Polarimetric Decomposition for Monitoring Crop Growth Status

This letter investigates the polarimetric decomposition for monitoring the crop growth status over agricultural fields. Based on an existing polarimetric decomposition, the vegetation volume scattering component is removed from the full polarimetric synthetic aperture radar (SAR). Then, the estimated crop orientation is combined with the dominant scattering mechanism in the remaining ground coherency matrix to define the vegetation growth indicators for the crop growth monitoring from SAR. The proposed method is evaluated on the time series of Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) data and the extensive ground truth measurements collected in the framework of the Soil Moisture Active Passive (SMAP) Validation Experiment in 2012. The results show that the scattering characteristics vary with the crop types and the phenological development stage. The random orientation is the most important case during the crop development period considered in this letter. For canola, corn, and wheat, the dihedral scattering is significant in the remaining ground coherency matrix at the early growth stage, and then, the surface scattering becomes important in the further growth. For soybean and pasture, the surface scattering dominates the remaining ground coherency matrix during the considered crop development stage. The vegetation growth indicators derived from UAVSAR data are well correlated with the ground measurements of crop height and biomass. This letter demonstrates, for the first time, the crop growth monitoring by using polarimetric decomposition via the vegetation orientation and scattering mechanisms.