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dc.contributor.authorNajafi, Amir
dc.contributor.authorHasanlou, Hasan
dc.contributor.authorAkbari, Vahid
dc.date.accessioned2023-09-08T11:36:07Z
dc.date.available2023-09-08T11:36:07Z
dc.date.issued2017-09-27
dc.description.abstractMonitoring and surveillance changes around the world need powerful methods, so detection, visualization, and assessment of significant changes are essential for planning and management. Incorporating polarimetric SAR images due to interactions between electromagnetic waves and target and because of the high spatial resolution almost one meter can be used to study changes in the Earth's surface. Full polarized radar images comparing to single polarized radar images use amplitude and phase information of the surface in different available polarization (HH, HV, VH, and VV). This study is based on the decomposition of full polarized airborne UAVSAR images and integration of these features with algebra method involves Image Differencing (ID) and Image Ratio (IR) algorithms with the mathematical nature and distance-based method involves Canberra (CA) and Euclidean (ED) algorithms with measuring distance between corresponding vector and similarity-based method involves Taminoto (TA) and Kulczynski (KU) algorithms with dependence corresponding vector for change detecting purposes on two real PolSAR datasets. Assessment of incorporated methods is implemented using ground truth data and different criteria for evaluating such as overall accuracy (OA), area under ROC curve (AUC) and false alarms rate (FAR). The output results show that ID, IR, and CA have superiority to detect changes comparing to other implemented algorithms. Also, numerical results show that the highest performance in two datasets has OA more than 90%. In other assessment criteria, mention algorithms have low FAR and high AUC value indices to detect changes in PolSAR images.en_US
dc.identifier.cristinIDFRIDAID 1505153
dc.identifier.doi10.5194/isprs-archives-XLII-4-W4-195-2017
dc.identifier.issn1682-1750
dc.identifier.issn2194-9034
dc.identifier.urihttps://hdl.handle.net/10037/30843
dc.language.isoengen_US
dc.publisherInternational Society of Photogrammetry and Remote Sensing (ISPRS)en_US
dc.relation.journalInternational Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright © The Author(s) 2017en_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0en_US
dc.rightsAttribution 4.0 International (CC BY 4.0)en_US
dc.titleLand cover changes detection in polarimetric SAR data using algebra, similarity and distance based methodsen_US
dc.type.versionpublishedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US


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Attribution 4.0 International (CC BY 4.0)
Except where otherwise noted, this item's license is described as Attribution 4.0 International (CC BY 4.0)