Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/1821
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dc.contributor.authorallStramondo, S.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Roma1, Roma, Italiaen
dc.contributor.authorallBignami, C.; Department of Electronic Engineering, University La Sapienzaen
dc.contributor.authorallChini, M.; Department of Physics, University of Bolognaen
dc.contributor.authorallPierdicca, N.; Department of Electronic Engineering, University La Sapienzaen
dc.contributor.authorallTertulliani, A.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Roma1, Roma, Italiaen
dc.date.accessioned2006-10-18T07:16:58Zen
dc.date.available2006-10-18T07:16:58Zen
dc.date.issued2006-10-20en
dc.identifier.urihttp://hdl.handle.net/2122/1821en
dc.description.abstractIn case of a seismic event, a fast and draft damage map of the hit urban areas can be very useful, in particular when the epicentre of the earthquake is located in remote regions, or the main communication systems are damaged. Our aim is to analyse the capability of remote sensing techniques for damage detection in urban areas and to explore the combined use of radar (SAR) and optical satellite data. Two case studies have been proposed: Izmit (1999; Turkey) and Bam (2003; Iran). Both areas have been affected by strong earthquakes causing heavy and extended damage in the urban settlements close to the epicentre. Different procedures for damage assessment have been successfully tested, either to perform a pixel by pixel classification or to assess damage within homogeneous extended areas. We have compared change detection capabilities of different features extracted from optical and radar data, and analysed the potential of combining measurements at different frequency ranges. Regarding the Izmit case, SAR features alone have reached 70% of correct classification of damaged areas and 5 m panchromatic optical images have given 82%; the fusion of SAR and optical data raised up to 89% of correct pixel‐to‐pixel classification. The same procedures applied to the Bam test case achieved about 61% of correct classification from SAR alone, 70% from optical data, while data fusion reached 76%. The results of the correlation between satellite remote sensing and ground surveys data have been presented by comparing remotely change detection features averaged within homogeneous blocks of buildings with ground survey data.en
dc.format.extent807089 bytesen
dc.format.mimetypeapplication/pdfen
dc.language.isoEnglishen
dc.publisher.nameTaylor & Francisen
dc.relation.ispartofInternational Journal of Remote Sensingen
dc.relation.ispartofseries20/27 (2006)en
dc.subjectInSARen
dc.subjectdamage detectionen
dc.subjectOptical dataen
dc.subjectUrban areasen
dc.titleSatellite radar and optical remote sensing for earthquake damage detection: results from different case studiesen
dc.typearticleen
dc.description.statusPublisheden
dc.type.QualityControlPeer-revieweden
dc.description.pagenumber4433 - 4447en
dc.identifier.URLhttp://www.journalsonline.tandf.co.uk/openurl.asp?genre=article&issn=0143-1161&volume=27&issue=20&spage=4433en
dc.subject.INGV04. Solid Earth::04.03. Geodesy::04.03.06. Measurements and monitoringen
dc.subject.INGV04. Solid Earth::04.03. Geodesy::04.03.07. Satellite geodesyen
dc.subject.INGV04. Solid Earth::04.03. Geodesy::04.03.09. Instruments and techniquesen
dc.subject.INGV04. Solid Earth::04.06. Seismology::04.06.06. Surveys, measurements, and monitoringen
dc.subject.INGV04. Solid Earth::04.06. Seismology::04.06.11. Seismic risken
dc.identifier.doi10.1080/01431160600675895en
dc.contributor.affiliationIstituto Nazionale di Geofisica e Vulcanologiaen
dc.description.fulltextpartially_openen
dc.contributor.authorStramondo, S.en
dc.contributor.authorBignami, C.en
dc.contributor.authorChini, M.en
dc.contributor.authorPierdicca, N.en
dc.contributor.authorTertulliani, A.en
dc.contributor.departmentIstituto Nazionale di Geofisica e Vulcanologia, Sezione Roma1, Roma, Italiaen
dc.contributor.departmentDepartment of Electronic Engineering, University La Sapienzaen
dc.contributor.departmentDepartment of Electronic Engineering, University La Sapienzaen
dc.contributor.departmentIstituto Nazionale di Geofisica e Vulcanologia, Sezione Roma1, Roma, Italiaen
item.openairetypearticle-
item.cerifentitytypePublications-
item.languageiso639-1en-
item.grantfulltextrestricted-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextWith Fulltext-
crisitem.author.deptIstituto Nazionale di Geofisica e Vulcanologia (INGV), Sezione ONT, Roma, Italia-
crisitem.author.deptIstituto Nazionale di Geofisica e Vulcanologia (INGV), Sezione ONT, Roma, Italia-
crisitem.author.deptLuxembourg Institute of Science and Technology (LIST)-
crisitem.author.deptSapienza Università di Roma-
crisitem.author.deptIstituto Nazionale di Geofisica e Vulcanologia (INGV), Sezione Roma1, Roma, Italia-
crisitem.author.orcid0000-0003-0163-7647-
crisitem.author.orcid0000-0002-8632-9979-
crisitem.author.orcid0000-0002-3746-0858-
crisitem.author.parentorgIstituto Nazionale di Geofisica e Vulcanologia-
crisitem.author.parentorgIstituto Nazionale di Geofisica e Vulcanologia-
crisitem.author.parentorgIstituto Nazionale di Geofisica e Vulcanologia-
crisitem.classification.parent04. Solid Earth-
crisitem.classification.parent04. Solid Earth-
crisitem.classification.parent04. Solid Earth-
crisitem.classification.parent04. Solid Earth-
crisitem.classification.parent04. Solid Earth-
crisitem.department.parentorgIstituto Nazionale di Geofisica e Vulcanologia-
crisitem.department.parentorgIstituto Nazionale di Geofisica e Vulcanologia-
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