Comparison of two landslide hazard zonation methods in the volcanic terrain of Temanggung Regency, Central Java, Indonesia

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Abstract

Landslides are a recurring phenomenon that disrupts the natural environment and causes yearly property damage, economic losses, and fatalities. The damage is expected to increase due to deforestation rates, population growth, agriculture, slope-building infrastructure expansion, and global climate change. This study assesses the susceptibility to landslides through Weight of Evidence (WoE) and Frequency Ratio (FR) methods in the Temanggung Regency, Central Java Province, Indonesia, that located on the slopes of two active volcanoes. Initially, a landslide record and the input parameters of the landslide controlling factors were prepared from field surveys, remote sensing data, and secondary data and processed by a geographic information system (GIS). Six landslide parameters in thematic layer maps were selected to develop landslide susceptibility: slope, lithology type, geological structure density, land cover, and rainfall. According to the WoE and FR models, a landslide susceptibility zoning map was classified into four landslide-prone zones from low to very high. Finally, the success and predictive rate curves method confirmed the landslide susceptibility maps to check the model accuracy. The results showed that the landslide susceptibility map using the WoE method had better accuracy than the FR method, with a success rate of 78.48% and a prediction rate of 81.1%. In comparison, the FR method was 74.53% for the success rate and 78.48% for the prediction rate. These landslide susceptibility maps can be used as a guideline to develop land-use planning and landslide disaster mitigation.

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APA

Wilopo, W., Putra, D. P. E., Fathani, T. F., Pramaditya, A., Tandirerung, R., & Erzagian, E. (2023). Comparison of two landslide hazard zonation methods in the volcanic terrain of Temanggung Regency, Central Java, Indonesia. Journal of Degraded and Mining Lands Management, 10(3), 4537–4546. https://doi.org/10.15243/jdmlm.2023.103.4537

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