Research Projects

Accurate crop monitoring is crucial for sustainable food security and improving farming practices. Previous studies have shown that fully polarimetric synthetic Aperture Radar (sAR) data can provide better information on crop scattering mechanisms, leading to more accurate crop monitoring at high spatial and temporal resolutions. However, previous algorithms have limitations in characterizing the different order of scattering from crops, which vary across different crop types and growth stages. The high levels of heterogeneity in farming practices in India make it challenging to apply polarimetry for crop monitoring. To address these limitations, further research is needed to develop advanced sAR-based algorithms that account for varying scattering mechanisms across different crops and growth stages, and to account for the high levels of heterogeneity in farming practices in India. The proposed project focuses on developing and utilizing a new Radar Vegetation Index (RVI) using fully polarized synthetic Aperture Radar (sAR) data for crop monitoring. This project aims to address the challenges posed by the heterogeneity of the field and make crop monitoring more efficient and accurate.