4.6 Article

Landslide susceptibility assessment using frequency ratio model in Bogor, West Java, Indonesia

Journal

GEOSCIENCE LETTERS
Volume 6, Issue 1, Pages -

Publisher

SPRINGEROPEN
DOI: 10.1186/s40562-019-0140-4

Keywords

Landslides; Hazard mapping; Geographic Information Systems (GIS); Spatial analysis; Frequency ratio (FR); Area Under a Curve (AUC)

Funding

  1. Ministry of Research, Technology and Higher Education of Indonesia through RISET-PRO scholarship 2017 [264/RISET-Pro/FGS/VIII/2017]

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Landslides are common natural disasters in Bogor, Indonesia, triggered by a combination of factors including slope aspect, soil type and bedrock lithology, land cover and land use, and hydrologic conditions. In the Bogor area, slopes with volcanic lithologies are more susceptible to failure. GIS mapping and analysis using a Frequency Ratio Model was implemented in this study to assess the contribution of conditioning factors to landslides, and to produce a landslide susceptibility map of the study area. A landslide inventory map was prepared from a database of historic landslides events. In addition, thematic maps (soil, rainfall, land cover, and geology map) and Digital Elevation Model (DEM) were prepared to examine landslide conditioning factors. A total of 173 landslides points were mapped in the area and randomly subdivided into a training set (70%) with 116 points and test set with 57 points (30%). The relationship between landslides and conditioning factors was statistically evaluated with FR analysis. The result shows that lithology, soil, and land cover are the most important factors generating landslides. FR values were used to produce the Landslide Susceptibility Index (LSI) and the study area was divided into five zones of relative landslide susceptibility. The result of landslide susceptibility from the mid-region area of Bogor to the southern part was categorized as moderate to high landslide susceptibility zones. The results of the analysis have been validated by calculating the Area Under a Curve (AUC), which shows an accuracy of success rate of 90.10% and an accuracy of prediction rate curve of 87.30%, which indicates a high-quality susceptibility map obtained from the FR model.

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