To address the limitations of conventional methods for monitoring landslide in complex terrains and vegetation-covered areas, this paper proposes an enhanced display and recognition method for landslide hazard based on airborne LiDAR technology. In particular, the construction of a high-precision digital elevation model is adopted in conjunction with various terrain-visualization techniques, such as mountain shadows, slope analysis, red stereo maps, and sky field of view factors. The support vector machine (SVM) model is used to classify fused images and identify landslide-susceptible areas. Experimental results show that this method effectively identifies and enhances the display of landslide hazard areas, and that its accuracy in identifying landslide-susceptible areas based on the SVM is 83.86%. The proposed method not only enhances the visualization of landslide hazard areas but also improves the accuracy in identifying landslide-susceptible areas, thus providing effective technical support for landslide disaster prevention and emergency response.