellation satellites, as well as C-band data acquired by the Sentinel-1A sensor; furthermore, we compare the achieved results to those based on first-generation ERS-1/2 and ENVISAT satellite data. The first case study shows how the COSMO-SkyMed X-band SAR systems open new opportunities for the detection and monitoring of deformation phenomena at the scale of a single building, even when they are characterized by a rather fast dynamic. The second experiment is based on the Sentinel-1A DInSAR measurements and permits us to envisage new scenarios for deformation analysis of very wide areas. The final discussion is devoted to summarise the lessons learned through the presented case studies and to identify the main future actions needed for a full exploitation of the surface deformation measurement capability provided by the new generation of SAR sensor.

    @Article{sansostiManuntaCasuBonanoOjhaMarsellaLanari2015PSIDINSAR,
    author = {Sansosti, Eugenio and Manunta, Michele and Casu, Francesco and Bonano, Manuela and Ojha, Chandrakanta and Marsella, Maria and Lanari, Riccardo},
    title = {Radar remote sensing from space for surface deformation analysis: present and future opportunities from the new {SAR} sensor generation},
    journal = {Rendiconti Lincei},
    year = {2015},
    volume = {26},
    number = {1},
    pages = {75-84},
    issn = {2037-4631},
    abstract = {This paper discusses, through two selected case studies based on real data, how the availability of the new generation of Synthetic Aperture Radar (SAR) sensors, characterized by reduced revisiting time and improved spatial resolution or coverage, is impacting the exploitation of Differential SAR Interferometry (DInSAR) techniques for the detection and monitoring of deformation phenomena. The presented analysis is carried out using X-band data of the COSMO-SkyMed constellation satellites, as well as C-band data acquired by the Sentinel-1A sensor; furthermore, we compare the achieved results to those based on first-generation ERS-1/2 and ENVISAT satellite data. The first case study shows how the COSMO-SkyMed X-band SAR systems open new opportunities for the detection and monitoring of deformation phenomena at the scale of a single building, even when they are characterized by a rather fast dynamic. The second experiment is based on the Sentinel-1A DInSAR measurements and permits us to envisage new scenarios for deformation analysis of very wide areas. The final discussion is devoted to summarise the lessons learned through the presented case studies and to identify the main future actions needed for a full exploitation of the surface deformation measurement capability provided by the new generation of SAR sensor.},
    doi = {10.1007/s12210-015-0440-3},
    file = {:sansostiManuntaCasuBonanoOjhaMarsellaLanari2015PSIDINSAR.pdf:PDF},
    keywords = {SAR Processing, Persistent Scatterer Interferometry, PSI, DINSAR, Differential SAR Interferometry, Ground deformation, Remote Sensing, Synthetic Aperture Radar (SAR), DInSAR, Urban monitoring, Wide area monitoring, Sentinel-1, ENVISAT, ASAR, COSMO-SkyMed, X-band,C-band, Spaceborne SAR},
    pdf = {../../../docs/sansostiManuntaCasuBonanoOjhaMarsellaLanari2015PSIDINSAR.pdf},
    publisher = {Springer Milan},
    url = {http://dx.doi.org/10.1007/s12210-015-0440-3},
    
    }
    


  41. Maurizio Santoro, Andr Beaudoin, Christian Beer, Oliver Cartus, Johan E.S. Fransson, Ronald J. Hall, Carsten Pathe, Christiane Schmullius, Dmitry Schepaschenko, Anatoly Shvidenko, Martin Thurner, and Urs Wegmuller. Forest growing stock volume of the northern hemisphere: Spatially explicit estimates for 2010 derived from Envisat {ASAR}. Remote Sensing of Environment, 168:316 - 334, 2015. Keyword(s): Envisat ASAR, Forest, Growing stock volume, Biomass, MODIS Vegetation Continuous Fields, BIOMASAR, Northern hemisphere.
    Abstract: This paper presents and assesses spatially explicit estimates of forest growing stock volume (GSV) of the northern hemisphere (north of 10 deg N) from hyper-temporal observations of Envisat Advanced Synthetic Aperture Radar (ASAR) backscattered intensity using the BIOMASAR algorithm. Approximately 70,000 ASAR images at a pixel size of 0.01 deg were used to estimate GSV representative for the year 2010. The spatial distribution of the GSV across four ecological zones (polar, boreal, temperate, subtropical) was well captured by the ASAR-based estimates. The uncertainty of the retrieved GSV was smallest in boreal and temperate forest <30% for approximately 80% of the forest area) and largest in subtropical forest. ASAR-derived GSV averages at the level of administrative units were mostly in agreement with inventory-derived estimates. Underestimation occurred in regions of very high GSV >300 m3/ha) and fragmented forest landscapes. For the major forested countries within the study region, the relative RMSE between ASAR-derived GSV averages at provincial level and corresponding values from National Forest Inventory was between 12% and 45% (average: 29%).

    @Article{santoroEtAlRSE2015GrowingStockVolume,
    author = {Maurizio Santoro and Andr\'e Beaudoin and Christian Beer and Oliver Cartus and Johan E.S. Fransson and Ronald J. Hall and Carsten Pathe and Christiane Schmullius and Dmitry Schepaschenko and Anatoly Shvidenko and Martin Thurner and Urs Wegmuller},
    title = {Forest growing stock volume of the northern hemisphere: Spatially explicit estimates for 2010 derived from Envisat \{ASAR\}},
    journal = {Remote Sensing of Environment},
    year = {2015},
    volume = {168},
    pages = {316 - 334},
    issn = {0034-4257},
    abstract = {This paper presents and assesses spatially explicit estimates of forest growing stock volume (GSV) of the northern hemisphere (north of 10 deg N) from hyper-temporal observations of Envisat Advanced Synthetic Aperture Radar (ASAR) backscattered intensity using the BIOMASAR algorithm. Approximately 70,000 ASAR images at a pixel size of 0.01 deg were used to estimate GSV representative for the year 2010. The spatial distribution of the GSV across four ecological zones (polar, boreal, temperate, subtropical) was well captured by the ASAR-based estimates. The uncertainty of the retrieved GSV was smallest in boreal and temperate forest <30% for approximately 80% of the forest area) and largest in subtropical forest. ASAR-derived GSV averages at the level of administrative units were mostly in agreement with inventory-derived estimates. Underestimation occurred in regions of very high GSV >300 m3/ha) and fragmented forest landscapes. For the major forested countries within the study region, the relative RMSE between ASAR-derived GSV averages at provincial level and corresponding values from National Forest Inventory was between 12% and 45% (average: 29%).},
    doi = {http://dx.doi.org/10.1016/j.rse.2015.07.005},
    file = {:santoroEtAlRSE2015GrowingStockVolume.pdf:PDF},
    keywords = {Envisat ASAR, Forest, Growing stock volume, Biomass, MODIS Vegetation Continuous Fields, BIOMASAR, Northern hemisphere},
    url = {http://www.sciencedirect.com/science/article/pii/S003442571530064X},
    
    }
    


  42. Michael Schmitt, Muhammad Shahzad, and Xiao Xiang Zhu. Reconstruction of individual trees from multi-aspect TomoSAR data. Remote Sensing of Environment, 165:175-185, 2015. Keyword(s): SAR Processing, SAR tomography, Synthetic aperture radar (SAR), Multi-aspect, Trees, 3D reconstruction, Forested areas, Point cloud segmentation.
    Abstract: Abstract The localization and reconstruction of individual trees as well as the extraction of their geometrical parameters is an important field of research in both forestry and remote sensing. While the current state-of-the-art mostly focuses on the exploitation of optical imagery and airborne LiDAR data, modern SAR sensors have not yet met the interest of the research community in that regard. This paper presents a prototypical processing chain for the reconstruction of individual deciduous trees: First, single-pass multi-baseline InSAR data acquired from multiple aspect angles are used for the generation of a layover- and shadow-free 3D point cloud by tomographic SAR processing. The resulting point cloud is then segmented by unsupervised mean shift clustering, before ellipsoid models are fitted to the points of each cluster. From these 3D ellipsoids the relevant geometrical tree parameters are extracted. Evaluation with respect to a manually derived reference dataset prove that almost 74% of all trees are successfully segmented and reconstructed, thus providing a promising perspective for further research toward individual tree recognition from SAR data.

    @Article{schmittShahzadZhu2015RSEonTomoSARSingleTree,
    author = {Michael Schmitt and Muhammad Shahzad and Xiao Xiang Zhu},
    title = {Reconstruction of individual trees from multi-aspect TomoSAR data},
    journal = {Remote Sensing of Environment},
    year = {2015},
    volume = {165},
    pages = {175-185},
    issn = {0034-4257},
    abstract = {Abstract The localization and reconstruction of individual trees as well as the extraction of their geometrical parameters is an important field of research in both forestry and remote sensing. While the current state-of-the-art mostly focuses on the exploitation of optical imagery and airborne LiDAR data, modern SAR sensors have not yet met the interest of the research community in that regard. This paper presents a prototypical processing chain for the reconstruction of individual deciduous trees: First, single-pass multi-baseline InSAR data acquired from multiple aspect angles are used for the generation of a layover- and shadow-free 3D point cloud by tomographic SAR processing. The resulting point cloud is then segmented by unsupervised mean shift clustering, before ellipsoid models are fitted to the points of each cluster. From these 3D ellipsoids the relevant geometrical tree parameters are extracted. Evaluation with respect to a manually derived reference dataset prove that almost 74% of all trees are successfully segmented and reconstructed, thus providing a promising perspective for further research toward individual tree recognition from SAR data.},
    doi = {http://dx.doi.org/10.1016/j.rse.2015.05.012},
    file = {:schmittShahzadZhu2015RSEonTomoSARSingleTree.pdf:PDF},
    keywords = {SAR Processing, SAR tomography, Synthetic aperture radar (SAR), Multi-aspect, Trees, 3D reconstruction,Forested areas, Point cloud segmentation},
    pdf = {../../../docs/schmittShahzadZhu2015RSEonTomoSARSingleTree.pdf},
    url = {http://www.sciencedirect.com/science/article/pii/S0034425715300110},
    
    }
    


  43. Zoran Sjanic and Frederik Gustafsson. Simultaneous navigation and synthetic aperture radar focusing. IEEE Transactions on Aerospace and Electronic Systems, 51(2):1253-1266, April 2015. Keyword(s): SAR Focusing, Autofocus, SLAM, Simultaneous Localization and Mapping, autonomous aerial vehicles, image resolution, radar imaging, radar resolution, radionavigation, synthetic aperture radar, synthetic aperture radar imaging equipment, image resolution, flying platform, image focusing, real-time SAR imaging, navigation system, trajectory joint estimation, unmanned aerial vehicle navigation, azimuth position error, Synthetic aperture radar, Trajectory, Radar imaging, Navigation, Entropy, Focusing.
    Abstract: Synthetic aperture radar (SAR) equipment is a radar imaging system that can be used to create high-resolution images of a scene by utilizing the movement of a flying platform. Knowledge of the platform's trajectory is essential to get good and focused images. An emerging application field is real-time SAR imaging using small and cheap platforms where estimation errors in navigation systems imply unfocused images. This contribution investigates a joint estimation of the trajectory and SAR image. Starting with a nominal trajectory, we successively improve the image by optimizing a focus measure and updating the trajectory accordingly. The method is illustrated using simulations using typical navigation performance of an unmanned aerial vehicle. One real data set is used to show feasibility, where the result indicates that, in particular, the azimuth position error is decreased as the image focus is iteratively improved.

