Publications about 'Anisotropy'

Articles in journal or book chapters

  1. S. Leinss, H. Löwe, M. Proksch, and A. Kontu. Modeling the evolution of the structural anisotropy of snow. The Cryosphere, 14(1):51-75, 2020. [Abstract] [bibtex-entry]

  2. S. Leinss, H. Löwe, 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. [bibtex-entry]

  3. Silvan Leinss, Giuseppe Parrella, and Irena Hajnsek. Snow height determination by polarimetric phase differences in X-band SAR data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7(9):3794-3810, Sept 2014. Keyword(s): hydrological techniques, remote sensing by radar, snow, synthetic aperture radar, AD 2012 01, AD 2012 12 to 2013 04, CPD temporal evolution, Finland, HH polarization, Sodankylae city, TanDEM-X, TanDEM-X acquisitions, TerraSAR-X acquisitions, VV polarization, X-band SAR acquisitions, X-band SAR data, aligned elliptical particles, computer tomography observations, copolar phase difference, fresh snow depth, polarimetric phase difference, snow height determination, snow microstructure, subsequent recrystallization process, temperature-gradient-driven recrystallization process, weather station data, Backscatter, Scattering, Snow, Soil, Soil measurements, Synthetic aperture radar, Temperature measurement, Birefringence, TanDEM-X, TerraSAR-X, VV-HH phase difference, copolar phase difference, dry snow, fresh snow, polarimetry, snow anisotropy, snow microstructure, synthetic aperture radar. [Abstract] [bibtex-entry]

  4. M. \cCetin, I. Stojanovic, N.O. Önhon, K.R. Varshney, S. Samadi, W.C. Karl, and A.S. Willsky. Sparsity-Driven Synthetic Aperture Radar Imaging: Reconstruction, autofocusing, moving targets, and compressed sensing. etationationToImprovePrecipitati, 31(4):27-40, July 2014. Keyword(s): SAR Processing, Autofocus, compressed sensing, image representation, radar imaging, synthetic aperture radar, SAR image formation, SAR sensing mission design, anisotropy characterization, compressed sensing-based analysis, joint autofocusing, joint imaging, phase errors, sparsity-based methods, sparsity-driven synthetic aperture radar imaging, synthesis-based sparse signal representation formulations, wide-angle SAR imaging, Image reconstruction, Imaging, Radar imaging, Radar polarimetry, Scattering, Synthetic aperture radar. [Abstract] [bibtex-entry]

  5. B. Minchew, C.E. Jones, and B. Holt. Polarimetric Analysis of Backscatter From the Deepwater Horizon Oil Spill Using L-Band Synthetic Aperture Radar. Geoscience and Remote Sensing, IEEE Transactions on, 50(10):3812-3830, October 2012. Keyword(s): AD 2010 06 23, Bragg scattering mechanism, DWH slick, Gulf of Mexico, L-band synthetic aperture radar, backscatter polarimetric analysis, coherency matrix eigenvalue, deepwater horizon, deepwater horizon oil spill, dielectric constant, entropy parameters, fully-polarimetric uninhabited aerial vehicle, ocean wave spectral components, oil slick, oil volumetric concentration, radar backscatter, sea water, slick detection method, substantial variation parameter, surface scattering analysis, synthetic aperture radar data, backscatter, eigenvalues and eigenfunctions, entropy, marine pollution, matrix algebra, ocean chemistry, ocean waves, oceanographic regions, oceanographic techniques, permittivity, radar interferometry, remote sensing by radar, seawater, synthetic aperture radar;. [Abstract] [bibtex-entry]

  6. Maxim Neumann, Laurent Ferro-Famil, and Andreas Reigber. Estimation of Forest Structure, Ground, and Canopy Layer Characteristics From Multibaseline Polarimetric Interferometric SAR Data. IEEE Trans. Geosci. Remote Sens., 48(3):1086-1104, March 2010. Keyword(s): SAR Processing, Multibaseline SAR, Germany, PolInSAR, RVoG, vertical structure, Traunstein test site, airborne SAR, L-band, angular distribution, canopy layer heights, differential extinction, double-bounce ground-trunk interactions, forest layer heights, forest parameter retrieval, forest structure estimation, forest vegetation, ground topography, ground-to-volume ratio, ground-truth measurements, interferometric coherence, particle scattering anisotropy, polarimetric Synthetic Aperture Radar interferometry, polarimetric decomposition, polarimetric scattering media model, polarization orientation randomness, random-volume-over-ground PolInSAR parameter inversion, repeat-pass configuration, root-mean-square error, surface scattering, temporal decorrelation, tree morphology, volume coherency matrices, volumetric canopy, volumetric understory scattering, wave attenuation, radar interferometry, radar polarimetry, remote sensing by radar, synthetic aperture radar, vegetation mapping;. [Abstract] [bibtex-entry]

