Publication:
Landslide susceptibility mapping using analytical hierarchy process and geographical information system in rudny altai region, East Kazakhstan

dc.contributor.authorZhanabayev, Dauren
dc.contributor.authorDzhanaleeva, Kulchikhan
dc.contributor.authorEfe, Recep
dc.contributor.buuauthorATASOY, EMİN
dc.contributor.departmentTürkçe ve Sosyal Bilimler Eğitimi Ana Bilim Dalı.
dc.contributor.departmentEğitim Fakültesi
dc.contributor.orcid0000-0002-6210-4193
dc.contributor.researcheridIUO-7258-2023
dc.date.accessioned2025-02-14T07:19:26Z
dc.date.available2025-02-14T07:19:26Z
dc.date.issued2024-03-01
dc.description.abstractLandslides are one of the important natural threats that often cause loss of life and property in Kazakhstan. One of the regions affected by landslides of different types and sizes that occur for different reasons in the country is the Rudny Altay Region in the east of Kazakhstan. This study deals with the landslide susceptibility assessment using remote sensing methods in Rudny Altai region of East Kazakhstan. The landslide inventory map was created based on historical information, remote sensing images, and field surveys. Images of 4 selected sites (Tikhaya, Berezovka, Manat and Chernovaya) were examined to determine potential landslide susceptibility. In combined Analytical Hierarchy Process method and GIS (AHP-GIS) used in this study, values are assigned to the selected indicators (layers) from low to high landslide susceptibility potential (1-5). Thus, to assess the potential of landslide processes, the following indicators were selected: calculated values of surface slope according to the NASADEM digital elevation model, soil density, average monthly precipitation OpenLandMap, and median values of the normalized difference vegetation index (NDVI). As a result, the data were obtained and maps of landslide susceptibility of the study areas were created. According to the research results, the highest coefficient of damage to the area by landslide processes is noted in Tikhaya, and the lowest - in Manat. On average, the coefficient of landslide damage in the Rudny Altai area is 0.03, which is a low indicator for this region. The results obtained with the study showed that about 25% of the study area had moderate to high landslide susceptibility. Accordingly, landslide susceptibility is high in the southwest and south of the study area, especially in mountainous areas where slopes are steep and in sloping areas in the south. It was revealed that the results obtained in this study are quite successful in determining the landslide susceptibility of the study area. The findings of the study can contribute in the effective management of the Rudny Altai Region.
dc.identifier.doi10.21163/GT_2024.191.11
dc.identifier.endpage165
dc.identifier.issn1842-5135
dc.identifier.issue1
dc.identifier.scopus2-s2.0-85189072719
dc.identifier.startpage151
dc.identifier.urihttps://doi.org/10.21163/GT_2024.191.11
dc.identifier.urihttps://hdl.handle.net/11452/50398
dc.identifier.volume19
dc.identifier.wos001237276400010
dc.indexed.wosWOS.ESCI
dc.language.isoen
dc.publisherGeographia Technica Assoc - Gt Assoc
dc.relation.journalGeographia Technica
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectFrequency ratio
dc.subjectLogistic-regression
dc.subjectModel
dc.subjectGis
dc.subjectNetwork
dc.subjectAhp
dc.subjectAhp
dc.subjectLandslides
dc.subjectSusceptibility mapping
dc.subjectGis
dc.subjectEast kazakhstan
dc.subjectScience & technology
dc.subjectPhysical sciences
dc.subjectGeography, physical
dc.subjectPhysical geography
dc.titleLandslide susceptibility mapping using analytical hierarchy process and geographical information system in rudny altai region, East Kazakhstan
dc.typeArticle
dspace.entity.typePublication
local.contributor.departmentEğitim Fakültesi/Türkçe ve Sosyal Bilimler Eğitimi Ana Bilim Dalı.
local.indexed.atWOS
local.indexed.atScopus
relation.isAuthorOfPublication3faa3407-845a-4ffb-91c9-3b0b5703834e
relation.isAuthorOfPublication.latestForDiscovery3faa3407-845a-4ffb-91c9-3b0b5703834e

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