Development of a Web-Based Analytical Framework for Soil Moisture Estimation Using Multipolarized SAR Data

Abstract. This study developed a novel framework to estimate and visualize soil moisture using KOMPSAT-5 synthetic aperture radar (SAR) data in a real-time web-based environment. We investigated two approaches: one combining NDWI derived from KOMPSAT-3A optical data with SAR backscatter, and another relying solely on the Radar Vegetation Index (RVI) computed from KOMPSAT-5 dual-polarized imagery. Through a modified Water Cloud Model (WCM), we compared the two methods against ground-truth measurements in wheat fields located in the Wimmera region of Australia. Results showed that both NDWI+SAR and RVI+SAR achieved similar levels of accuracy (R2 ranging from 0.6865 to 0.6951), suggesting that a SAR-only approach can be a valid alternative when optical data are unavailable or affected by atmospheric conditions. Our integrated web system further automates tasks such as SAR preprocessing, vegetation index calculation, and map overlay, enabling users to interpret soil moisture trends and dynamic changes over time with minimal effort. Looking ahead, future satellites such as KOMPSAT-6, providing higher resolution and full polarization data, may enhance the performance of SAR-only models. This study thereby demonstrates a scalable and practical solution for soil moisture monitoring and broader agricultural or environmental applications.