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Assessment of Terrain Dependence of Radiometric Terrain Corrected C-Band Sentinel-1 SAR Backscatter over Different Target Types

IGARSS 2023 - 2023 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM(2023)

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摘要
Now, more than ever, there is a need for higher-quality products for remote-sensing end users. Following recent advancements in synthetic aperture radar (SAR) processing algorithms, we provide a full assessment of the radiometric dependence of geocoded C-band SAR backscatter processed with radiometric terrain correction (RTC) over differing target types. In particular, we compare the flatness of RTC-normalized backscatter coefficient gamma-naught with respect to local incidence angle over 46 Sentinel-1 (S1) datasets representing about 20 land classes in the Copernicus Global Land Service (CGLS) Land Cover 100m classification using the Observational Products for End-Users from Remote Sensing (OPERA) RTC-S1 product workflow and the ISCE3 framework. We also calculate the mean and median radar backscatter over areas of foreslope and backslope. Our results suggest that the dependence of gamma-naught on the local topography depends strongly on the land type and only exhibits near-constant behavior in certain forest land types. Evidence also suggests that as we move further away from densely tree-covered areas, the dependence of gamma-naught on the local incidence angle becomes stronger.
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关键词
C-band Sentinel-1 SAR backscatter,CGLS land cover classification,Copernicus Global Land Service,densely tree-covered areas,forest land types,local topography,mean radar backscatter,median radar backscatter,Observational Products for End-Users from Remote Sensing,OPERA RTC-S1 product workflow,radiometric terrain correction,SAR processing algorithms,synthetic aperture radar
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