Remote Sensing and GIS Approach for Landslide Susceptibility Mapping: A Case Study in Hofu City, Yamaguchi, Japan

Abstract

Landslide is one of the natural hazards that often initiates by the interaction between environmental factors and triggering factor. The identi?cation of areas where landslides are likely to occur is important for the reduction of potential damage. This study utilizes remote sensing data and Geographic Information System (GIS) to identify areas where landslides are likely to occur and generates landslide susceptibility map based on logistic regression model. The study area is located in Hofu city, Yamaguchi prefecture, Japan. The data that were used in this study are satellite imagery from ALOS AVNIR-2, elevation and geology data from GSI, Rainfall data from AMEDAS, and landslide inventory map provided from Ministry of Land, Infrastructure, Transportation and Tourism. The result from this study revealed that elevation from > 50 to < 350 m, slope angle from> 5° to < 50°, slope direction of north and northeast, land cover of agriculture, urban, bare soil, and forest, and lithology of graniodorite, fan deposits, and middle terrace are favorable for landslide occurrence. The landslide susceptiility map showed that 98% of the result calculations of logistic regression are similar to the historical data of landslide event which is among 911 landslide points, 899 points were existed in high and very high susceptibility areas.