Quantitative landslide susceptibility mapping at Pemalang area, Indonesia.

摘要: For quantitative landslide susceptibility mapping, this study applied and verified a frequency ratio, logistic regression, artificial neural network models to Pemalang area, Indonesia, using Geographic Information System (GIS). Landslide locations were identified in the area from interpretation of aerial photographs, satellite imagery, field surveys; spatial database was constructed topographic geological maps. The factors that influence occurrence, such as slope gradient, aspect, curvature topography, distance stream, calculated database. Lithology extracted geologic Using these factors, indexes by models. Then maps compared with known locations. regression model (accuracy 87.36%) had higher prediction accuracy than ratio (85.60%) (81.70%) can be used reduce hazards associated landslides land-use planning.