Analysis on the relation between statistical similarity measures and agricultural parameters: A case study

Polarimetric Synthetic Aperture Radar (PolSAR) images are widely used for agricultural fields monitoring and change detection applications due to their all-weather acquisition possibilities and inherent properties including phase and amplitude information. The techniques used for such temporal applications can be cast in two groups: polarimetric (incoherent) and polarimetric-interferometric (coherent) being represented in this work by the KL-distance and the Mutual Information, respectively. The goal of this work is to characterize these two kinds of different information sources in terms of ground measurement parameters of the agricultural fields, and to figure out the relationship between temporal trends of the similarity measures versus temporal trends of the physical parameters without dealing with inverse problems. For this purpose multi-temporal fully polarimetric SAR images, acquired in the frame of the AgriSAR 2006 campaign with synchronous ground surface measurements over a whole vegetation period are analyzed.