  7. Xiao Xiang Zhu and Richard Bamler. Tomographic SAR Inversion by $L_1$-Norm Regularization --- The Compressive Sensing Approach. IEEE Trans. Geosci. Remote Sens., 48(10):3839-3846, 2010. Keyword(s): SAR Processing, SAR Tomography, Tomography, Compressive Sensing, CS, InSAR, SAR Interferometry, Interferometry, Anisotropic magnetoresistance, Azimuth, Control systems, Image reconstruction, Radar tracking, Reconstruction algorithms, Signal resolution, Spaceborne radar, Synthetic aperture radar, Tomography, image reconstruction, image resolution, radar imaging, radar resolution, remote sensing by radar, spaceborne radar, synthetic aperture radar, 3D imaging, 3D tomographic resolution element, L1-norm regularization, azimuth-range cell, compressive sensing, elevation direction, point localization, spaceborne SAR systems, super-resolution reconstruction algorithm, synthetic aperture radar, tomographic SAR inversion, tomographic elevation resolution, Compressive sensing (CS), TerraSAR-X, differential synthetic aperture radar tomography (D-TomoSAR), urban mapping. [Abstract] [bibtex-entry]

  8. Franck Garestier, Pascale C. Dubois-Fernandez, Dominique Guyon, and Thuy Le Toan. Forest Biophysical Parameter Estimation Using L- and P-Band Polarimetric SAR Data. IEEE Transactions on Geoscience and Remote Sensing, 47(10):3379-3388, October 2009. Keyword(s): SAR Processing, Biomass, Biophysical Parameters, Forst, L-Band, P-Band, PolSAR, SAR Polarimetry, Airborne SAR, RAMSES, ONERA. [Abstract] [bibtex-entry]

  9. Jong-Sen Lee, T.L. Ainsworth, J.P. Kelly, and C. Lopez-Martinez. Evaluation and Bias Removal of Multilook Effect on Entropy/Alpha/Anisotropy in Polarimetric SAR Decomposition. IEEE Trans. Geosci. Remote Sens., 46(10):3039-3052, Oct. 2008. Keyword(s): Monte Carlo methods, geophysical techniques, radar interferometry, radar polarimetry, remote sensing by radar, synthetic aperture radar, vegetationGerman Aerospace Research Center, JPL, Jet Propulsion Laboratory, L-band Advanced Land Observing Satellite, Monte Carlo simulation, airborne X-band polarimetric SAR, airborne interferometric SAR, alpha estimation, anisotropy estimation, bias removal algorithm, entropy estimation, forest, geophysical parameter estimation, grassland, multilook processing, phased array type L-band SAR, polarimetric SAR decomposition, scattering mechanisms, synthetic aperture radar, urban returns. [Abstract] [bibtex-entry]

  10. Shane R. Cloude and Eric Pottier. An entropy based classification scheme for land applications of polarimetric SAR. IEEE Trans. Geosci. Remote Sens., 35(1):68-78, January 1997. Keyword(s): SAR Processing, Polarimetric Decomposition, Cloude-Pottier Decomposition, Polarimetry, PolSAR, Entropy, Anisotropy, Alpha, H-A-alpha, S-matrix theory, geophysical signal processing, geophysical techniques, image classification, radar imaging, radar polarimetry, radar theory, remote sensing by radar, synthetic aperture radar, S-matrix theory, average target scattering matrix parameters, coherency matrix, eigenvalue analysis, entropy based classification, geophysical measurement technique, image classification, land surface, land use, parameterization, polarimetric SAR, polarimetric scattering problem, quantitative analysis, radar polarimetry, radar remote sensing, scattering entropy, terrain mapping, three-level Bernoulli statistical model, unsupervised classifier. [Abstract] [bibtex-entry]

Conference articles

  1. O. Ponce, P. Prats, R. Scheiber, A. Reigber, and A. Moreira. Analysis and optimization of multi-circular SAR for fully polarimetric holographic tomography over forested areas. In Proc. IEEE Int. Geoscience and Remote Sensing Symp. - IGARSS, pages 2365-2368, July 2013. Keyword(s): geophysical image processing, holography, radar imaging, radar polarimetry, synthetic aperture radar, vegetation, 3D resolution, DLR F-SAR sensor, GLRT algorithm, Germany, IRF, Kauf-beuren, L-band, acquisition geometry, anisotropic analysis, forested areas, fully polarimetric holographic tomography, generalized likelihood ratio test, holographic SAR tomograms, impulse response function, incoherent imaging, multicircular SAR analysis, multicircular SAR optimization, polarimetric MCSAR campaign, scatterers, sidelobe suppression, system bandwidth, Apertures, Bandwidth, Geometry, Image resolution, Imaging, L-band, Synthetic aperture radar, Anisotropy, compressive sensing (CS), fast factorized back-projection (FFBP), holographic tomography, multi-circular synthetic aperture radar (MCSAR), polarimetric synthetic aperture radar (PolSAR). [bibtex-entry]



Please note that access to full text PDF versions of papers is restricted to the Chair of Earth Observation and Remote Sensing, Institute of Environmental Engineering, ETH Zurich.
Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright.

This collection of SAR literature is far from being complete.
It is rather a collection of papers which I store in my literature data base. Hence, the list of publications under PUBLICATIONS OF AUTHOR'S NAME should NOT be mistaken for a complete bibliography of that author.

Last modified: Mon Feb 1 16:39:11 2021
Author: Othmar Frey, Earth Observation and Remote Sensing, Institute of Environmental Engineering, Swiss Federal Institute of Technology - ETH Zurich .

This document was translated from BibTEX by bibtex2html