Please use this identifier to cite or link to this item: https://ktisis.cut.ac.cy/handle/10488/9302
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dc.contributor.authorFranci, Francesca-
dc.contributor.authorBitelli, Gabriele-
dc.contributor.authorMandanici, Emanuele-
dc.contributor.authorHadjimitsis, Diofantos G.-
dc.contributor.authorAgapiou, Athos-
dc.contributor.otherΧατζημιτσής, Διόφαντος-
dc.contributor.otherΑγαπίου, Άθως-
dc.date.accessioned2017-01-30T12:24:50Z-
dc.date.available2017-01-30T12:24:50Z-
dc.date.issued2016-10-01-
dc.identifier.citationNatural Hazards, 2016, vol. 83, pp. 31-51en_US
dc.identifier.issn0921-030X-
dc.description.abstractThis work focuses on the exploitation of very high-resolution (VHR) satellite imagery coupled with multi-criteria analysis (MCA) to produce flood hazard maps. The methodology was tested over a portion of the Yialias river watershed basin (Nicosia, Cyprus). The MCA methodology was performed selecting five flood-conditioning factors: slope, distance to channels, drainage texture, geology and land cover. Among MCA methods, the analytic hierarchy process technique was chosen to derive the weight of each criterion in the computation of the flood hazard index (FHI). The required information layers were obtained by processing a VHR GeoEye-1 image and a digital elevation model. The satellite image was classified using an object-based technique to extract land use/cover data, while GIS geoprocessing of the DEM provided slope, stream network and drainage texture data. Using the FHI, the study area was finally classified into seven hazard categories ranging from very low to very high in order to generate an easily readable map. The hazard seems to be severe, in particular, in some urban areas, where extensive anthropogenic interventions can be observed. This work confirms the benefits of using remote sensing data coupled with MCA approach to provide fast and cost-effective information concerning the hazard assessment, especially when reliable data are not available.en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.publisherSpringer Netherlandsen_US
dc.relation.ispartofNatural Hazardsen_US
dc.rights© Springer Natureen_US
dc.subjectAnalytic hierarchy processen_US
dc.subjectFlood hazarden_US
dc.subjectGeoEye-1en_US
dc.subjectObject-based classificationen_US
dc.subjectYialias riveren_US
dc.titleSatellite remote sensing and GIS-based multi-criteria analysis for flood hazard mappingen_US
dc.typeArticleen_US
dc.collaborationUniversity of Bolognaen_US
dc.collaborationCyprus University of Technologyen_US
dc.subject.categoryEarth and Related Environmental Sciencesen_US
dc.journalsSubscriptionen_US
dc.countryItalyen_US
dc.countryCyprusen_US
dc.subject.fieldNatural Sciencesen_US
dc.publicationPeer Revieweden_US
dc.identifier.doi10.1007/s11069-016-2504-9en_US
dc.relation.volume83en_US
cut.common.academicyear2016-2017en_US
dc.identifier.spage31en_US
dc.identifier.epage51en_US
item.languageiso639-1en-
item.grantfulltextnone-
item.cerifentitytypePublications-
item.openairetypearticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.fulltextNo Fulltext-
crisitem.author.deptDepartment of Civil Engineering and Geomatics-
crisitem.author.deptDepartment of Civil Engineering and Geomatics-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.orcid0000-0002-2684-547X-
crisitem.author.orcid0000-0001-9106-6766-
crisitem.author.parentorgFaculty of Engineering and Technology-
crisitem.author.parentorgFaculty of Engineering and Technology-
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