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Publications about 'AD 2012'

Articles in journal or book chapters

  1. 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] [bibtex-entry]


  2. 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] [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]


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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 16:39:06 2021
Author: Othmar Frey, Earth Observation and Remote Sensing, Institute of Environmental Engineering, Swiss Federal Institute of Technology - ETH Zurich .


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