Crop Growth Assessment Using Sentinel-1 GRD SAR Descriptors

Accurate and high-resolution spatio-temporal information on crop growth is an essential factor for agronomic management and grain yield estimation. Dual polarimetric Synthetic Aperture Radar (SAR) on board Sentinel-1 is an effective way for crop mapping and monitoring from space independent of weather conditions. However, crop growth monitoring studies seldom exploit complete polarimetric information in dual-pol Ground Range Detected (GRD) SAR data. This study analyses the recently proposed dual polarimetric descriptors (viz., the pseudo scattering entropy Hc, the co-pol purity parameter mc, and the pseudo scattering-type parameter θc) from GRD SAR data for crop growth assessment. The analysis of these descriptors is carried out over a time series of Sentinel-1 data for a winter crop (wheat) and a summer crop (potato) at a test site in Germany. The algorithm is implemented on the Google Earth Engine (GEE) cloud platform for Sentinel-1 SAR data. From the leaf development stage to the flowering stage for both crops, the θc changes by approximately 10° to 17°. Within the entire phenology window, both mc and Hc varies by about 0.4 to 0.6. These descriptors are highly sensitive to crop growth dynamics. The cloud-based implementation of the proposed method has the potential for operational scale monitoring applications at global scale.