    @Article{sjanicGustafssonTAES2015SLAMandSARFocusing,
    author = {Zoran Sjanic and Frederik Gustafsson},
    title = {Simultaneous navigation and synthetic aperture radar focusing},
    journal = {IEEE Transactions on Aerospace and Electronic Systems},
    year = {2015},
    volume = {51},
    number = {2},
    pages = {1253-1266},
    month = apr,
    issn = {0018-9251},
    abstract = {Synthetic aperture radar (SAR) equipment is a radar imaging system that can be used to create high-resolution images of a scene by utilizing the movement of a flying platform. Knowledge of the platform's trajectory is essential to get good and focused images. An emerging application field is real-time SAR imaging using small and cheap platforms where estimation errors in navigation systems imply unfocused images. This contribution investigates a joint estimation of the trajectory and SAR image. Starting with a nominal trajectory, we successively improve the image by optimizing a focus measure and updating the trajectory accordingly. The method is illustrated using simulations using typical navigation performance of an unmanned aerial vehicle. One real data set is used to show feasibility, where the result indicates that, in particular, the azimuth position error is decreased as the image focus is iteratively improved.},
    doi = {10.1109/TAES.2015.120820},
    file = {:sjanicGustafssonTAES2015SLAMandSARFocusing.pdf:PDF},
    keywords = {SAR Focusing, Autofocus, SLAM, Simultaneous Localization and Mapping, autonomous aerial vehicles;image resolution;radar imaging;radar resolution;radionavigation;synthetic aperture radar;synthetic aperture radar imaging equipment;image resolution;flying platform;image focusing;real-time SAR imaging;navigation system;trajectory joint estimation;unmanned aerial vehicle navigation;azimuth position error;Synthetic aperture radar;Trajectory;Radar imaging;Navigation;Entropy;Focusing},
    owner = {ofrey},
    
    }
    


  44. Maciej J. Soja, H.J. Persson, and Lars M.H. Ulander. Estimation of Forest Biomass From Two-Level Model Inversion of Single-Pass InSAR Data. IEEE Trans. Geosci. Remote Sens., 53(9):5083-5099, September 2015. Keyword(s): data acquisition, digital elevation models, forestry, radar interferometry, remote sensing by radar, synthetic aperture radar, vegetation, AD 2008, AD 2010, AD 2011, AD 2012, AD 2013, InSAR processing, Krycklan feature, Remningstorp feature, Swedish test site, VV-polarized TanDEM-X acquisition, aboveground biomass estimation, biomass predictor, canopy density, digital terrain model, forest biomass estimation, forest height, hemiboreal forest, northern Sweden, single-pass InSAR data, single-pass interferometric synthetic aperture radar data, southern Sweden, two-level model inversion, Biological system modeling, Biomass, Computational modeling, Correlation, Decorrelation, Estimation, Synthetic aperture radar, Aboveground biomass (AGB), TanDEM-X (TDM), canopy density, forest height, interferometric model, interferometric syntheticaperture radar (InSAR), two-level model (TLM).
    Abstract: A model for aboveground biomass estimation from single-pass interferometric synthetic aperture radar (InSAR) data is presented. Forest height and canopy density estimates dh and n0, respectively, obtained from two-level model (TLM) inversion, are used as biomass predictors. Eighteen bistatic VV-polarized TanDEM-X (TDM) acquisitions are used, made over two Swedish test sites in the summers of 2011, 2012, and 2013 (nominal incidence angle: 41 deg, height-of-ambiguity: 32-63 m) . Remningstorp features a hemiboreal forest in southern Sweden, with flat topography and where 32 circular plots have been sampled between 2010 and 2011 (area: 0.5 ha; biomass: 42-242 t/ha; height: 14-32 m) . Krycklan features a boreal forest in northern Sweden, 720-km north-northeast from Remningstorp, with significant topography and where 31 stands have been sampled in 2008 (area: 2.4-26.3 ha; biomass: 23-183 t/ha; height: 7-21 m) . A high-resolution digital terrain model has been used as ground reference during InSAR processing. For the aforementioned plots and stands and if the same acquisition is used for model training and validation, the new model explains 65%-89% of the observed variance, with root-mean-square error (RMSE) of 12%-19% (median: 15%) . By fixing two of the three model parameters, accurate biomass estimation can also be done when different acquisitions or different test sites are used for model training and validation, with RMSE of 12%-56% (median: 17%) . Compared with a simple scaling model computing biomass from the phase center elevation above ground, the proposed model shows significantly better performance in Remningstorp, as it accounts for the large canopy density variations caused by active management. In Krycklan, the two models show similar performance.

    @Article{sojaPerssonUlanderTGRS2015BiomassTandemX,
    author = {Soja, Maciej J. and Persson, H.J. and Ulander, Lars M.H.},
    title = {Estimation of Forest Biomass From Two-Level Model Inversion of Single-Pass {InSAR} Data},
    journal = {IEEE Trans. Geosci. Remote Sens.},
    year = {2015},
    volume = {53},
    number = {9},
    pages = {5083-5099},
    month = sep,
    issn = {0196-2892},
    abstract = {A model for aboveground biomass estimation from single-pass interferometric synthetic aperture radar (InSAR) data is presented. Forest height and canopy density estimates dh and n0, respectively, obtained from two-level model (TLM) inversion, are used as biomass predictors. Eighteen bistatic VV-polarized TanDEM-X (TDM) acquisitions are used, made over two Swedish test sites in the summers of 2011, 2012, and 2013 (nominal incidence angle: 41 deg, height-of-ambiguity: 32-63 m) . Remningstorp features a hemiboreal forest in southern Sweden, with flat topography and where 32 circular plots have been sampled between 2010 and 2011 (area: 0.5 ha; biomass: 42-242 t/ha; height: 14-32 m) . Krycklan features a boreal forest in northern Sweden, 720-km north-northeast from Remningstorp, with significant topography and where 31 stands have been sampled in 2008 (area: 2.4-26.3 ha; biomass: 23-183 t/ha; height: 7-21 m) . A high-resolution digital terrain model has been used as ground reference during InSAR processing. For the aforementioned plots and stands and if the same acquisition is used for model training and validation, the new model explains 65%-89% of the observed variance, with root-mean-square error (RMSE) of 12%-19% (median: 15%) . By fixing two of the three model parameters, accurate biomass estimation can also be done when different acquisitions or different test sites are used for model training and validation, with RMSE of 12%-56% (median: 17%) . Compared with a simple scaling model computing biomass from the phase center elevation above ground, the proposed model shows significantly better performance in Remningstorp, as it accounts for the large canopy density variations caused by active management. In Krycklan, the two models show similar performance.},
    doi = {10.1109/TGRS.2015.2417205},
    file = {:sojaPerssonUlanderTGRS2015BiomassTandemX.pdf:PDF},
    keywords = {data acquisition;digital elevation models;forestry;radar interferometry;remote sensing by radar;synthetic aperture radar;vegetation;AD 2008;AD 2010;AD 2011;AD 2012;AD 2013;InSAR processing;Krycklan feature;Remningstorp feature;Swedish test site;VV-polarized TanDEM-X acquisition;aboveground biomass estimation;biomass predictor;canopy density;digital terrain model;forest biomass estimation;forest height;hemiboreal forest;northern Sweden;single-pass InSAR data;single-pass interferometric synthetic aperture radar data;southern Sweden;two-level model inversion;Biological system modeling;Biomass;Computational modeling;Correlation;Decorrelation;Estimation;Synthetic aperture radar;Aboveground biomass (AGB);TanDEM-X (TDM);canopy density;forest height;interferometric model;interferometric syntheticaperture radar (InSAR);two-level model (TLM)},
    owner = {ofrey},
    pdf = {../../../docs/sojaPerssonUlanderTGRS2015BiomassTandemX.pdf},
    
    }
    


  45. Maciej J. Soja, H. Persson, and Lars M. H. Ulander. Estimation of Forest Height and Canopy Density From a Single InSAR Correlation Coefficient. IEEE Geosci. Remote Sens. Lett., 12(3):646-650, March 2015. Keyword(s): digital elevation models, geophysical image processing, parameter estimation, radar interferometry, remote sensing by radar, synthetic aperture radar, vegetation mapping, AD 2011 to 2013, VV-polarized bistatic-interferometric TanDEM-X image pairs, canopy density, forest height estimation, hemiboreal test site Remningstorp, high-resolution digital terrain model, single InSAR correlation coefficient, southern Sweden, synthetic aperture radar, two-level model, vegetation, Backscatter, Coherence, Laser radar, Remote sensing, Synthetic aperture radar, Time division multiplexing, Vegetation, Canopy density, TanDEM-X, forest height, interferometric model, interferometry, synthetic aperture radar (SAR), two-level model (TLM).
    Abstract: A two-level model (TLM) is introduced and investigated for the estimation of forest height and canopy density from a single ground-corrected InSAR complex correlation coefficient. The TLM models forest as two scattering levels, namely, ground and vegetation, separated by a distance dh and with area-weighted backscatter ratio mu. The model is evaluated using eight VV-polarized bistatic-interferometric TanDEM-X image pairs acquired in the summers of 2011, 2012, and 2013 over the managed hemi-boreal test site Remningstorp, which is situated in southern Sweden. Ground phase is removed using a highresolution digital terrain model. Inverted TLM parameters for thirty-two 0.5-ha plots of four different types (regular plots, sparse plots, seed trees, and clear-cuts) are studied against reference lidar data. It is concluded that the level distance dh can be used as an estimate of the 50th percentile forest height estimated from lidar (for regular plots: r > 0.95 and root-mean-square difference (sigma) < 10%, or 1.8 m). Moreover, the uncorrected area fill factor n0 = 1/(1 + mu) can be used as an estimate of the vegetation ratio, which is a canopy density estimate defined as the fraction of lidar returns coming from the canopy to all lidar returns (for regular plots: r > 0.59 and sigma = 10%, or 0.07).

    @Article{sojaPerssonUlanderGRSL2015ForestHeightTandemX,
    author = {Soja, Maciej J. and Persson, H. and Ulander, Lars M. H.},
    title = {Estimation of Forest Height and Canopy Density From a Single {InSAR} Correlation Coefficient},
    journal = {IEEE Geosci. Remote Sens. Lett.},
    year = {2015},
    volume = {12},
    number = {3},
    pages = {646-650},
    month = mar,
    issn = {1545-598X},
    abstract = {A two-level model (TLM) is introduced and investigated for the estimation of forest height and canopy density from a single ground-corrected InSAR complex correlation coefficient. The TLM models forest as two scattering levels, namely, ground and vegetation, separated by a distance dh and with area-weighted backscatter ratio mu. The model is evaluated using eight VV-polarized bistatic-interferometric TanDEM-X image pairs acquired in the summers of 2011, 2012, and 2013 over the managed hemi-boreal test site Remningstorp, which is situated in southern Sweden. Ground phase is removed using a highresolution digital terrain model. Inverted TLM parameters for thirty-two 0.5-ha plots of four different types (regular plots, sparse plots, seed trees, and clear-cuts) are studied against reference lidar data. It is concluded that the level distance dh can be used as an estimate of the 50th percentile forest height estimated from lidar (for regular plots: r > 0.95 and root-mean-square difference (sigma) < 10%, or 1.8 m). Moreover, the uncorrected area fill factor n0 = 1/(1 + mu) can be used as an estimate of the vegetation ratio, which is a canopy density estimate defined as the fraction of lidar returns coming from the canopy to all lidar returns (for regular plots: r > 0.59 and sigma = 10%, or 0.07).},
    doi = {10.1109/LGRS.2014.2354551},
    file = {:sojaPerssonUlanderGRSL2015ForestHeightTandemX.pdf:PDF},
    keywords = {digital elevation models;geophysical image processing;parameter estimation;radar interferometry;remote sensing by radar;synthetic aperture radar;vegetation mapping;AD 2011 to 2013;VV-polarized bistatic-interferometric TanDEM-X image pairs;canopy density;forest height estimation;hemiboreal test site Remningstorp;high-resolution digital terrain model;single InSAR correlation coefficient;southern Sweden;synthetic aperture radar;two-level model;vegetation;Backscatter;Coherence;Laser radar;Remote sensing;Synthetic aperture radar;Time division multiplexing;Vegetation;Canopy density;TanDEM-X;forest height;interferometric model;interferometry;synthetic aperture radar (SAR);two-level model (TLM)},
    owner = {ofrey},
    pdf = {../../../docs/sojaPerssonUlanderGRSL2015ForestHeightTandemX.pdf},
    
    }
    


  46. Alireza Tabatabaeenejad, Mariko S. Burgin, X. Duan, and Mahta Moghaddam. P-Band Radar Retrieval of Subsurface Soil Moisture Profile as a Second-Order Polynomial: First AirMOSS Results. IEEE Transactions on Geoscience and Remote Sensing, 53(2):645-658, February 2015. Keyword(s): hydrological techniques, remote sensing by radar, vegetation, AD 2012 09, AD 2012 10, AirMOSS mission flights, AirMOSS results, Airborne Microwave Observatory of Sub- canopy and Subsurface, Arizona, P-band radar data, Root Mean Squared Error, Walnut Gulch Experimental Watershed, barren terrain, discrete scattering model, radar pixel, second-order polynomial, shrubland terrain, subsurface depth function, subsurface soil moisture profile, synthetic radar data, terrain radar backscattering coefficients, vegetated terrain, Atmospheric modeling, Data models, Moisture, Polynomials, Radar, Soil moisture, Airborne Microwave Observatory of Subcanopy and Subsurface (AirMOSS), discrete scattering model, quadratic function, radar, remote sensing, second-order polynomial, simulated annealing, soil moisture profile.
    Abstract: We propose a new model for estimating subsurface soil moisture using P-band radar data over barren, shrubland, and vegetated terrains. The unknown soil moisture profile is assumed to have a second-order polynomial form as a function of subsurface depth with three unknown coefficients that we estimate using the simulated annealing algorithm. These retrieved coefficients produce the value of soil moisture at any given depth up to a prescribed depth of validity. We use a discrete scattering model to calculate the radar backscattering coefficients of the terrain. The retrieval method is tested and developed with synthetic radar data and is validated with measured radar data and in situ soil moisture measurements. Both forward and inverse models are briefly explained. The radar data used in this paper have been collected during the Airborne Microwave Observatory of Subcanopy and Subsurface (AirMOSS) mission flights in September and October of 2012 over a 100 km by 25 km area in Arizona, including the Walnut Gulch Experimental Watershed. The study area and the ancillary data layers used to characterize each radar pixel are explained. The inversion results are presented, and it is shown that the RMSE between the retrieved and measured soil moisture profiles ranges from 0.060 to 0.099 m3/m3, with a Root Mean Squared Error (RMSE) of 0.075 m3/m3 over all sites and all acquisition dates. We show that the accuracy of retrievals decreases as depth increases. The profiles used in validation are from a fairy dry season in Walnut Gulch and so are the accuracy conclusions.

