Automatic change detection in multitemporal X- and P-band SAR images using Gram-Schmidt process

Forest monitoring is a major concern today due to climate changes, conservation of fauna and flora and to the lack of water. Therefore, several environmental monitoring techniques have been developed and used to detect changes in the scenes. However, the main techniques have limitations related to weather conditions and does not have the expected effect. The use of SAR seems appropriate to detect changes due to its independence of atmospheric and lighting conditions. This paper will present a new method of change detection in multitemporal SAR imagery using Gram-Schmidt process to do the orthogonalization of the X- and P-band images to calculate a change indicator image. Experimental tests have been conducted using real SAR data obtained by the airborne sensor OrbiSAR-2 from Bradar in the Amazon Forest and the preliminary results showed very good quality detections.