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.
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