    @Article{tabatabaeenejadBurginDuanMoghaddamTGRS2015PBandSoilMoistureAIRMOSS,
    author = {Alireza Tabatabaeenejad and Mariko S. Burgin and X. Duan and Mahta Moghaddam},
    title = {{P}-Band Radar Retrieval of Subsurface Soil Moisture Profile as a Second-Order Polynomial: First {AirMOSS} Results},
    journal = {IEEE Transactions on Geoscience and Remote Sensing},
    year = {2015},
    volume = {53},
    number = {2},
    pages = {645-658},
    month = feb,
    issn = {0196-2892},
    abstract = {We propose a new model for estimating subsurface soil moisture using P-band radar data over barren, shrubland, and vegetated terrains. The unknown soil moisture profile is assumed to have a second-order polynomial form as a function of subsurface depth with three unknown coefficients that we estimate using the simulated annealing algorithm. These retrieved coefficients produce the value of soil moisture at any given depth up to a prescribed depth of validity. We use a discrete scattering model to calculate the radar backscattering coefficients of the terrain. The retrieval method is tested and developed with synthetic radar data and is validated with measured radar data and in situ soil moisture measurements. Both forward and inverse models are briefly explained. The radar data used in this paper have been collected during the Airborne Microwave Observatory of Subcanopy and Subsurface (AirMOSS) mission flights in September and October of 2012 over a 100 km by 25 km area in Arizona, including the Walnut Gulch Experimental Watershed. The study area and the ancillary data layers used to characterize each radar pixel are explained. The inversion results are presented, and it is shown that the RMSE between the retrieved and measured soil moisture profiles ranges from 0.060 to 0.099 m3/m3, with a Root Mean Squared Error (RMSE) of 0.075 m3/m3 over all sites and all acquisition dates. We show that the accuracy of retrievals decreases as depth increases. The profiles used in validation are from a fairy dry season in Walnut Gulch and so are the accuracy conclusions.},
    doi = {10.1109/TGRS.2014.2326839},
    file = {:tabatabaeenejadBurginDuanMoghaddamTGRS2015PBandSoilMoistureAIRMOSS.pdf:PDF},
    keywords = {hydrological techniques;remote sensing by radar;vegetation;AD 2012 09;AD 2012 10;AirMOSS mission flights;AirMOSS results;Airborne Microwave Observatory of Sub- canopy and Subsurface;Arizona;P-band radar data;Root Mean Squared Error;Walnut Gulch Experimental Watershed;barren terrain;discrete scattering model;radar pixel;second-order polynomial;shrubland terrain;subsurface depth function;subsurface soil moisture profile;synthetic radar data;terrain radar backscattering coefficients;vegetated terrain;Atmospheric modeling;Data models;Moisture;Polynomials;Radar;Soil moisture;Airborne Microwave Observatory of Subcanopy and Subsurface (AirMOSS);discrete scattering model;quadratic function;radar;remote sensing;second-order polynomial;simulated annealing;soil moisture profile},
    
    }
    


  47. Ekaterina Tymofyeyeva and Yuri Fialko. Mitigation of atmospheric phase delays in InSAR data, with application to the eastern California shear zone. Journal of Geophysical Research: Solid Earth, 120(8):5952-5963, 2015. Note: 2015JB011886. Keyword(s): SAR Processing, Interferometry, SAR interferometry, differential SAR interferometry, DInSAR, Displacement, Surface Displacement, Atmosphere, APS, Transient deformation, Satellite geodesy: results, Satellite geodesy: technical issues, Seismic cycle related deformations, Integrations of techniques, InSAR, time series, atmospheric delays, transient deformation.
    Abstract: We present a method for estimating radar phase delays due to propagation through the troposphere and the ionosphere based on the averaging of redundant interferograms that share a common scene. Estimated atmospheric contributions can then be subtracted from the radar interferograms to improve measurements of surface deformation. Inversions using synthetic data demonstrate that this procedure can considerably reduce scatter in the time series of the line-of-sight displacements. We demonstrate the feasibility of this method by comparing the interferometric synthetic aperture radar (InSAR) time series derived from ERS-1/2 and Envisat data to continuous Global Positioning System data from eastern California. We also present results from several sites in the eastern California shear zone where anomalous deformation has been reported by previous studies, including the Blackwater fault, the Hunter Mountain fault, and the Coso geothermal plant.

    @Article{tymofyeyevaFialkoJGRB2015AtmosphereInSAR,
    author = {Tymofyeyeva, Ekaterina and Fialko, Yuri},
    title = {Mitigation of atmospheric phase delays in InSAR data, with application to the eastern California shear zone},
    journal = {Journal of Geophysical Research: Solid Earth},
    year = {2015},
    volume = {120},
    number = {8},
    pages = {5952--5963},
    issn = {2169-9356},
    note = {2015JB011886},
    abstract = {We present a method for estimating radar phase delays due to propagation through the troposphere and the ionosphere based on the averaging of redundant interferograms that share a common scene. Estimated atmospheric contributions can then be subtracted from the radar interferograms to improve measurements of surface deformation. Inversions using synthetic data demonstrate that this procedure can considerably reduce scatter in the time series of the line-of-sight displacements. We demonstrate the feasibility of this method by comparing the interferometric synthetic aperture radar (InSAR) time series derived from ERS-1/2 and Envisat data to continuous Global Positioning System data from eastern California. We also present results from several sites in the eastern California shear zone where anomalous deformation has been reported by previous studies, including the Blackwater fault, the Hunter Mountain fault, and the Coso geothermal plant.},
    doi = {10.1002/2015JB011886},
    file = {:tymofyeyevaFialkoJGRB2015AtmosphereInSAR.pdf:PDF},
    keywords = {SAR Processing, Interferometry, SAR interferometry, differential SAR interferometry, DInSAR, Displacement, Surface Displacement, Atmosphere, APS, Transient deformation, Satellite geodesy: results, Satellite geodesy: technical issues, Seismic cycle related deformations, Integrations of techniques, InSAR, time series, atmospheric delays, transient deformation},
    pdf = {../../../docs/tymofyeyevaFialkoJGRB2015AtmosphereInSAR.pdf},
    url = {http://dx.doi.org/10.1002/2015JB011886},
    
    }
    


  48. Alberto Villa, Lorenzo Iannini, Davide Giudici, Andrea Monti-Guarnieri, and Stefano Tebaldini. Calibration of SAR Polarimetric Images by Means of a Covariance Matching Approach. IEEE Trans. Geosci. Remote Sens., 53(2):674-686, February 2015. Keyword(s): Faraday effect, calibration, covariance analysis, numerical analysis, optimisation, parameter estimation, radar imaging, radar polarimetry, synthetic aperture radar, Faraday rotation, SAR polarimetric imaging, corner reflector, covariance matching approach, intrinsic ambiguity identification, numerical method, optimization, polarimetric calibration, repeated full polarimetric ALOS PALSAR imaging, retrieved distortion parameter stability, synthetic aperture radar, system polarimetric distortion parameter estimation, Calibration, Eigenvalues and eigenfunctions, Estimation, Faraday effect, Noise, Sensitivity, Thyristors, Covariance matching, Faraday rotation, numerical methods, polarimetric calibration.
    Abstract: In this paper, a numerical method optimizer based on covariance matching is proposed for synthetic aperture radar (SAR) polarimetric calibration. The method makes use of the information provided by a distributed target and a corner reflector in order to jointly estimate the system polarimetric distortion parameters and the Faraday rotation. A preliminary analysis is conducted to show the expected accuracy values and to identify the intrinsic ambiguities of the problem. Results from simulations are shown to assess the accuracy and convergence of the method. Finally, tests have been conducted on stack of repeated full polarimetric ALOS PALSAR images to check the stability of the retrieved distortion parameters in a realistic case.

    @Article{villaIanniniGiudiciMontiGuarnieriTebaldiniTGRS2015PolCalibration,
    author = {Alberto Villa and Lorenzo Iannini and Davide Giudici and Andrea Monti-Guarnieri and Stefano Tebaldini},
    title = {Calibration of {SAR} Polarimetric Images by Means of a Covariance Matching Approach},
    journal = {IEEE Trans. Geosci. Remote Sens.},
    year = {2015},
    volume = {53},
    number = {2},
    pages = {674-686},
    month = feb,
    issn = {0196-2892},
    abstract = {In this paper, a numerical method optimizer based on covariance matching is proposed for synthetic aperture radar (SAR) polarimetric calibration. The method makes use of the information provided by a distributed target and a corner reflector in order to jointly estimate the system polarimetric distortion parameters and the Faraday rotation. A preliminary analysis is conducted to show the expected accuracy values and to identify the intrinsic ambiguities of the problem. Results from simulations are shown to assess the accuracy and convergence of the method. Finally, tests have been conducted on stack of repeated full polarimetric ALOS PALSAR images to check the stability of the retrieved distortion parameters in a realistic case.},
    doi = {10.1109/TGRS.2014.2326955},
    file = {:villaIanniniGiudiciMontiGuarnieriTebaldiniTGRS2015PolCalibration.pdf:PDF},
    keywords = {Faraday effect;calibration;covariance analysis;numerical analysis;optimisation;parameter estimation;radar imaging;radar polarimetry;synthetic aperture radar;Faraday rotation;SAR polarimetric imaging;corner reflector;covariance matching approach;intrinsic ambiguity identification;numerical method;optimization;polarimetric calibration;repeated full polarimetric ALOS PALSAR imaging;retrieved distortion parameter stability;synthetic aperture radar;system polarimetric distortion parameter estimation;Calibration;Eigenvalues and eigenfunctions;Estimation;Faraday effect;Noise;Sensitivity;Thyristors;Covariance matching;Faraday rotation;numerical methods;polarimetric calibration},
    pdf = {../../../docs/villaIanniniGiudiciMontiGuarnieriTebaldiniTGRS2015PolCalibration.pdf},
    
    }
    


  49. Viet Thuy Vu and Mats I. Pettersson. Nyquist Sampling Requirements for Polar Grids in Bistatic Time-Domain Algorithms. IEEE Transactions on Signal Processing, 63(2):457-465, January 2015. Keyword(s): SAR Processing, Time-Domain Back-Projection, TDBP, Fast-Factorized Back-Projection, FFBP, Bistatic SAR, Bistatic Fast-Factorized Back-Projection, BiFFBP, radar signal processing, signal sampling, Nyquist sampling, airborne bistatic system, bistatic CARABAS-II like data, bistatic cases, bistatic time-domain algorithms, general bistatic geometry, polar grids, Geometry, Radar polarimetry, Receivers, Signal processing algorithms, Synthetic aperture radar, Time-domain analysis, Transmitters, Bistatic, Nyquist sampling, SAR, fast backprojection.
    Abstract: The paper presents a derivation of Nyquist sampling requirements for the polar grids in some bistatic time-domain algorithms. The derivation is based on an airborne bistatic system with general bistatic geometry. The Nyquist sampling requirements are shown to be the functions of operating radar frequency, transmitter and receiver subaperture lengths, and bistatic geometry. How to decide the Nyquist sampling requirements for different bistatic geometries and the relationship between the Nyquist sampling requirements in the monostatic and bistatic cases are also addressed in the paper. The derived Nyquist sampling requirements is examined with the bistatic CARABAS-II like data.

    @Article{vuPettersson2015SamplingReqBistaticFFBP,
    author = {Vu, Viet Thuy and Pettersson, Mats I.},
    title = {Nyquist Sampling Requirements for Polar Grids in Bistatic Time-Domain Algorithms},
    journal = {IEEE Transactions on Signal Processing},
    year = {2015},
    volume = {63},
    number = {2},
    pages = {457-465},
    month = jan,
    issn = {1053-587X},
    abstract = {The paper presents a derivation of Nyquist sampling requirements for the polar grids in some bistatic time-domain algorithms. The derivation is based on an airborne bistatic system with general bistatic geometry. The Nyquist sampling requirements are shown to be the functions of operating radar frequency, transmitter and receiver subaperture lengths, and bistatic geometry. How to decide the Nyquist sampling requirements for different bistatic geometries and the relationship between the Nyquist sampling requirements in the monostatic and bistatic cases are also addressed in the paper. The derived Nyquist sampling requirements is examined with the bistatic CARABAS-II like data.},
    doi = {10.1109/TSP.2014.2375157},
    file = {:vuPettersson2015SamplingReqBistaticFFBP.pdf:PDF},
    keywords = {SAR Processing, Time-Domain Back-Projection, TDBP, Fast-Factorized Back-Projection, FFBP, Bistatic SAR, Bistatic Fast-Factorized Back-Projection, BiFFBP, radar signal processing;signal sampling;Nyquist sampling;airborne bistatic system;bistatic CARABAS-II like data;bistatic cases;bistatic time-domain algorithms;general bistatic geometry;polar grids;Geometry;Radar polarimetry;Receivers;Signal processing algorithms;Synthetic aperture radar;Time-domain analysis;Transmitters;Bistatic;Nyquist sampling;SAR;fast backprojection},
    pdf = {../../../docs/vuPettersson2015SamplingReqBistaticFFBP.pdf},
    
    }
    


  50. Ze Yu, Zhou Li, and Shusen Wang. An Imaging Compensation Algorithm for Correcting the Impact of Tropospheric Delay on Spaceborne High-Resolution SAR. IEEE Transactions on Geoscience and Remote Sensing, 53(9):4825-4836, September 2015. Keyword(s): SAR Processing, SAR Focusing, Azimuth Focusing, Autofocus, Motion Compensation, atmospheric electromagnetic wave propagation, delays, geophysical image processing, image filtering, image resolution, radar cross-sections, radar imaging, remote sensing by radar, spaceborne radar, synthetic aperture radar, troposphere, imaging compensation algorithm, tropospheric delay, spaceborne high-resolution SAR, atmospheric refraction, electromagnetic signalpropagation speed, propagation path delay, geometrical straight-line path, spaceborne synthetic aperture radar, imaging filter, rectilinear propagation, residual phase, focusing quality, focusing performance, spaceborne SAR echo model, range delay coefficient, European Geostationary Navigation Overlay Service model, zenith delay, Niell mapping function, looking direction, range compensation, classical imaging, azimuth compensation, Delays, Synthetic aperture radar, Atmospheric modeling, Focusing, Data models, Real-time systems, High-resolution imaging, phase compensation, synthetic aperture radar (SAR), tropospheric delay, High-resolution imaging, phase compensation.
    Abstract: Atmospheric refraction in the troposphere causes the propagation speed of electromagnetic signals to be less than the light speed. This creates a difference between the actual propagation path delay and the distance of the geometrical straight-line path, i.e, a quantity known as the tropospheric delay. As classical imaging algorithms for spaceborne synthetic aperture radar (SAR) do not take the tropospheric delay into account, imaging filters are designed based on the assumption of rectilinear propagation with the light speed. Therefore, a residual phase exists in imaging results, which affects focusing quality under the condition of high resolution. In order to compensate for the impact of tropospheric delay on focusing performance, this paper modifies the spaceborne SAR echo model and then proposes an imaging compensation algorithm. The key to this algorithm is to fit a range delay coefficient based on the European Geostationary Navigation Overlay Service model of zenith delay and Niell mapping function, which projects the zenith delay onto the looking direction. After range compensation, classical imaging, and azimuth compensation, which compose the proposed algorithm, the processed results are well focused.

