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Publications about 'double-bounce scattering'

Articles in journal or book chapters

  1. Albert R. Monteith and Lars M. H. Ulander. Temporal Survey of P- and L-Band Polarimetric Backscatter in Boreal Forests. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 11(10):3564-3577, October 2018. Keyword(s): SAR Tomography, backscatter, radar imaging, radar polarimetry, remote sensing by radar, spaceborne radar, synthetic aperture radar, vegetation mapping, temporal survey, L-band polarimetric backscatter, boreal forests, environmental conditions, seasonal variations, backscattered radar signal, biomass retrieval scheme, synthetic aperture radar data, electromagnetic scattering mechanisms, biomass estimation algorithms, L-band SAR missions, temporal changes, HV-polarized P, L-band radar backscatter, boreal forest site, environmental parameters, mature Norway spruce, above-ground biomass, approximately 250 tons/ha, BorealScat tower-based scatterometer, L-band backscatter, HH/VV backscatter ratio, average backscatter, double-bounce scattering, severe temporal decorrelation, P-band temporal coherence, mass 250.0 ton, time 5.0 min, noise figure 4.0 dB to 10.0 dB, Synthetic aperture radar, L-band, Backscatter, Biomass, Antenna arrays, Coherence, Backscatter, boreal forest, L-band, P-band, synthetic aperture radar (SAR), temporal coherence, time series. [Abstract] [bibtex-entry]


  2. Simon H. Yueh, Steve J. Dinardo, Ahmed Akgiray, Richard West, Donald W. Cline, and Kelly Elder. Airborne Ku-Band Polarimetric Radar Remote Sensing of Terrestrial Snow Cover. IEEE Transactions on Geoscience and Remote Sensing, 47(10):3347-3364, October 2009. Keyword(s): snow, ku-band, airborne radar, backscatter, hydrological techniques, ice, radar cross-sections, radar polarimetry, remote sensing by radar, snow, vegetation, AD 2006 to 2008, CLPX-II, Cold Land Processes Experiment, Colorado, HH/VV backscatter ratio, Ku-band polarimetric scatterometer, POLSCAT data acquisition, USA, airborne Ku-band polarimetric radar, biomass, freeze-thaw cycles, ice crust layers, ice lenses, radar echoes, radar signals, radiative transfer scattering model, remote sensing, snow-grain size, snow-water-equivalent accumulation, snowpack change, surface hoar growth, terrestrial snow cover, vegetation types, Microwave remote sensing, radar, snow. [Abstract] [bibtex-entry]


  3. Y. Yamaguchi, T. Moriyama, M. Ishido, and H. Yamada. Four-component scattering model for polarimetric SAR image decomposition. IEEE Trans. Geosci. Remote Sens., 43(8):1699-1706, August 2005. Keyword(s): SAR Processing, polarimetric decomposition, Yamaguchi decomposition, asymmetric covariance matrix, cloud, co-pol correlation, cross-pol correlation, dipole scatterers, double bounce scattering, four-component scattering model, helix scattering power, image decomposition, nonreflection symmetric scattering, polarimetric SAR, probability density function, radar polarimetry, reflection symmetry condition, scattering contribution decomposition, surface scattering, symmetric covariance matrix, synthetic aperture radar, three-component decomposition method, urban area scattering, volume scattering, covariance matrices, geophysical signal processing, probability, radar polarimetry, remote sensing by radar, synthetic aperture radar. [Abstract] [bibtex-entry]


Conference articles

  1. G. Krieger, T. Rommel, and A. Moreira. MIMO-SAR Tomography. In Proceedings of EUSAR 2016: 11th European Conference on Synthetic Aperture Radar, pages 1-6, June 2016. [Abstract] [bibtex-entry]


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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.
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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 16:39:38 2021
Author: Othmar Frey, Earth Observation and Remote Sensing, Institute of Environmental Engineering, Swiss Federal Institute of Technology - ETH Zurich .


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