Assessment of landslide susceptibility using multivariate logistic regression: A case study in Southern Japan

Landslides are one of the major hazards in large parts of Japan, especially in hilly and mountainous terrains. To minimize the loss of lives and damage to property, factors causing unstable slope conditions should be understood so that we can determine landslide susceptibility with high accuracy and reliability. The purpose of this study is to evaluate landslide susceptibility using multivariate statistical methods and Geographical Information System (GIS) analyses. The Minamata area of southern Kyushu Island of Japan was chosen for this study. This area has experienced repeated landslide activity, including a disastrous one in July 2003. Within this area, we compiled a landslide inventory using aerial photographs and constructed a geospatial database of geology (lithology), topography, soil, and land use/cover. This study documents the relationship between environmental factors and landslide occurrence. A logistic regression was performed to relate independent variables of lithology, slope gradient, aspect, elevation, soil, and land use/cover, to the absence or presence of landslide deposits and landforms. The derived regression model was adopted to evaluate landslide susceptibility in the study area. The spatial probability of landsliding, categorized as very low, low, medium, and high, is portrayed as a landslide susceptibility map with a 25-m-grid cell resolution.