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dc.contributor.authorAteş, Hasan Fehmien_US
dc.contributor.authorKahraman, Fatihen_US
dc.contributor.authorİmamoğlu, Müminen_US
dc.date.accessioned2016-10-24T17:24:41Z
dc.date.available2016-10-24T17:24:41Z
dc.date.issued2016-08
dc.identifier.citationKahraman, F., İmamoğlu, M. & Ateş, H. F. (2016). Disaster damage assessment of buildings using adaptive self-similarity descriptor. IEEE Geoscience and Remote Sensing Letters, 13(8), 1188-1192. doi:10.1109/LGRS.2016.2574960en_US
dc.identifier.issn1545-598X
dc.identifier.issn1558-0571
dc.identifier.otherWOS:000382683100031
dc.identifier.urihttps://hdl.handle.net/11729/1129
dc.identifier.urihttp://dx.doi.org/10.1109/LGRS.2016.2574960
dc.description.abstractAssessment of damage caused by a disaster is significant for coordinating emergency response teams and planning emergency aid. In this letter, a robust method for rapid building damage assessment is proposed using pre- and postevent EO images and building footprints. The method uses a local self-similarity descriptor (SSD) for change detection in buildings, which is shown to be robust against variations in global illumination and small local deformations. The use of building footprints helps reduce the false alarms due to changes in nonbuilding areas. Footprint is also used to differentiate small and large buildings, extract the boundary region of a building, and adapt the descriptor computation accordingly. It is shown that the adaptive SSD provides a more accurate measure of local damage on the building. The 2010 Haiti Earthquake and Typhoon Haiyan 2013 Philippines are analyzed with the proposed method, and 75/82% true positive rate and 25/15% false positive rate are obtained for detection of collapsed buildings with respect to the ground truth data of UNITAR/UNOSAT and HOT.en_US
dc.description.sponsorshipThis work was supported in part by the Republic of Turkey Prime Ministry Disaster and Emergency Management Presidency (AFAD) and TUBITAK BILGEM under Grant B740-G585000en_US
dc.language.isoengen_US
dc.relation.isversionof10.1109/LGRS.2016.2574960
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectAdaptive self-similarity descriptoren_US
dc.subjectBuilding damage detectionen_US
dc.subjectChange detectionen_US
dc.subjectRapid damage assessmenten_US
dc.subjectRemote sensingen_US
dc.subjectEarthquakeen_US
dc.titleDisaster damage assessment of buildings using adaptive self-similarity descriptoren_US
dc.typearticleen_US
dc.description.versionPublisher's Versionen_US
dc.relation.journalIEEE Geoscience and Remote Sensing Lettersen_US
dc.contributor.departmentIşık Üniversitesi, Mühendislik Fakültesi, Elektrik-Elektronik Mühendisliği Bölümüen_US
dc.contributor.departmentIşık University, Faculty of Engineering, Department of Electrical-Electronics Engineeringen_US
dc.contributor.authorID0000-0002-6842-1528
dc.identifier.volume13
dc.identifier.issue8
dc.identifier.startpage1188
dc.identifier.endpage1192
dc.peerreviewedYesen_US
dc.publicationstatusPublisheden_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.contributor.institutionauthorAteş, Hasan Fehmien_US


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