Landslide susceptibility mapping using shallow neural networks model at refahiye district in turkey

dc.contributor.authorAbujayyab, Sohaib K M
dc.contributor.authorKaras, İsmail Rakip
dc.date.accessioned2024-09-29T16:32:20Z
dc.date.available2024-09-29T16:32:20Z
dc.date.issued2020
dc.departmentKarabük Üniversitesien_US
dc.description.abstractLandslides represent a continuous hazard for population and infrastructure. Mapping the landslide susceptibility is an essential issue to avoid the landslides risks. The aim of this paper is to produce a high-accuracy model for landslide susceptibility mapping in Refahiye district in Turkey. The model employed shallow neural networks for landslide susceptibility mapping, while bivariate spearman correlation test was utilized to select the related factors to extract the appropriate data and reduce the computation time of training and mapping. 12 out of 21 spatial factors were selected as relevant factors using Spearman correlation test. Relevant factors are geology, distance from roads, distance from geological faults, distance from water streams, flow direction, aspect, hillshade, heat load index, slope/aspect transformation, site exposure index, compound topographic index, and elevation. The generated dataset was divided into training, validation, and testing datasets using 10-folds cross-validation method. The TrainIm was found to be the best training function with an overall accuracy of 86.3%. The developed NN model was tested using IRIS benchmark dataset and showed higher performance against the logistic regression algorithm. As a result, shallow neural networks method was successfully applied in landslide susceptibility mapping in this study and the method is recommended for future studies.en_US
dc.identifier.endpage77en_US
dc.identifier.issue2en_US
dc.identifier.startpage61en_US
dc.identifier.trdizinid496049en_US
dc.identifier.urihttps://search.trdizin.gov.tr/tr/yayin/detay/496049
dc.identifier.urihttps://hdl.handle.net/20.500.14619/11545
dc.identifier.volume1en_US
dc.indekslendigikaynakTR-Dizinen_US
dc.language.isoenen_US
dc.relation.ispartofTürk Uzaktan Algılama ve CBS Dergisien_US
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.titleLandslide susceptibility mapping using shallow neural networks model at refahiye district in turkeyen_US
dc.typeArticleen_US

Dosyalar