Morphology estimation of rice fields using X-band PolSAR data

Synthetic Aperture Radar (SAR) remote sensing techniques play a significant role in modern agricultural crop monitoring by relating the plant structure (height, biomass, yield and growth-stage) to the backscattering behavior of the vegetative canopy. The current trend in crop monitoring is towards precision agriculture, which needs detailed morphology information. By predicting the physical structure, one can just determine the under and overgrowth conditions. In this study, we propose a probabilistic inversion algorithm for a Radiative Transfer Theory (RTT) model which relates the backscattering response of a canopy to its physical structure. The outcomes of the inversion provided promising results by estimating the dimensions of the primary structures with a small bias.