    @Article{yuLiWangTGRS2015SpaceborneSARFocusingWithTropoDelayCorr,
    author = {Ze Yu and Zhou Li and Shusen Wang},
    title = {An Imaging Compensation Algorithm for Correcting the Impact of Tropospheric Delay on Spaceborne High-Resolution {SAR}},
    journal = {IEEE Transactions on Geoscience and Remote Sensing},
    year = {2015},
    volume = {53},
    number = {9},
    pages = {4825-4836},
    month = sep,
    issn = {0196-2892},
    abstract = {Atmospheric refraction in the troposphere causes the propagation speed of electromagnetic signals to be less than the light speed. This creates a difference between the actual propagation path delay and the distance of the geometrical straight-line path, i.e, a quantity known as the tropospheric delay. As classical imaging algorithms for spaceborne synthetic aperture radar (SAR) do not take the tropospheric delay into account, imaging filters are designed based on the assumption of rectilinear propagation with the light speed. Therefore, a residual phase exists in imaging results, which affects focusing quality under the condition of high resolution. In order to compensate for the impact of tropospheric delay on focusing performance, this paper modifies the spaceborne SAR echo model and then proposes an imaging compensation algorithm. The key to this algorithm is to fit a range delay coefficient based on the European Geostationary Navigation Overlay Service model of zenith delay and Niell mapping function, which projects the zenith delay onto the looking direction. After range compensation, classical imaging, and azimuth compensation, which compose the proposed algorithm, the processed results are well focused.},
    doi = {10.1109/TGRS.2015.2411261},
    file = {:yuLiWangTGRS2015SpaceborneSARFocusingWithTropoDelayCorr.pdf:PDF},
    keywords = {SAR Processing, SAR Focusing, Azimuth Focusing, Autofocus, Motion Compensation, atmospheric electromagnetic wave propagation;delays;geophysical image processing;image filtering;image resolution;radar cross-sections;radar imaging;remote sensing by radar;spaceborne radar;synthetic aperture radar;troposphere;imaging compensation algorithm;tropospheric delay;spaceborne high-resolution SAR;atmospheric refraction;electromagnetic signalpropagation speed;propagation path delay;geometrical straight-line path;spaceborne synthetic aperture radar;imaging filter;rectilinear propagation;residual phase;focusing quality;focusing performance;spaceborne SAR echo model;range delay coefficient;European Geostationary Navigation Overlay Service model;zenith delay;Niell mapping function;looking direction;range compensation;classical imaging;azimuth compensation;Delays;Synthetic aperture radar;Atmospheric modeling;Focusing;Data models;Real-time systems;High-resolution imaging;phase compensation;synthetic aperture radar (SAR);tropospheric delay;High-resolution imaging;phase compensation;synthetic aperture radar (SAR);tropospheric delay},
    owner = {ofrey},
    
    }
    


  51. Evan C. Zaugg and David G. Long. Generalized Frequency Scaling and Backprojection for LFM-CW SAR Processing. IEEE Trans. Geosci. Remote Sens., 53(7):3600-3614, July 2015. Keyword(s): SAR Processing, Time-Domain Back-Projection, TDBP, Back-Projection, Fast-Factorized Back-Projection, FFBP, GPU, SAR focusing, Azimuth Focusing, GPU, GPU-based parallelized TDBP, graphics processing units, LFM-CW, FMCW, Airborne SAR, Approximation algorithms, Approximation methods, Bandwidth, Chirp, Doppler effect, Synthetic aperture radar, Radar imaging, synthetic aperture radar (SAR).
    Abstract: This paper presents a generalized treatment of image formation for a linear-frequency-modulated continuous wave (LFM-CW) synthetic aperture radar (SAR) signal, which is a key technology in making very small SAR systems viable. The signal model is derived, which includes the continuous platform motion. The effect of this motion on the SAR signal is discussed, and an efficient compensation method is developed. Processing algorithms are developed including precise and approximate backprojection methods and a generalized frequency scaling algorithm that accounts for an arbitrary number of terms of a Taylor expansion approximation of the SAR signal in the Doppler frequency domain. Together, these algorithms allow for the processing of LFM-CW SAR data for a wide variety of system parameters, even in scenarios where traditional algorithms and signal approximations break down.

    @Article{zauggLongTGRS2015Backprojection,
    author = {Zaugg, Evan C. and Long, David G.},
    title = {Generalized Frequency Scaling and Backprojection for {LFM-CW} {SAR} Processing},
    journal = {IEEE Trans. Geosci. Remote Sens.},
    year = {2015},
    volume = {53},
    number = {7},
    pages = {3600-3614},
    month = jul,
    issn = {0196-2892},
    abstract = {This paper presents a generalized treatment of image formation for a linear-frequency-modulated continuous wave (LFM-CW) synthetic aperture radar (SAR) signal, which is a key technology in making very small SAR systems viable. The signal model is derived, which includes the continuous platform motion. The effect of this motion on the SAR signal is discussed, and an efficient compensation method is developed. Processing algorithms are developed including precise and approximate backprojection methods and a generalized frequency scaling algorithm that accounts for an arbitrary number of terms of a Taylor expansion approximation of the SAR signal in the Doppler frequency domain. Together, these algorithms allow for the processing of LFM-CW SAR data for a wide variety of system parameters, even in scenarios where traditional algorithms and signal approximations break down.},
    doi = {10.1109/TGRS.2014.2380154},
    file = {:zauggLongTGRS2015Backprojection.pdf:PDF},
    keywords = {SAR Processing, Time-Domain Back-Projection, TDBP, Back-Projection, Fast-Factorized Back-Projection, FFBP, GPU, SAR focusing, Azimuth Focusing, GPU, GPU-based parallelized TDBP, graphics processing units, LFM-CW, FMCW, Airborne SAR, Approximation algorithms;Approximation methods;Bandwidth;Chirp;Doppler effect;Synthetic aperture radar;Radar imaging;synthetic aperture radar (SAR)},
    pdf = {../../../docs/zauggLongTGRS2015Backprojection.pdf},
    
    }
    


Conference articles

  1. W. M. Boerner, G. Krieger, A. Reigber, I. Hajnsek, C. C. Schmullius, A. Moreira, M. Eineder, R. Bamler, F. J. Meyer, S. Hensley, J. J. van Zyl, M. Neumann, M. Shimada, M. Ohki, J. T. S. Sumantyo, K. Hattori, F. J. Ocampo-Torres, O. Ponce, J. Moreira, J. Campos, L. Yi-Long, P. Dubois-Fernandez, E. Pottier, T. LeToan, C. Surussavadee, V. C. Koo, T. S. Lim, R. H. Triharjanto, W. Hasbi, S. Mohan, and G. Singh. Development of new multi-band equatorially orbiting POLinSAR satellite sensors system configurations for varying latitudinal coverage within total tropical belt: Invited group presentation for establishing an associated Consortium. In Proc. IEEE 5th Asia-Pacific Conf. Synthetic Aperture Radar (APSAR), pages 342-345, September 2015. Keyword(s): meteorological radar, radar interferometry, radar polarimetry, remote sensing by radar, energy resources, global weather phenomena, latitudinal coverage, local environmental deterioration, mineral extraction, multiband equatorially orbiting POLINSAR satellite sensors, polarimetric POLINSAR satellite, stable food base, total tropical belt, Belts, Hazards, Orbits, Remote sensing, Satellites, Sensors, Synthetic aperture radar, Disaster assessment and reduction, Environmental remote sensing, Equatorial orbiting satellite sensors, Geophysical monitoring, Natural and manmade hazard detection, Polarimetric Synthetic Aperture Radar (SAR), Polarization radar, Surveillance, Tropical Equatorial Belt (TEB).
    @InProceedings{Boerner2015,
    author = {W. M. Boerner and G. Krieger and A. Reigber and I. Hajnsek and C. C. Schmullius and A. Moreira and M. Eineder and R. Bamler and F. J. Meyer and S. Hensley and J. J. van Zyl and M. Neumann and M. Shimada and M. Ohki and J. T. S. Sumantyo and K. Hattori and F. J. Ocampo-Torres and O. Ponce and J. Moreira and J. Campos and L. Yi-Long and P. Dubois-Fernandez and E. Pottier and T. LeToan and C. Surussavadee and V. C. Koo and T. S. Lim and R. H. Triharjanto and W. Hasbi and S. Mohan and G. Singh},
    title = {Development of new multi-band equatorially orbiting POLinSAR satellite sensors system configurations for varying latitudinal coverage within total tropical belt: Invited group presentation for establishing an associated Consortium},
    booktitle = {Proc. IEEE 5th Asia-Pacific Conf. Synthetic Aperture Radar (APSAR)},
    year = {2015},
    month = sep,
    pages = {342--345},
    doi = {10.1109/APSAR.2015.7306222},
    keywords = {meteorological radar, radar interferometry, radar polarimetry, remote sensing by radar, energy resources, global weather phenomena, latitudinal coverage, local environmental deterioration, mineral extraction, multiband equatorially orbiting POLINSAR satellite sensors, polarimetric POLINSAR satellite, stable food base, total tropical belt, Belts, Hazards, Orbits, Remote sensing, Satellites, Sensors, Synthetic aperture radar, Disaster assessment and reduction, Environmental remote sensing, Equatorial orbiting satellite sensors, Geophysical monitoring, Natural and manmade hazard detection, Polarimetric Synthetic Aperture Radar (SAR), Polarization radar, Surveillance, Tropical Equatorial Belt (TEB)},
    owner = {ofrey},
    
    }
    


  2. T. J. Czernuszewicz, J. W. Homeister, M. C. Caughey, M. A. Farber, J. J. Fulton, P. F. Ford, W. A. Marston, R. Vallabhaneni, T. C. Nichols, and C. M. Gallippi. In vivo carotid plaque stiffness measurements with ARFI ultrasound in endarterectomy patients. In Proc. IEEE Int. Ultrasonics Symp. (IUS), pages 1-4, October 2015. Keyword(s): biological tissues, biomechanics, biomedical ultrasonics, diseases, ultrasonic imaging, ARFI ultrasound, acoustic radiation force impulse ultrasound, atherosclerotic plaque, calcification, carotid endarterectomy, carotid plaque stiffness measurements, elasticity imaging technique, endarterectomy patients, fibrosis, fibrotic-calcified areas, fibrous cap, hemorrhage, lipid-necrotic areas, necrotic core, Atherosclerosis, Biomedical imaging, Computed tomography, Hemorrhaging, Thickness measurement, Ultrasonic imaging, ARFI, CEA, acoustic radiation force, atherosclerosis, carotid endarterectomy, plaque characterization, stroke.
    @InProceedings{Czernuszewicz2015,
    author = {T. J. Czernuszewicz and J. W. Homeister and M. C. Caughey and M. A. Farber and J. J. Fulton and P. F. Ford and W. A. Marston and R. Vallabhaneni and T. C. Nichols and C. M. Gallippi},
    title = {In vivo carotid plaque stiffness measurements with ARFI ultrasound in endarterectomy patients},
    booktitle = {Proc. IEEE Int. Ultrasonics Symp. (IUS)},
    year = {2015},
    month = oct,
    pages = {1--4},
    doi = {10.1109/ULTSYM.2015.0004},
    keywords = {biological tissues, biomechanics, biomedical ultrasonics, diseases, ultrasonic imaging, ARFI ultrasound, acoustic radiation force impulse ultrasound, atherosclerotic plaque, calcification, carotid endarterectomy, carotid plaque stiffness measurements, elasticity imaging technique, endarterectomy patients, fibrosis, fibrotic-calcified areas, fibrous cap, hemorrhage, lipid-necrotic areas, necrotic core, Atherosclerosis, Biomedical imaging, Computed tomography, Hemorrhaging, Thickness measurement, Ultrasonic imaging, ARFI, CEA, acoustic radiation force, atherosclerosis, carotid endarterectomy, plaque characterization, stroke},
    owner = {ofrey},
    
    }
    


  3. Othmar Frey, Charles L. Werner, Martin Schneebeli, Amy Macfarlane, and Andreas Wiesmann. Enhancement of SnowScat for tomographic observation capabilities. In Proc. FRINGE 2015, ESA SP-731, March 2015. Keyword(s): SAR Processing, SAR Tomography, Snow, Snowpack, X-band, Ku-band, SnowScat, ESA, European Space Agency.
    Abstract: The SnowScat device, a tower-mounted fully polarimetric scatterometer for measurements of the radar cross-section of snow at X-band up to Ku-band, has recently been enhanced to also support a tomographic profiling mode. The new tomographic profiling capability of SnowScat allows for performing high-resolution observations providing further insights into the complex electromagnetic interaction within snowpacks. In this paper, we present first results obtained from a series of tomographic profiles of a snowpack acquired with the enhanced SnowScat device at a test site of SLF in Davos, Switzerland, between Dec. 2014 and March 2015.

