In this study, a semi-automatic landslide classification method is proposed and implemented using both airborne LiDAR data and color aerial photographs. A man-machine interface is implemented with three-dimensional perspective display capability, thus to ease the manual interpretation and editing after a preliminary result of landslide polygons are generated by an automatic algorithm proposed in this study. Four parameters are used in the automatic algorithm, namely Greenness, Slope, OHM and Roughness. Greenness is derived from color aerial photograph and employed to define non-vegetated land of fresh scars of shallow-seated landslides. All the other tree parameters are derived from LiDAR DSM and DEM to portray the geomorphometric characteristics of landslides. Thresholds are derived automatically from training areas and then are applied in real time to show the distribution of possible landslides. With the 3D interactive interface, the possible landslides are draped on 3D perspective landscape on the screen. This is convenient to assist the human expert to further modify the results by deleting erroneous ones or modify the boundaries of landslides visually. In addition, the interface system can go without the semi-automatic approach and just be used for visual interpretation solely on basis of the expert knowledge of feature locations, shapes, and types of landslides. Attribute table linked with the landslide spatial feature can also be established in this system. It is proved in this study that this is a practical and efficient system.