Identification of landslide area using remote sensing data and quantitative assessment of landslide hazard

This paper discusses the application of remote sensing techniques and GIS-based prediction modeling for landslide hazard mapping. First, we aim at identifying the past landslide locations by comparing various remote sensing data (KOMPSAT EOC, IRS, SPOT). Using the detected landslides locations and spatial database, probabilistic prediction model based on likelihood ratio function is constructed to generate a prediction map for landslide hazard mapping. After generating the prediction results, to provide the measures of significance of prediction results, a validation of the prediction results is carried out. Through the validation procedure, the prediction results can provide meaningful interpretation with respect to the future landslides. A case study from Jangheung area in Korea is carried out to illustrate above schemes.