    @InProceedings{freyWernerSchneebeliMacfarlaneWiesmannFRINGE2015SnowScatTomo,
    author = {Othmar Frey and Charles L. Werner and Martin Schneebeli and Amy Macfarlane and Andreas Wiesmann},
    title = {Enhancement of {SnowScat} for tomographic observation capabilities},
    booktitle = {Proc. FRINGE 2015},
    year = {2015},
    series = {ESA SP-731},
    month = mar,
    abstract = {The SnowScat device, a tower-mounted fully polarimetric scatterometer for measurements of the radar cross-section of snow at X-band up to Ku-band, has recently been enhanced to also support a tomographic profiling mode. The new tomographic profiling capability of SnowScat allows for performing high-resolution observations providing further insights into the complex electromagnetic interaction within snowpacks. In this paper, we present first results obtained from a series of tomographic profiles of a snowpack acquired with the enhanced SnowScat device at a test site of SLF in Davos, Switzerland, between Dec. 2014 and March 2015.},
    file = {:freyWernerSchneebeliMacfarlaneWiesmannFRINGE2015SnowScatTomo.pdf:PDF},
    keywords = {SAR Processing, SAR Tomography, Snow, Snowpack, X-band, Ku-band, SnowScat, ESA, European Space Agency},
    pdf = {http://www.ifu-sar.ethz.ch/otfrey/SARbibliography/myPapers/freyWernerSchneebeliMacfarlaneWiesmannFRINGE2015SnowScatTomo.pdf},
    url = {http://proceedings.esa.int/files/37.pdf},
    
    }
    


  4. Othmar Frey, Charles L. Werner, and Andreas Wiesmann. SnowScat tomography: first experimental results. In Proc. IEEE Int. Geosci. Remote Sens. Symp., volume 1, pages 1-4, July 2015. Note: Abstract.Keyword(s): SAR Processing, SAR Tomography, Tomographic profiling, SnowScat, ESA, European Space Agency, X-Band, Ku-Band, Polarimetry, ground-based radar, Snow, Snowpack, geophysical signal processing, radar polarimetry, synthetic aperture radar.
    Abstract: The SnowScat device is a fully-polarimetric scatterometer that has originally been designed to measure the radar cross-section of snow at a frequency range from 9.2 to 17.8 GHz (X-band to Ku-band). Recently, a modification of the measurement setup was implemented an tested that extends the capabilities of the SnowScat device towards tomographic profiling of snowpacks. This extension aims at enhancing the SnowScat device in order to better respond to the ESAC recommendations which were made on the deselected CoReH2O candidate following the User Consultation meeting in March 2013 for the 7 Earth Explorer mission. Such new capability allows for performing high-resolution tomographic profiling observations providing further insights into the complex electromagnetic interaction within snowpacks. In this contribution, we (1) describe the tomographic mode of the SnowScat device including the experimental setup at the test site in Davos, Switzerland, as well as the tomographic processing approach. (2) First results are presented that validate the tomographic measurement concept with the help of a tomographic test target.

    @InProceedings{freyWernerWiesmannIGARSS2015SnowScatTomo,
    Title = {SnowScat tomography: first experimental results},
    Author = {Othmar Frey and Charles L. Werner and Andreas Wiesmann},
    Booktitle = {Proc. IEEE Int. Geosci. Remote Sens. Symp.},
    Month = jul,
    Note = {Abstract.},
    Pages = {1-4},
    Volume = {1},
    Year = {2015},
    Abstract = {The SnowScat device is a fully-polarimetric scatterometer that has originally been designed to measure the radar cross-section of snow at a frequency range from 9.2 to 17.8 GHz (X-band to Ku-band). Recently, a modification of the measurement setup was implemented an tested that extends the capabilities of the SnowScat device towards tomographic profiling of snowpacks. This extension aims at enhancing the SnowScat device in order to better respond to the ESAC recommendations which were made on the deselected CoReH2O candidate following the User Consultation meeting in March 2013 for the 7 Earth Explorer mission. Such new capability allows for performing high-resolution tomographic profiling observations providing further insights into the complex electromagnetic interaction within snowpacks. In this contribution, we (1) describe the tomographic mode of the SnowScat device including the experimental setup at the test site in Davos, Switzerland, as well as the tomographic processing approach. (2) First results are presented that validate the tomographic measurement concept with the help of a tomographic test target.},
    Keywords = {SAR Processing, SAR Tomography, Tomographic profiling, SnowScat, ESA, European Space Agency, X-Band, Ku-Band,Polarimetry, ground-based radar; Snow,Snowpack, geophysical signal processing;radar polarimetry;synthetic aperture radar} 
    }
    


  5. Othmar Frey, Charles L. Werner, and Andreas Wiesmann. Tomographic Profiling of the Structure of a Snow Pack at X-/Ku-Band Using SnowScat in SAR Mode. In Proc. EuRAD 2015 - 12th European Radar Conference, pages 21-24, September 2015. Keyword(s): SAR Processing, SAR Tomography, Tomographic profiling, SnowScat, ESA, European Space Agency, X-Band, Ku-Band, Polarimetry, ground-based radar, Snow, Snowpack, geophysical signal processing, radar polarimetry, synthetic aperture radar.
    Abstract: The SnowScat device, a fully-polarimetric scatterometer originally designed to measure the radar cross-section of snow at a frequency range from 9.2 to 17.8 GHz (X-band to Ku-band), has recently been extended towards a high-resolution tomographic measurement mode. Such tomographic profiling observations provide further insights into the complex electromagnetic interaction within snowpacks, e.g., by revealing different layers, such as melt-freeze crusts, inside the snowpack. In this contribution, we report first results from an initial tomographic measurement campaign carried out at a test site in Davos, Switzerland, in winter 2014/2015.

    @InProceedings{freyWernerWiesmannEURAD2015SnowScatTomo,
    author = {Othmar Frey and Charles L. Werner and Andreas Wiesmann},
    title = {Tomographic Profiling of the Structure of a Snow Pack at {X-/}{Ku}-Band Using {SnowScat} in {SAR} Mode},
    booktitle = {Proc. EuRAD 2015 - 12th European Radar Conference},
    year = {2015},
    pages = {21-24},
    month = sep,
    abstract = {The SnowScat device, a fully-polarimetric scatterometer originally designed to measure the radar cross-section of snow at a frequency range from 9.2 to 17.8 GHz (X-band to Ku-band), has recently been extended towards a high-resolution tomographic measurement mode. Such tomographic profiling observations provide further insights into the complex electromagnetic interaction within snowpacks, e.g., by revealing different layers, such as melt-freeze crusts, inside the snowpack. In this contribution, we report first results from an initial tomographic measurement campaign carried out at a test site in Davos, Switzerland, in winter 2014/2015.},
    doi = {10.1109/EuRAD.2015.7346227},
    file = {:freyWernerWiesmannEURAD2015SnowScatTomo.pdf:PDF},
    keywords = {SAR Processing, SAR Tomography, Tomographic profiling, SnowScat, ESA, European Space Agency, X-Band, Ku-Band,Polarimetry, ground-based radar; Snow,Snowpack, geophysical signal processing;radar polarimetry;synthetic aperture radar},
    pdf = {http://www.ifu-sar.ethz.ch/otfrey/SARbibliography/myPapers/freyWernerWiesmannEURAD2015SnowScatTomo.pdf},
    url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7346227},
    
    }
    


  6. M. T. Ghasr, K. P. Ying, and R. Zoughi. Wideband millimeter wave interferometer for high-resolution 3D SAR imaging. In 2015 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Proceedings, pages 925-929, May 2015. Keyword(s): SAR Processing, W-Band, holographic interferometry, image resolution, millimetre wave imaging, millimetre wave radar, radar imaging, radar interferometry, radar resolution, reflectometers, synthetic aperture radar, high-resolution 3D SAR imaging, nondestructive testing, phase referencing, portable millimeter wave imaging system, synthetic aperture radar image resolution, three-dimensional millimeter wave holographic image production, wideband millimeter wave interferometer, Apertures, Imaging, Millimeter wave technology, Ports (Computers), Rubber, Three-dimensional displays, Wideband, high-resolution, holographical images, millimeter wave imaging, synthetic aperture radar, wideband interferometer.
    Abstract: Portable millimeter wave imaging systems are desired in many nondestructive testing and imaging applications. Interferometry-based instruments have shown to produce three-dimensional holographic images when proper phase referencing is implemented. This paper introduces the design of an interferometry-based wideband, and low-cost reflectometer capable of producing holographic three-dimensional millimeter wave images. Analysis of sources of image errors, and three-dimensional synthetic aperture radar (SAR) image examples are presented at Ka-band (26.5-40 GHz), V-band (50-75 GHz) and W-band (75-110 GHz).

    @INPROCEEDINGS{ghasrYingZoughi2015WBandfor3DSARImaging,
    author={M. T. Ghasr and K. P. Ying and R. Zoughi},
    booktitle={2015 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Proceedings},
    title={Wideband millimeter wave interferometer for high-resolution 3D SAR imaging},
    year={2015},
    volume={},
    number={},
    pages={925-929},
    abstract={Portable millimeter wave imaging systems are desired in many nondestructive testing and imaging applications. Interferometry-based instruments have shown to produce three-dimensional holographic images when proper phase referencing is implemented. This paper introduces the design of an interferometry-based wideband, and low-cost reflectometer capable of producing holographic three-dimensional millimeter wave images. Analysis of sources of image errors, and three-dimensional synthetic aperture radar (SAR) image examples are presented at Ka-band (26.5-40 GHz), V-band (50-75 GHz) and W-band (75-110 GHz).},
    keywords={SAR Processing, W-Band,holographic interferometry;image resolution;millimetre wave imaging;millimetre wave radar;radar imaging;radar interferometry;radar resolution;reflectometers;synthetic aperture radar;high-resolution 3D SAR imaging;nondestructive testing;phase referencing;portable millimeter wave imaging system;synthetic aperture radar image resolution;three-dimensional millimeter wave holographic image production;wideband millimeter wave interferometer;Apertures;Imaging;Millimeter wave technology;Ports (Computers);Rubber;Three-dimensional displays;Wideband;high-resolution;holographical images;millimeter wave imaging;synthetic aperture radar;wideband interferometer},
    doi={10.1109/I2MTC.2015.7151393},
    ISSN={1091-5281},
    month=may,
    owner = {ofrey},
    
    }
    


  7. G. Gomba, X. Y. Cong, and M. Eineder. Correction of ionospheric and tropospheric path delay for L-band interferograms. In Proc. IEEE Int. Geoscience and Remote Sensing Symp. (IGARSS), pages 310-313, July 2015. Keyword(s): SAR Processing, split-spectrum, split-spectrum interferometry, split-band, split-band interferometry, ionospheric electromagnetic wave propagation, ionospheric techniques, refractive index, remote sensing by radar, synthetic aperture radar, tropospheric electromagnetic wave propagation, weather forecasting, L-band interferograms, SAR data, differential atmospheric path delay, direct integration method, error source, geophysical processes, ground deformation signal, height-dependent tropospheric effects, ionospheric path delay correction, nominal value, numerical weather prediction data, radio wave delay, radio wave propagation, refractivity index variation, slant range distance, split-spectrum method, stratified delay, topography signal, tropospheric path delay correction, Atmospheric measurements, Delays, Dispersion, Ionosphere, L-band, Synthetic aperture radar, InSAR, SAR ionospheric effects, ionosphere estimation.
    @InProceedings{gombaCongEineder2015IonoSplitSpectrumInSAR,
    author = {G. Gomba and X. Y. Cong and M. Eineder},
    title = {Correction of ionospheric and tropospheric path delay for L-band interferograms},
    booktitle = {Proc. IEEE Int. Geoscience and Remote Sensing Symp. (IGARSS)},
    year = {2015},
    pages = {310--313},
    month = jul,
    doi = {10.1109/IGARSS.2015.7325762},
    issn = {2153-6996},
    keywords = {SAR Processing, split-spectrum, split-spectrum interferometry, split-band, split-band interferometry,ionospheric electromagnetic wave propagation, ionospheric techniques, refractive index, remote sensing by radar, synthetic aperture radar, tropospheric electromagnetic wave propagation, weather forecasting, L-band interferograms, SAR data, differential atmospheric path delay, direct integration method, error source, geophysical processes, ground deformation signal, height-dependent tropospheric effects, ionospheric path delay correction, nominal value, numerical weather prediction data, radio wave delay, radio wave propagation, refractivity index variation, slant range distance, split-spectrum method, stratified delay, topography signal, tropospheric path delay correction, Atmospheric measurements, Delays, Dispersion, Ionosphere, L-band, Synthetic aperture radar, InSAR, SAR ionospheric effects, ionosphere estimation},
    owner = {ofrey},
    
