Development of surface soil moisture (SSM) retrieval algorithm using multi-temporal sentinel-1 C band SAR data

Abstract

Soil Moisture is a crucial component for farmers, disaster management units, and meteorologists. Here, I present an algorithm to estimate surface soil moisture (SSM) from ESA’s Sentinel-1 satellite-carrying C-band SAR(CSAR) sensors and providing the most abundant and freely available SAR data so far with unprecedented spatiotemporal coverage. The method bases on the interpretation of S-1 data of GRD product type, recorded in the VV polarisation with IW sensor mode. The proposed algorithm is based on Change Detection(CD) Method and provides a Soil Moisture Change(SMC) or Change detection Index(CDI) with a spatial resolution of 500m. The algorithm formulates in time-series domain using data cube architecture and high-performance computing environments. The algorithm relies on the difference between backscattered Sentinel-1 radar signals in VV polarisation. We have applied the method to one year of satellite data(January 2018 - December 2018) of Anand district, Gujarat. It does not require any site calibrations and applies to any vegetation-covered areas for which time-series SAR C-band data is available.