Polsar time series temporal change detection and analysis with binary partition trees
Document typeConference report
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Rights accessRestricted access - publisher's policy
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.
CitationAlonso, A., Lopez, C. Polsar time series temporal change detection and analysis with binary partition trees. A: IEEE International Geoscience and Remote Sensing Symposium. "2013 IEEE International Geoscience & Remote Sensing Symposium: proceedings: July 21–26, 2013: Melbourne, Australia". Melboune: Institute of Electrical and Electronics Engineers (IEEE), 2013, p. 2321-2324.