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Angular-Based Radiometric Slope Correction for Sentinel-1 on Google Earth Engine

Published on
June 9, 2020

An article of Andreas Vollrath, Adugna Mullissa and Johannes Reiche: Angular-Based Radiometric Slope Correction for Sentinel-1 on Google Earth Engine, has been published in Remote Sensing 2020, 12(11), 1867.

doi:10.3390/rs12111867

Abstract
This article provides an angular-based radiometric slope correction routine for Sentinel-1 SAR imagery on the Google Earth Engine platform. Two established physical reference models are implemented. The first model is optimised for vegetation applications by assuming volume scattering on the ground. The second model is optimised for surface scattering, and therefore targeted at urban environments or analysis of soil characteristics. The framework of both models is extended to simultaneously generate masks of invalid data in active layover and shadow affected areas. A case study, using openly available and reproducible code, exemplarily demonstrates the improvement of the backscatter signal in a mountainous area of the Austrian Alps. Furthermore, suggestions for specific use cases are discussed and drawbacks of the method with respect to pixel-area based methods are highlighted. The radiometrically corrected radar backscatter products are overcoming current limitations and are compliant with recent CEOS specifications for SAR backscatter over land. This improves a wide range of potential usage scenarios of the Google Earth Engine platform in mapping various land surface parameters with Sentinel-1 on a large scale and in a rapid manner. The provision of an openly accessible Earth Engine module allows users a smooth integration of the routine into their own workflows.

Keywords: radiometric slope correction; Google Earth Engine; Sentinel-1; Analysis-Ready-Data