Comprehensive landslide hazard assessment using spatial, temporal and size probabilities combined with landslide density analysis in Canakkale (NW Turkiye)

dc.contributor.authorBerber, Samet
dc.contributor.authorCeryan, Sener
dc.contributor.authorErcanoglu, Murat
dc.date.accessioned2025-07-03T21:26:41Z
dc.date.issued2025
dc.departmentBalıkesir Üniversitesi
dc.description.abstractTo assess the landslide hazard (LH) of the area between Lapseki and Guzelyal & imath; (C,anakkale, NW Turkiye) the LH map and the landslide density hazard map were produced. The LH maps produced in this study were calculated by multiplying the spatial probability, size probability, and temporal probability. The landslide susceptibility (LS) map was produced using the Random Forest method. While producing the LS map, elevation, land use, curvature, lithology, NDVI, distance to streams, slope, TWI, and aspect were used as input parameters. The rainfall triggering landslides was obtained as 220 mm. Using Gumbel distribution, the exceedance probability of the 220 mm rainfall value in 5, 10, 25, and 50 years were calculated as 0.453, 0.701, 0.951, and 0.997, respectively. The probability of occurrence of a landslide that is equal to or greater than a selected area was found using landslide frequency-area distribution. The probability of a landslide in the study area, surpassing an area of 0.1 km2, an area of 0,35 km2, and an area of 1 km2, with corresponding probabilities of 0.701, 0,361, and 0.184, respectively. To solve questions about where and how densely potential landslides will occur at a given time, a landslide density hazard map was produced. The Landslide density hazard map was calculated from the spatial probability, landslide density, and temporal probability. It was seen in this study that the landslide hazard concept should be considered by the decision makers for the future works such as land-use management and urban development strategies. (c) 2025 COSPAR. Published by Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
dc.description.sponsorshipScientific Research Projects Unit of Balikesir University [2022/063]; Balikesir University
dc.description.sponsorshipThis research was financially supported by the Scientific Research Projects Unit of Balikesir University (Project No: 2022/063) . The authors thank Balikesir University for their support to conduct this work.
dc.identifier.doi10.1016/j.asr.2025.04.048
dc.identifier.endpage188
dc.identifier.issn0273-1177
dc.identifier.issn1879-1948
dc.identifier.issue1
dc.identifier.scopus2-s2.0-105004285472
dc.identifier.scopusqualityQ1
dc.identifier.startpage170
dc.identifier.urihttps://doi.org/10.1016/j.asr.2025.04.048
dc.identifier.urihttps://hdl.handle.net/20.500.12462/21851
dc.identifier.volume76
dc.identifier.wosWOS:001507159500002
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherElsevier Sci Ltd
dc.relation.ispartofAdvances in Space Research
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20250703
dc.subjectLandslide hazard
dc.subjectLandslide density
dc.subjectProbability
dc.subjectRandom Forest
dc.subjectC , anakkale
dc.titleComprehensive landslide hazard assessment using spatial, temporal and size probabilities combined with landslide density analysis in Canakkale (NW Turkiye)
dc.typeArticle

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