Remote sensing and GIS-based landslide susceptibility mapping using frequency ratio and analytical hierarchy methods in Rize province (NE Turkey)

dc.authorid0000-0002-1942-8950
dc.contributor.authorReis, Selçuk
dc.contributor.authorAtasoy, Mustafa
dc.contributor.authorNişancı, Recep
dc.contributor.authorBayrak, Temel
dc.contributor.authorErduran, Murat
dc.contributor.authorSancar, Cenap
dc.contributor.authorEkercin, Semih
dc.date.accessioned2019-07-12T12:27:18Z
dc.date.available2019-07-12T12:27:18Z
dc.date.issued2012
dc.departmentMühendislik Fakültesi
dc.description.abstractThe northeast part of Turkey is prone to landslides because of the climatic conditions, as well as geologic and geomorphologic characteristics of the region. Especially, frequent landslides in the Rize province often result in significant damage to people and property. Therefore, in order to mitigate the damage from landslides and help the planners in selecting suitable locations for implementing development projects, especially in large areas, it is necessary to scientifically assess susceptible areas. In this study, the frequency ratio method and the analytical hierarchy process (AHP) were used to produce susceptibility maps. Especially, AHP gives best results because of allowing better structuring of various components, including both objective and subjective aspects and comparing them by a logical and thorough method, which involves a matrix-based pairwise comparison of the contribution of different factors for landslide. For this purpose, lithology, slope angle, slope aspect, land cover, distance to stream, drainage density, and distance to road were considered as landslide causal factors for the study area. The processing of multi-geodata sets was carried out in a raster GIS environment. Lithology was derived from the geological database and additional field studies; slope angle, slope aspect, distance to stream, distance to road and drainage density were invented from digital elevation models; land cover was produced from remote sensing imagery. In the end of study, the results of the analysis were verified using actual landslide location data. The validation results showed satisfactory agreement between the susceptibility map and the existing data on landslide locations.
dc.identifier.doi10.1007/s12665-011-1432-y
dc.identifier.endpage2073en_US
dc.identifier.issn1866-6280
dc.identifier.issue7en_US
dc.identifier.scopusqualityQ1
dc.identifier.startpage2063en_US
dc.identifier.urihttps://dx.doi.org/10.1007/s12665-011-1432-y
dc.identifier.urihttps://hdl.handle.net/20.500.12451/2230
dc.identifier.volume66en_US
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherSpringer Nature
dc.relation.ispartofEnvironmental Earth Sciences
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectLandslide
dc.subjectAHP
dc.subjectStatistical methods
dc.subjectSatellite Imagery
dc.subjectRize
dc.titleRemote sensing and GIS-based landslide susceptibility mapping using frequency ratio and analytical hierarchy methods in Rize province (NE Turkey)
dc.typeArticle

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