    }
    


  8. G. Gomba and F. De Zan. Estimation of ionospheric height variations during an aurora event using multiple semi-focusing levels. In Proc. IEEE Int. Geoscience and Remote Sensing Symp. (IGARSS), pages 4065-4068, July 2015. Keyword(s): SAR Processing, split-spectrum, split-spectrum interferometry, split-band, split-band interferometry, aurora, ionospheric electromagnetic wave propagation, ionospheric techniques, remote sensing by radar, synthetic aperture radar, SAR images, SAR interferograms, aurora event, integrated-azimuth-shifts method, ionosphere scintillation, ionosphere vertical profile, ionospheric effects, ionospheric height variation estimation, ionospheric phase screen, multiple semifocusing levels, normal ionospheric state, Azimuth, Estimation, Hafnium, Ionosphere, Satellites, InSAR, SAR ionospheric effects, ionosphere estimation, ionosphere scintillation.
    @InProceedings{Gomba2015a,
    author = {G. Gomba and F. De Zan},
    title = {Estimation of ionospheric height variations during an aurora event using multiple semi-focusing levels},
    booktitle = {Proc. IEEE Int. Geoscience and Remote Sensing Symp. (IGARSS)},
    year = {2015},
    pages = {4065--4068},
    month = jul,
    doi = {10.1109/IGARSS.2015.7326718},
    issn = {2153-6996},
    keywords = {SAR Processing, split-spectrum, split-spectrum interferometry, split-band, split-band interferometry,aurora, ionospheric electromagnetic wave propagation, ionospheric techniques, remote sensing by radar, synthetic aperture radar, SAR images, SAR interferograms, aurora event, integrated-azimuth-shifts method, ionosphere scintillation, ionosphere vertical profile, ionospheric effects, ionospheric height variation estimation, ionospheric phase screen, multiple semifocusing levels, normal ionospheric state, Azimuth, Estimation, Hafnium, Ionosphere, Satellites, InSAR, SAR ionospheric effects, ionosphere estimation, ionosphere scintillation},
    owner = {ofrey},
    
    }
    


  9. Marc Jger, Muriel Pinheiro, Octavio Ponce, Andreas Reigber, and Rolf Scheiber. A Survey of novel airborne SAR signal processing techniques and applications for DLR's F-SAR sensor. In Proc. 16th Int. Radar Symp. (IRS), pages 236-241, June 2015. Keyword(s): airborne radar, image filtering, radar detection, radar imaging, radar interferometry, radar polarimetry, radar resolution, synthetic aperture radar, DLR F-SAR sensor, SAR imaging capability, advanced filtering, airborne SAR signal processing technique, dual-frequency SAR interferometry, high resolution circular SAR imaging, large baseline, polarimetric change detection, precise DEM generation, Covariance matrices, Image resolution, Imaging, Interferometry, Radar polarimetry, Speckle, Synthetic aperture radar.
    @InProceedings{jaegerPinheiroPonceReigberScheiber2015OverviewAirborneSAR,
    author = {Marc J{\"a}ger and Muriel Pinheiro and Octavio Ponce and Andreas Reigber and Rolf Scheiber},
    title = {A Survey of novel airborne {SAR} signal processing techniques and applications for DLR's F-{SAR} sensor},
    booktitle = {Proc. 16th Int. Radar Symp. (IRS)},
    year = {2015},
    month = jun,
    pages = {236--241},
    doi = {10.1109/IRS.2015.7226358},
    issn = {2155-5745},
    keywords = {airborne radar, image filtering, radar detection, radar imaging, radar interferometry, radar polarimetry, radar resolution, synthetic aperture radar, DLR F-SAR sensor, SAR imaging capability, advanced filtering, airborne SAR signal processing technique, dual-frequency SAR interferometry, high resolution circular SAR imaging, large baseline, polarimetric change detection, precise DEM generation, Covariance matrices, Image resolution, Imaging, Interferometry, Radar polarimetry, Speckle, Synthetic aperture radar},
    owner = {ofrey},
    
    }
    


  10. A. Martinez, M. Lort, A. Aguasca, and A. Broquetas. Submillimetric motion detection with a 94 GHZ ground based synthetic aperture radar. In IET International Radar Conference 2015, pages 1-5, October 2015. Keyword(s): SAR Processing, W-Band, CW radar, FM radar, motion compensation, radar imaging, radar interferometry, synthetic aperture radar, CW-FM radar, W band, frequency 94 GHz, ground based synthetic aperture radar, high resolution imaging, radar interferometry, submillimetric motion detection, Band, CW-FM Radar, Ground Based SAR.
    Abstract: The paper presents the validation and experimental assessment of a 94 GHz (W-Band) CW-FM Radar that can be configured as a Ground Based SAR for high resolution imaging and interferometry. Several experimental campaigns have been carried out to assess the capability of the system to remotely observe submillimetric deformation and vibration in infrastructures.

    @INPROCEEDINGS{martinezLortAguascaBroquetasIRC2015WBandDeformation,
    author={A. Martinez and M. Lort and A. Aguasca and A. Broquetas},
    booktitle={IET International Radar Conference 2015},
    title={Submillimetric motion detection with a 94 GHZ ground based synthetic aperture radar},
    year={2015},
    volume={},
    number={},
    pages={1-5},
    abstract={The paper presents the validation and experimental assessment of a 94 GHz (W-Band) CW-FM Radar that can be configured as a Ground Based SAR for high resolution imaging and interferometry. Several experimental campaigns have been carried out to assess the capability of the system to remotely observe submillimetric deformation and vibration in infrastructures.},
    keywords={SAR Processing, W-Band,CW radar;FM radar;motion compensation;radar imaging;radar interferometry;synthetic aperture radar;CW-FM radar;W band;frequency 94 GHz;ground based synthetic aperture radar;high resolution imaging;radar interferometry;submillimetric motion detection;Band;CW-FM Radar;Ground Based SAR},
    doi={10.1049/cp.2015.1425},
    ISSN={},
    month=oct,
    owner = {ofrey},
    
    }
    


  11. A. Moreira, O. Ponce, M. Nannini, M. Pardini, and P. Prats. Multi-baseline imaging: A vision for spaceborne SAR. In Proc. 16th Int. Radar Symp. (IRS), pages 20-29, June 2015. Keyword(s): radar interferometry, remote sensing by radar, spaceborne radar, synthetic aperture radar, topography (Earth), across-track interferometry, along-track interferometry, glacier movement, ground deformation measurement, holography SAR, image product, multibaseline imaging, multidimensional data space, multistatic SAR configuration, ocean current measurement, polarimetric SAR interferometry, spaceborne SAR system development, sparse array, surface topography measurement, tomography SAR, Imaging, Interferometry, Radar imaging, Radar polarimetry, Spaceborne radar, Synthetic aperture radar.
    @InProceedings{Moreira2015,
    author = {A. Moreira and O. Ponce and M. Nannini and M. Pardini and P. Prats},
    title = {Multi-baseline imaging: A vision for spaceborne {SAR}},
    booktitle = {Proc. 16th Int. Radar Symp. (IRS)},
    year = {2015},
    month = jun,
    pages = {20--29},
    doi = {10.1109/IRS.2015.7226407},
    issn = {2155-5745},
    keywords = {radar interferometry, remote sensing by radar, spaceborne radar, synthetic aperture radar, topography (Earth), across-track interferometry, along-track interferometry, glacier movement, ground deformation measurement, holography SAR, image product, multibaseline imaging, multidimensional data space, multistatic SAR configuration, ocean current measurement, polarimetric SAR interferometry, spaceborne SAR system development, sparse array, surface topography measurement, tomography SAR, Imaging, Interferometry, Radar imaging, Radar polarimetry, Spaceborne radar, Synthetic aperture radar},
    owner = {ofrey},
    
    }
    


  12. M. Pieraccini, N. Agostini, F. Papi, and S. Rocchio. A rotating antenna ground-based SAR. In Proc. European Radar Conf. (EuRAD), pages 493-496, September 2015. Keyword(s): GB-SAR, ground-based SAR, terrestrial SAR, radar interferometry, synthetic aperture radar, RotoSAR, ground based linear SAR, imagery quality performances, in-field tests, rotating antenna GB-SAR, rotating antenna ground-based SAR, Monitoring, Radar antennas, Radar imaging, Radar remote sensing, Spaceborne radar, Synthetic aperture radar, GB-SAR, SAR, radar.
    @InProceedings{Pieraccini2015b,
    author = {M. Pieraccini and N. Agostini and F. Papi and S. Rocchio},
    title = {A rotating antenna ground-based {SAR}},
    booktitle = {Proc. European Radar Conf. (EuRAD)},
    year = {2015},
    month = sep,
    pages = {493--496},
    doi = {10.1109/EuRAD.2015.7346345},
    keywords = {GB-SAR,ground-based SAR, terrestrial SAR,radar interferometry, synthetic aperture radar, RotoSAR, ground based linear SAR, imagery quality performances, in-field tests, rotating antenna GB-SAR, rotating antenna ground-based SAR, Monitoring, Radar antennas, Radar imaging, Radar remote sensing, Spaceborne radar, Synthetic aperture radar, GB-SAR, SAR, radar},
    owner = {ofrey},
    
    }
    


  13. M. Pieraccini, F. Papi, and S. Rocchio. SAR imagery by RotoSAR. In Proc. Antennas and Electronic Systems (COMCAS) 2015 IEEE Int. Conf. Microwaves, Communications, pages 1-5, November 2015. Keyword(s): GB-SAR, ground-based SAR, terrestrial SAR, radar antennas, radar imaging, synthetic aperture radar, GB-SAR, RotoSAR, SAR imagery, imagery performances, in-field measurements, rotating antenna, Monitoring, Radar antennas, Radar imaging, Radar remote sensing, Spaceborne radar, Synthetic aperture radar, GB-SAR, SAR, radar.
    @InProceedings{Pieraccini2015,
    author = {M. Pieraccini and F. Papi and S. Rocchio},
    title = {{SAR} imagery by RotoSAR},
    booktitle = {Proc. Antennas and Electronic Systems (COMCAS) 2015 IEEE Int. Conf. Microwaves, Communications},
    year = {2015},
    month = nov,
    pages = {1--5},
    doi = {10.1109/COMCAS.2015.7360370},
    keywords = {GB-SAR,ground-based SAR, terrestrial SAR,radar antennas, radar imaging, synthetic aperture radar, GB-SAR, RotoSAR, SAR imagery, imagery performances, in-field measurements, rotating antenna, Monitoring, Radar antennas, Radar imaging, Radar remote sensing, Spaceborne radar, Synthetic aperture radar, GB-SAR, SAR, radar},
    owner = {ofrey},
    
    }
    


  14. O. Ponce, P. Prats, R. Scheiber, A. Reigber, I. Hajnsek, and A. Moreira. Polarimetric 3-D imaging with airborne holographic SAR tomography over glaciers. In Proc. IEEE Int. Geoscience and Remote Sensing Symp. (IGARSS), pages 5280-5283, July 2015. Keyword(s): airborne radar, glaciology, hydrological techniques, radar polarimetry, synthetic aperture radar, DLR F-SAR sensor, Findel glacier, HoloSAR campaign, L-band, Monte Rosa, Switzerland, airborne holographic SAR tomography mode, arc-pattern, bedrock vertical profile, biosphere, circular pattern, circular synthetic aperture, cryosphere, glacier backscattering, ice sheet vertical profile, polarimetric 3-D imaging reconstruction, polarimetric analysis, single circular flight, snow vertical profile, vertical synthetic aperture, Apertures, Ice, Image resolution, Radar imaging, Synthetic aperture radar, Tomography, Compressive Sensing (CS), Cryosphere, Fast Factorized Back-Projection (FFBP), Holographic SAR Tomography (HoloSAR), Polarimetric Synthetic Aperture Radar (PolSAR).
    @InProceedings{Ponce2015,
    author = {O. Ponce and P. Prats and R. Scheiber and A. Reigber and I. Hajnsek and A. Moreira},
    title = {Polarimetric {3-D} imaging with airborne holographic {SAR} tomography over glaciers},
    booktitle = {Proc. IEEE Int. Geoscience and Remote Sensing Symp. (IGARSS)},
    year = {2015},
    month = jul,
    pages = {5280--5283},
    doi = {10.1109/IGARSS.2015.7327026},
    issn = {2153-6996},
    keywords = {airborne radar, glaciology, hydrological techniques, radar polarimetry, synthetic aperture radar, DLR F-SAR sensor, Findel glacier, HoloSAR campaign, L-band, Monte Rosa, Switzerland, airborne holographic SAR tomography mode, arc-pattern, bedrock vertical profile, biosphere, circular pattern, circular synthetic aperture, cryosphere, glacier backscattering, ice sheet vertical profile, polarimetric 3-D imaging reconstruction, polarimetric analysis, single circular flight, snow vertical profile, vertical synthetic aperture, Apertures, Ice, Image resolution, Radar imaging, Synthetic aperture radar, Tomography, Compressive Sensing (CS), Cryosphere, Fast Factorized Back-Projection (FFBP), Holographic SAR Tomography (HoloSAR), Polarimetric Synthetic Aperture Radar (PolSAR)},
    owner = {ofrey},
    
    }
    


  15. Badreddine Rekioua, Matthieu Davy, and Laurent Ferro-Famil. Snowpack characterization using SAR tomography: experimental results of the AlpSAR campaign. In Radar Conference (EuRAD), 2015 European, pages 33-36, Sept 2015. Keyword(s): SAR Processing, Tomography, SAR tomography, Antennas, Ice, Lenses, Refractive index, Snow, Ground-based SAR.
    Abstract: In this paper, we present experimental results of 3D characterization of snowpack layers using Ground Based SAR (GB-SAR) data. The data have been acquired using a GB-SAR system operating at X and Ku frequency bands. We process the acquired data using the Back Projection Algorithm (BPA). The results of this processing show strong backscattering contributions from interfaces between different layers of the snowpack. We notice also geometrical distortions due to the assumption of free space propagation medium during the processing. We introduce in this paper a correction process in order to recover the true thickness of snow layers and the corresponding refractive indexes. The obtained results are discussed according to the in situ measurement relating grain size, density and snow particle shapes description at different depths of the snowpack.

