Semi-automatic shallow landslide detection by the integration of airborne imagery and laser scanning data

Abstract

Landslide mapping is essential for effective watershed management. In Taiwan, a typhoon or earthquake event can trigger hundreds, even thousands, of shallow landslides in mountainous watersheds. Thus, improving the efficiency of landslide mapping by means of remote sensing techniques is an important issue. This study proposes a new method that uses concurrent aerial laser scanning (ALS) data and color ortho-imagery as input data: the topographic indices of slope, surface roughness, and object height model can be derived from the ALS data and the Green–Red Vegetation Index from the ortho-images. The method first uses these topographic and spectral indices in a global, semi-automatic algorithm to separate landslide from non-landslide pixels. It then offers a region growing tool and a 3D Eraser/Painter to edit detected landslides locally. These global and local operations are designed with a user interface, which is intuitive and user-friendly. Results from four test sites in a mountainous watershed prove that the method is easy, accurate, and suitable for landslide mapping in Taiwan.