Polsar time series temporal change detection and analysis with binary partition trees

In this paper the exploitation of PolSAR temporal series datasets is presentedin the context of change detection and characterization. A Binary Partition Tree (BPT) data structure is employed in order to extract homogeneous regions of the image containing pixels that are following a similar polarimetric temporal evolution. Then the temporal dimension of the data is analyzed firstly to quantify the significance of the polarimetric temporal variation, making possible the detection of scene changes, and secondly to analyze and characterize those changes. Finally, the proposed technique is employed to process a real RADARSAT-2 dataset to show its capabilities and potentialities.