Multi-Temporal Quad-Polarimetric Change Matrix for Agricultural Fields Monitoring

Abstract

In this work, a new way to extract temporal polarimetric information from a stack of co-registered images is presented. This method considers not only polarimetric evolution of consecutive acquisitions but also includes polarimetric changes between every image with respect to the rest of images in the stack. The methodology is tested for different crop types exploiting C-band quad-polarimetric RADARSAT-2 data over rice fields in Seville, South-West of Spain and the Indian Head in Canada as part of the Agrisar 2009 Campaign.