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Weights of Evidence Method for Landslide Susceptibility Mapping in Takengon, Central Aceh, Indonesia

Pamelaa, Sadisun I.A.b, Arifianti Y.a

a Geological Agency of Indonesia, Bandung, Indonesia
b Faculty of Geological Engineering, Bandung Institute of Technology, Bandung, Indonesia

Abstract

© Published under licence by IOP Publishing Ltd.Takengon is an area prone to earthquake disaster and landslide. On July 2, 2013, Central Aceh earthquake induced large numbers of landslides in Takengon area, which resulted in casualties of 39 people. This location was chosen to assess the landslide susceptibility of Takengon, using a statistical method, referred to as the weight of evidence (WoE). This WoE model was applied to indicate the main factors influencing the landslide susceptible area and to derive landslide susceptibility map of Takengon. The 251 landslides randomly divided into two groups of modeling/training data (70%) and validation/test data sets (30%). Twelve thematic maps of evidence are slope degree, slope aspect, lithology, land cover, elevation, rainfall, lineament, peak ground acceleration, curvature, flow direction, distance to river and roads used as landslide causative factors. According to the AUC, the significant factor controlling the landslide is the slope, the slope aspect, peak ground acceleration, elevation, lithology, flow direction, lineament, and rainfall respectively. Analytical result verified by using test data of landslide shows AUC prediction rate is 0.819 and AUC success rate with all landslide data included is 0.879. This result showed the selective factors and WoE method as good models for assessing landslide susceptibility. The landslide susceptibility map of Takengon shows the probabilities, which represent relative degrees of susceptibility for landslide proneness in Takengon area.

Author keywords

Analytical results,Earthquake disaster,Landslide susceptibility,Landslide susceptibility mapping,Peak ground acceleration,Selective factors,Weight of evidences (WoE),Weights of evidences

Indexed keywords

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DOI