Monitoring Agricultural Fields Using an Optimisation of the Difference of Covariance Matrices for Polsar

Abstract

SAR polarimetry (PolSAR) can play an important role in monitoring agricultural fields both in terms of improving detection of specific plants conditions and providing physical information regarding the change. Such information can be used to help retrieving the phenological stage and eventually identifying stress conditions. In this work, a new change detection based on PolSAR data is first tested over time series of images acquired over agricultural fields. The methodology is based on the use of the normalised difference between covariance matrices acquired at two different instants. A diagonalisation of such matrix allows identifying the scattering mechanisms that suffer the largest change. The methodology is tested exploiting C-band quad-polarimetric RADARSAT-2 data over rice fields in Sevilla, South-West of Spain.