Time Series Analysis of Multi-Polarisation Synthetic Aperture Radar Images with a Textural-Contextual Model

Abstract:
This paper presents a methodology for post-classification change detection of Arctic glaciers from multi-polarimetric synthetic aperture radar (SAR) images. Specifically, an unsupervised contextual non- Gaussian clustering algorithm is used for segmentation of sequences of multi-polarimetric SAR images into glacier facies. Subsequently, the segmented images of succeeding years are compared, and changes are identified as the detected differences in the location of boundaries between glacier facies. In the current analysis, a series of dual polarization C-band Envisat ASAR images over the Kongsvegen glacier, Svalbard, is used for demonstration.