This study proposes a system for quickly and accurately analyzing suspected landslides without terrain and surface height restrictions. Two satellite images are obtained in the same location but at different times, and the changes in their NDVI (Normalized Difference Vegetation Index) values are analyzed. When large changes occur,image processing methods are employed to detect image territorial variations, and the Faster R-CNN (Region-based Convolutional Neural Network), a deep learning network, is used to determine whether the territorial variation is a landslide. The performance of this system was evaluated using landslide data from the Big Geospatial Information System and the Soil and Water Conservation Bureau, Council of Agriculture; the resulting precision was 92.2 %. The system also outputs the outer contour of the landslide area to facilitate subsequent analysis and application.
Key Words: Landslide, Satellite Image, NDVI, Deep Learning Neural Network.