Monitoring Irrigation Events and Crop Dynamics Using Sentinel-1 and Sentinel-2 Time Series

Capturing and identifying field-based agricultural activities, such as the start, duration end of irrigation, together with crop sowing/germination, growing period time harvest, offer informative metrics that can assist in precision activities addition to broader water food security monitoring efforts. While optically based band-ratios, normalized difference vegetation index (NDVI) (NDWI), have been used descriptors for dynamics, data are not always available due influence clouds other atmospheric effects on optical sensors. Satellite-based microwave systems, synthetic aperture radar (SAR), an all-weather advantage soil conditions. In this paper, we leverage relative strengths both optical- microwave-based approaches by combining high resolution Sentinel-1 SAR Sentinel-2 imagery monitor irrigation events dynamics a dryland landscape. A backscatter model was analyze responses simulated backscatters moisture, NDVI NDWI (both correlated content be regarded descriptors), allowing empirical relationship between these two platforms. correlation analysis also performed using over crops maize, alfalfa, carrot Rhodes grass Al Kharj farm Saudi Arabia identify appropriate SAR-based descriptor. The results illustrate demonstrated cross-polarization ratio (VH/VV) indices. We explore capacity multi-platform multi-sensor approach inform spatio-temporal range which facilitate management decisions.