Estimation of snow density using full-polarimetric Synthetic Aperture Radar (SAR) data |
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| Institution: | 1. Yazd University, Natural Resources Faculty, P. O. Box: 8961719311, Iran;2. Ardakan University, College of Agr. and Natural Resources, P. O. Box: 8951656767, Iran;1. Department of Civil and Environmental Engineering, Politecnico di Milano, Piazza Leonardo da Vinci, Milano, Italy;2. Snow and Ice Research Center, National Research Institute for Earth Science and Disaster Prevention, Suyoshi-machi, Nagaoka-shi, Niigata-ken, 940-0821, Japan;1. School of Geography and Planning, Guangdong Key Laboratory for Urbanization and Geo-simulation, Sun Yat-sen University, Guangzhou 510275, Guangdong, China;2. Department of Geography, Dartmouth College, Hanover, NH, 03755, USA;3. Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, 818 South Beijing Road, Urumqi, Xinjiang, China;1. Environment and Climate Change Canada, Climate Research Division, Toronto, Canada;2. Université de Sherbrooke, Centre d''Applications et de Recherches en Télédétection, Québec, Canada;3. University of Alaska Fairbanks, Geophysical Institute, Fairbanks, AK, USA;4. Finnish Meteorological Institute, Arctic Research, Helsinki, Finland;5. Chinese Academy of Sciences, Institute of Remote Sensing and Digital Earth, Beijing, China;6. Wilfrid Laurier University, Cold Regions Centre, Waterloo, Canada;7. Environment and Climate Change Canada, Wildlife and Landscape Science Division, Ottawa, Canada;8. Université de Montréal, Département de Géographie, Montréal, Canada;9. Northumbria University, Department of Geography and Environmental Sciences, Newcastle upon Tyne, UK |
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| Abstract: | In this paper, a new snow density estimation methodology is proposed for full-polarimetric Synthetic Aperture Radar (SAR) data. The generalized four component polarimetric decomposition with unitary transformation (G4U) based generalized volume parameter is utilized to invert snowpack dielectric constant using the Fresnel transmission coefficients. The snow density is then estimated using an empirical relationship. Six Radarsat-2 fine resolution full-polarimetric C-band datasets were acquired over Himachal Pradesh, India. The near-real time in-situ measurements were collected with the satellite pass to validate the proposed method. The mean absolute error (MAE) of the proposed method is 0.027 g cm?3 and the root mean square error (RMSE) is 0.032 g cm?3. The snow density variation within a season were also analyzed using multi-temporal Radarsat-2 data. |
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| Keywords: | SAR Polarimetry Decomposition Dielectric Snow density |
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