    @InProceedings{rekiouaDavyFerroFamilEuRAD2015TomoSnowAlpSAR,
    author = {Rekioua, Badreddine and Davy, Matthieu and Ferro-Famil, Laurent},
    title = {Snowpack characterization using {SAR} tomography: experimental results of the {AlpSAR} campaign},
    booktitle = {Radar Conference (EuRAD), 2015 European},
    year = {2015},
    pages = {33-36},
    month = {Sept},
    abstract = {In this paper, we present experimental results of 3D characterization of snowpack layers using Ground Based SAR (GB-SAR) data. The data have been acquired using a GB-SAR system operating at X and Ku frequency bands. We process the acquired data using the Back Projection Algorithm (BPA). The results of this processing show strong backscattering contributions from interfaces between different layers of the snowpack. We notice also geometrical distortions due to the assumption of free space propagation medium during the processing. We introduce in this paper a correction process in order to recover the true thickness of snow layers and the corresponding refractive indexes. The obtained results are discussed according to the in situ measurement relating grain size, density and snow particle shapes description at different depths of the snowpack.},
    doi = {10.1109/EuRAD.2015.7346230},
    file = {:rekiouaDavyFerroFamilEuRAD2015TomoSnowAlpSAR.pdf:PDF},
    keywords = {SAR Processing, Tomography, SAR tomography, Antennas;Ice;Lenses;Refractive index;Snow, Ground-based SAR},
    owner = {ofrey},
    pdf = {../../../docs/rekiouaDavyFerroFamilEuRAD2015TomoSnowAlpSAR.pdf},
    
    }
    


  16. Muhammad Adnan Siddique, Irena Hajnsek, Urs Wegmuller, and Othmar Frey. Investigating the Combined Use of Differential SAR Tomography and PSI for Spatio-Temporal Inversion. In Proc. Joint Urban Remote Sensing Event - JURSE, pages 1-4, March 2015. Keyword(s): SAR Processing, SAR Tomography, persistent scatterer interferometry, PSI, DInSAR, multibaseline interferometry, interferometric stacking, deformation monitoring, subsidence monitoring, thermal dilation, urban, urban remote sensing, buildings, estimation, remote sensing, synthetic aperture radar, thermal expansion, tomography, urban areas.
    Abstract: Persistent Scatterer Interferometry (PSI) inherently assumes a single temporally coherent scatterer inside a range-azimuth resolution cell. This restriction leads to the rejection of numerous persistent scatterer (PS) candidates, particularly in urban areas where layovers occur frequently. Moreover, in case of high-rise buildings, it is necessary to compensate the phase associated with thermal expansion in an iterative way. It is worthwhile to approach tomographic techniques to address these concerns. SAR tomography has the potential to separate scatterers in elevation, thus resolving layover. Differential SAR tomography additionally allows retrieval of deformation parameters, including a possible thermal expansion term. In this paper, we investigate the combined use of SAR tomographic approaches and PSI for elevation and deformation estimation. Results are presented for an interferometric time-series of 50 TerraSAR-X stripmap images acquired over Barcelona city. Spatio-temporal inversion of scatterers along the facade of a high-rise building is presented as a special case.

    @InProceedings{siddiqueHajnsekWegmullerFreyJURSE2015TomoTSXBarca,
    author = {Siddique, Muhammad Adnan and Hajnsek, Irena and Wegmuller, Urs and Frey, Othmar},
    title = {Investigating the Combined Use of Differential {SAR} Tomography and {PSI} for Spatio-Temporal Inversion},
    booktitle = {Proc. Joint Urban Remote Sensing Event - JURSE},
    year = {2015},
    pages = {1-4},
    month = mar,
    abstract = {Persistent Scatterer Interferometry (PSI) inherently assumes a single temporally coherent scatterer inside a range-azimuth resolution cell. This restriction leads to the rejection of numerous persistent scatterer (PS) candidates, particularly in urban areas where layovers occur frequently. Moreover, in case of high-rise buildings, it is necessary to compensate the phase associated with thermal expansion in an iterative way. It is worthwhile to approach tomographic techniques to address these concerns. SAR tomography has the potential to separate scatterers in elevation, thus resolving layover. Differential SAR tomography additionally allows retrieval of deformation parameters, including a possible thermal expansion term. In this paper, we investigate the combined use of SAR tomographic approaches and PSI for elevation and deformation estimation. Results are presented for an interferometric time-series of 50 TerraSAR-X stripmap images acquired over Barcelona city. Spatio-temporal inversion of scatterers along the facade of a high-rise building is presented as a special case.},
    doi = {10.1109/JURSE.2015.7120504},
    file = {:siddiqueHajnsekWegmullerFreyJURSE2015TomoTSXBarca.pdf:PDF},
    keywords = {SAR Processing, SAR Tomography, persistent scatterer interferometry, PSI, DInSAR, multibaseline interferometry, interferometric stacking, deformation monitoring, subsidence monitoring, thermal dilation, urban, urban remote sensing, buildings, estimation, remote sensing, synthetic aperture radar, thermal expansion, tomography, urban areas},
    owner = {ofrey},
    pdf = {http://www.ifu-sar.ethz.ch/otfrey/SARbibliography/myPapers/siddiqueHajnsekWegmullerFreyJURSE2015TomoTSXBarca.pdf},
    
    }
    


  17. Muhammad Adnan Siddique, Irena Hajnsek, Urs Wegmuller, and Othmar Frey. Towards the integration of SAR tomography and PSI for improved deformation assessment in urban areas. In Proc. FRINGE 2015, ESA SP-731, March 2015. Keyword(s): SAR Processing, SAR Tomography, persistent scatterer interferometry, PSI, DInSAR, multibaseline interferometry, interferometric stacking, deformation monitoring, subsidence monitoring, thermal dilation, urban, urban remote sensing.
    Abstract: Persistent scatterer interferometry (PSI) typically rejects the range-azimuth pixels containing multiple scatterers, such as in a layover scenario. Since layovers occur frequently in urban areas, a significant number of candidates may get rejected. SAR tomography allows for resolving layover and has thus the potential to extend the spatial sampling of deformation measurements to layoveraffected areas. Using extended phase models, also taking into account temperature, an improved simultaneous estimation of elevation, deformation velocity, and temperature-induced scatterer displacement is possible. This paper explores the combined use of PSI and SAR tomography for deformation analysis in urban areas, using a multibaseline and multitemporal interferometric stack of stripmap TerraSAR-X images acquired over the city of Barcelona.

    @InProceedings{siddiqueHajnsekWegmullerFreyFRINGE2015TomoTSXBarca,
    author = {Siddique, Muhammad Adnan and Hajnsek, Irena and Wegmuller, Urs and Frey, Othmar},
    title = {Towards the integration of {SAR} tomography and {PSI} for improved deformation assessment in urban areas},
    booktitle = {Proc. FRINGE 2015},
    year = {2015},
    series = {ESA SP-731},
    month = mar,
    abstract = {Persistent scatterer interferometry (PSI) typically rejects the range-azimuth pixels containing multiple scatterers, such as in a layover scenario. Since layovers occur frequently in urban areas, a significant number of candidates may get rejected. SAR tomography allows for resolving layover and has thus the potential to extend the spatial sampling of deformation measurements to layoveraffected areas. Using extended phase models, also taking into account temperature, an improved simultaneous estimation of elevation, deformation velocity, and temperature-induced scatterer displacement is possible. This paper explores the combined use of PSI and SAR tomography for deformation analysis in urban areas, using a multibaseline and multitemporal interferometric stack of stripmap TerraSAR-X images acquired over the city of Barcelona.},
    file = {:siddiqueHajnsekWegmullerFreyFRINGE2015TomoTSXBarca.pdf:PDF},
    keywords = {SAR Processing, SAR Tomography, persistent scatterer interferometry, PSI, DInSAR, multibaseline interferometry, interferometric stacking, deformation monitoring, subsidence monitoring, thermal dilation, urban, urban remote sensing},
    owner = {ofrey},
    pdf = {http://www.ifu-sar.ethz.ch/otfrey/SARbibliography/myPapers/siddiqueHajnsekWegmullerFreyFRINGE2015TomoTSXBarca.pdf},
    
    }
    


  18. Muhammad Adnan Siddique, Urs Wegmuller, Irena Hajnsek, and Othmar Frey. SAR tomography for spatio-temporal inversion of point-like scatterers in urban areas. In Proc. IEEE Int. Geosci. Remote Sens. Symp., volume 1, pages 5272-5275, July 2015. Keyword(s): SAR Processing, SAR tomography, Synthetic aperture radar (SAR), SAR Interferometry, InSAR, interferometric stacking, persistent scatterer interferometry, PSI, spaceborne SAR radar interferometry, spaceborne radar, X-Band, TerraSAR-X, synthetic aperture radar, tomography, 3-D point cloud retrieval, Barcelona, SAR tomography based 3-D point cloud extraction, high-resolution spaceborne TerraSAR-X data, interferometric stack, high-rise building vertical tomographic slice, layover scenario case, persistent scatterer interferometry, PSI, point-like scatterer, processing approach, Urban Remote Sensing, Spaceborne radar, Synthetic aperture radar, Three-dimensional displays, Tomography, 3-D point cloud, SAR interferometry.
    Abstract: Persistent scatterer interferometry (PSI) assumes the presence of a single temporally coherent scatterer in a range-azimuth pixel. Multiple scatterers interfering in the same pixel, as for the case of a layover, are typically rejected. Conventional SAR tomography (3D SAR) is a means to separate the individual scatterers in layover. Advanced tomographic inversion approaches employing extended phase models additionally allow simultaneous retrieval of scatterer elevation and deformation parameters. In this way, SAR tomography can increase deformation sampling and thereby complement a PSI-based analysis. This paper investigates the use of tomography as an add-on to PSI for spatio-temporal inversion of single and double scatterers in urban areas. Results are provided on an interferometric stack of 50 stripmap TerraSAR-X images acquired over the city of Barcelona.

    @InProceedings{siddiqueWegmullerHajnsekFreyIGARSS2015PSITomo,
    author = {Muhammad Adnan Siddique and Urs Wegmuller and Irena Hajnsek and Othmar Frey},
    title = {{SAR} tomography for spatio-temporal inversion of point-like scatterers in urban areas},
    booktitle = {Proc. IEEE Int. Geosci. Remote Sens. Symp.},
    year = {2015},
    volume = {1},
    pages = {5272-5275},
    month = jul,
    abstract = {Persistent scatterer interferometry (PSI) assumes the presence of a single temporally coherent scatterer in a range-azimuth pixel. Multiple scatterers interfering in the same pixel, as for the case of a layover, are typically rejected. Conventional SAR tomography (3D SAR) is a means to separate the individual scatterers in layover. Advanced tomographic inversion approaches employing extended phase models additionally allow simultaneous retrieval of scatterer elevation and deformation parameters. In this way, SAR tomography can increase deformation sampling and thereby complement a PSI-based analysis. This paper investigates the use of tomography as an add-on to PSI for spatio-temporal inversion of single and double scatterers in urban areas. Results are provided on an interferometric stack of 50 stripmap TerraSAR-X images acquired over the city of Barcelona.},
    doi = {10.1109/IGARSS.2015.7327024},
    file = {:siddiqueWegmullerHajnsekFreyIGARSS2015PSITomo.pdf:PDF},
    keywords = {SAR Processing, SAR tomography; Synthetic aperture radar (SAR); SAR Interferometry, InSAR, interferometric stacking;persistent scatterer interferometry; PSI, spaceborne SAR radar interferometry;spaceborne radar; X-Band, TerraSAR-X, synthetic aperture radar;tomography;3-D point cloud retrieval; Barcelona; SAR tomography based 3-D point cloud extraction; high-resolution spaceborne TerraSAR-X data, interferometric stack;high-rise building vertical tomographic slice; layover scenario case;persistent scatterer interferometry; PSI, point-like scatterer;processing approach;Urban Remote Sensing; Spaceborne radar;Synthetic aperture radar;Three-dimensional displays;Tomography; 3-D point cloud;SAR interferometry},
    owner = {ofrey},
    pdf = {http://www.ifu-sar.ethz.ch/otfrey/SARbibliography/myPapers/siddiqueWegmullerHajnsekFreyIGARSS2015PSITomo.pdf},
    
    }
    


  19. Urs Wegmuller and Charles L. Werner. Mitigation of thermal expansion phase in persistent scatterer interferometry in an urban environment. In 2015 Joint Urban Remote Sensing Event (JURSE), pages 1-4, 2015. IEEE.
    @InProceedings{wegmullerWernerJURSE2015PSIThermalExpansion,
    author = {Wegmuller, Urs and Werner, Charles L.},
    title = {Mitigation of thermal expansion phase in persistent scatterer interferometry in an urban environment},
    booktitle = {2015 Joint Urban Remote Sensing Event (JURSE)},
    year = {2015},
    organization = {IEEE},
    pages = {1-4},
    owner = {ofrey},
    
    }
    


  20. Urs Wegmuller, Charles L. Werner, Tazio Strozzi, Andreas Wiesmann, and Othmar Frey. Sentinel-1 support in the GAMMA Software. In Proc. FRINGE 2015, ESA SP-731, pages 1-6, March 2015. Keyword(s): SAR Processing, Sentinel-1, Spaceborne SAR, C-band, European Space Agency, ESA, Terrain Observation by Progressive Scans, TOPS, TOPSAR.
    Abstract: First results using the new Sentinel-1 SAR look very promising but the special interferometric wide-swath data acquired in the TOPS mode makes InSAR processing challenging. The steep azimuth spectra ramp in each burst results in very stringent co-registration requirements. Combining the data of the individual bursts and sub-swaths into consistent mosaics requires careful book-keeping in the handling of the data and meta data and the large file sizes and high data throughputs require also a good performance. Considering these challenges good support from software is getting increasingly important. In this contribution we describe the Sentinel-1 support in the GAMMA Software, a high-level software package used by researchers, service providers and operational users in their SAR, InSAR and PSI work.

    @InProceedings{wegmullerWernerStrozziWiesmannFreyFRINGE2015Sentinel1Gamma,
    author = {Urs Wegmuller and Charles L. Werner and Tazio Strozzi and Andreas Wiesmann and Othmar Frey},
    title = {Sentinel-1 support in the {GAMMA} Software},
    booktitle = {Proc. FRINGE 2015},
    year = {2015},
    series = {ESA SP-731},
    pages = {1-6},
    month = mar,
    abstract = {First results using the new Sentinel-1 SAR look very promising but the special interferometric wide-swath data acquired in the TOPS mode makes InSAR processing challenging. The steep azimuth spectra ramp in each burst results in very stringent co-registration requirements. Combining the data of the individual bursts and sub-swaths into consistent mosaics requires careful book-keeping in the handling of the data and meta data and the large file sizes and high data throughputs require also a good performance. Considering these challenges good support from software is getting increasingly important. In this contribution we describe the Sentinel-1 support in the GAMMA Software, a high-level software package used by researchers, service providers and operational users in their SAR, InSAR and PSI work.},
    file = {:wegmullerWernerStrozziWiesmannFreyFRINGE2015Sentinel1Gamma.pdf:PDF},
    keywords = {SAR Processing, Sentinel-1, Spaceborne SAR, C-band, European Space Agency, ESA, Terrain Observation by Progressive Scans, TOPS,TOPSAR},
    pdf = {http://www.ifu-sar.ethz.ch/otfrey/SARbibliography/myPapers/wegmullerWernerStrozziWiesmannFreyFRINGE2015Sentinel1Gamma.pdf},
    
    }
    


  21. Urs Wegmuller, Charles L. Werner, Tazio Strozzi, Andreas Wiesmann, Othmar Frey, and Maurizio Santoro. Sentinel-1 IWS mode support in the GAMMA software. In IEEE 5th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR), pages 431-436, September 2015. Keyword(s): SAR Processing, TOPS, TOPS mode, Terrain Observation by Progressive Scans, Sentinel-1, Interferometry, SAR Interferometry, Spaceborne SAR, geophysics computing, image registration, meta data, radar computing, radar imaging, radar interferometry, remote sensing by radar, synthetic aperture radar, Fhe steep azimuth spectra ramp, GAMMA software, IWS data, InSAR processing, PSI, Sentinel-1 IWS mode support, Sentinel-1 SAR, TOPS, high-level software package, interferometrie wide-swath data, meta data, synthetic aperture radar, Apertures, Conferences, Decision support systems, DINSAR, GAMMA Software, Nepal earthquake, PSI, Sentinel-1 TOPS IWS, ionospheric effects, offset-tracking, spectral diversity, split-beam interferometry.
    Abstract: First results using the new Sentinel-1 SAR look very promising, but the special interferometrie wide-swath (IWS) data acquired in the TOPS mode makes InSAR processing challenging. The steep azimuth spectra ramp in each burst results in very stringent co-registration requirements. Combining the data of the individual bursts and sub-swaths into consistent mosaics requires careful bookkeeping in the handling of the data and meta data and the large file sizes and high data throughputs require also a good performance. Considering these challenges good support from software is getting increasingly important. In this contribution we describe the Sentinel-1 support in the GAMMA Software, a high-level software package used by researchers, service providers and operational users in their SAR, InSAR and PSI work.

    @InProceedings{wegmullerWernerStrozziWiesmannFreySantoro2015,
    author = {Wegmuller, Urs and Werner, Charles L. and Strozzi, Tazio and Wiesmann, Andreas and Frey, Othmar and Santoro, Maurizio},
    title = {{Sentinel-1} {IWS} mode support in the {GAMMA} software},
    booktitle = {IEEE 5th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR)},
    year = {2015},
    pages = {431-436},
    month = sep,
    abstract = {First results using the new Sentinel-1 SAR look very promising, but the special interferometrie wide-swath (IWS) data acquired in the TOPS mode makes InSAR processing challenging. The steep azimuth spectra ramp in each burst results in very stringent co-registration requirements. Combining the data of the individual bursts and sub-swaths into consistent mosaics requires careful bookkeeping in the handling of the data and meta data and the large file sizes and high data throughputs require also a good performance. Considering these challenges good support from software is getting increasingly important. In this contribution we describe the Sentinel-1 support in the GAMMA Software, a high-level software package used by researchers, service providers and operational users in their SAR, InSAR and PSI work.},
    doi = {10.1109/APSAR.2015.7306242},
    file = {:wegmullerWernerStrozziWiesmannFreySantoro2015.pdf:PDF},
    keywords = {SAR Processing, TOPS, TOPS mode, Terrain Observation by Progressive Scans, Sentinel-1, Interferometry, SAR Interferometry, Spaceborne SAR, geophysics computing;image registration;meta data;radar computing;radar imaging;radar interferometry;remote sensing by radar;synthetic aperture radar;Fhe steep azimuth spectra ramp;GAMMA software;IWS data;InSAR processing;PSI;Sentinel-1 IWS mode support;Sentinel-1 SAR;TOPS;high-level software package;interferometrie wide-swath data;meta data;synthetic aperture radar;Apertures;Conferences;Decision support systems;DINSAR;GAMMA Software;Nepal earthquake;PSI;Sentinel-1 TOPS IWS;ionospheric effects;offset-tracking;spectral diversity;split-beam interferometry},
    
    }
    


  22. Urs Wegmuller, Charles L. Werner, Andreas Wiesmann, Tazio Strozzi, and Othmar Frey. Wide-area persistent scatterer interferometry with Sentinel-1 TOPS mode data. In Proc. IEEE Int. Geosci. Remote Sens. Symp., volume 1, pages 1-4, July 2015. Note: Abstract.Keyword(s): SAR Processing, Sentinel-1, TOPS, Terrain Observation by progressive scans, ESA, European Space Agency, C-Band, Spaceborne SAR, Persistent Scatterer Interferometry, PSI, Interferometry, SAR Interferometry, geophysical signal processing, radar polarimetry, synthetic aperture radar.
    Abstract: In 2014 the Sentinel-1A satellite was launched as part of the EU/ESA Copernicus Program. One of the novelties of the Sentinel 1 SAR (S1) mission is that the satellite is mainly operated in the so-called TOPS mode [1]. TOPS stands for Terrain Observation with Progressive Scans in azimuth, but the word is also the reverse of SPOT and actually the beam scanning done is the opposite of the scanning done in spotlight mode. One of the strengths of TOPS mode is that wide areas can be covered. In the in IWS (Interferometric Wide-Swath) mode of S1 the width of the strips is about 250km. S1 is operated at C-band with an orbit repeat cycle of 12 days. The orbital tube is very narrow (of the order of 100m) and the TOPS mode bursts are almost perfectly synchronized. As a result S1 IWS data are well suited for interferometric SAR (InSAR). First very promising S1 interferograms were presented by several authors at two workshops organized by ESA in September and December 2014. An example of a S1 IWS differential interferogram is shown in Figure 1. Such results confirm on one hand the usefulness of S1 TOPS mode data for interferometric techniques and on the other hand the adequacy of the processing techniques applied. In particular the co-registration accuracy requirements are very stringent [2]. Because of the strong Doppler Centroid variation within each burst even a very tiny azimuth co-registration error of 0.01 pixel lead to significant phase jumps between adjacent bursts in the resulting interferogram. Spectral diversity techniques [3] permit refining the co-registration to the required level considering in the burst overlap area the difference between the interferometric phases of the two overlapping bursts. Being confident about the co-registration and interferometric processing we investigated as a next step how well Persistent Scatterer Interferometry (PSI) can be applied. Regular IWS acquisitions started in October 2014. Thanks to the 12 day repeat cycle consistent data stacks suited for PSI are now becoming available.

    @InProceedings{wegmullerWernerWiesmannStrozziFreyIGARSS2015Sentinel1InSAR,
    Title = {Wide-area persistent scatterer interferometry with {Sentinel-1} {TOPS} mode data},
    Author = {Urs Wegmuller and Charles L. Werner and Andreas Wiesmann and Tazio Strozzi and Othmar Frey},
    Booktitle = {Proc. IEEE Int. Geosci. Remote Sens. Symp.},
    Month = jul,
    Note = {Abstract.},
    Pages = {1-4},
    Volume = {1},
    Year = {2015},
    Abstract = {In 2014 the Sentinel-1A satellite was launched as part of the EU/ESA Copernicus Program. One of the novelties of the Sentinel 1 SAR (S1) mission is that the satellite is mainly operated in the so-called TOPS mode [1]. TOPS stands for Terrain Observation with Progressive Scans in azimuth, but the word is also the reverse of SPOT and actually the beam scanning done is the opposite of the scanning done in spotlight mode. One of the strengths of TOPS mode is that wide areas can be covered. In the in IWS (Interferometric Wide-Swath) mode of S1 the width of the strips is about 250km. S1 is operated at C-band with an orbit repeat cycle of 12 days. The orbital tube is very narrow (of the order of 100m) and the TOPS mode bursts are almost perfectly synchronized. As a result S1 IWS data are well suited for interferometric SAR (InSAR). First very promising S1 interferograms were presented by several authors at two workshops organized by ESA in September and December 2014. An example of a S1 IWS differential interferogram is shown in Figure 1. Such results confirm on one hand the usefulness of S1 TOPS mode data for interferometric techniques and on the other hand the adequacy of the processing techniques applied. In particular the co-registration accuracy requirements are very stringent [2]. Because of the strong Doppler Centroid variation within each burst even a very tiny azimuth co-registration error of 0.01 pixel lead to significant phase jumps between adjacent bursts in the resulting interferogram. Spectral diversity techniques [3] permit refining the co-registration to the required level considering in the burst overlap area the difference between the interferometric phases of the two overlapping bursts. Being confident about the co-registration and interferometric processing we investigated as a next step how well Persistent Scatterer Interferometry (PSI) can be applied. Regular IWS acquisitions started in October 2014. Thanks to the 12 day repeat cycle consistent data stacks suited for PSI are now becoming available.},
    Keywords = {SAR Processing, Sentinel-1, TOPS, Terrain Observation by progressive scans, ESA, European Space Agency, C-Band, Spaceborne SAR, Persistent Scatterer Interferometry, PSI, Interferometry, SAR Interferometry, geophysical signal processing, radar polarimetry, synthetic aperture radar} 
    }
    


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This collection of SAR literature is far from being complete.
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Last modified: Mon Feb 1 16:39:00 2021
Author: Othmar Frey, Earth Observation and Remote Sensing, Institute of Environmental Engineering, Swiss Federal Institute of Technology - ETH Zurich .


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