Abstract: In order to better meet the needs of geohazard identification in mountainous towns and effectively detect small-sized, medium-sized, and hidden geohazards, a case study was conducted in several typical towns in Xide County, southwest Sichuan. The study employed a comprehensive suite of techniques, including optical remote sensing, InSAR, LiDAR, detailed slope investigation, and high-density resistivity methods, to identify geohazards from various perspectives and levels of precision. The results show that these methods complement each other well and are effective in geohazard identification. A total of 80 occurrences of geohazards were identified, including 29 new identifications, along with 131 potential geohazard dangers. The differences in disaster-inducing factors in the study area constrain the effectiveness of different methods. Optical remote sensing proved more effective in areas characterized by strong structural deformation and hard rock formations. In contrast, unmanned aerial vehicle (UAV) photogrammetry, combined with detailed ground surveys and geophysical exploration, was more suitable for identifying geohazards in the red layer distribution areas of the Mishi wide gentle syncline. Airborne LiDAR high-definition 3D photography was particularly effective for identifying "dustpan-shaped" landslides and "oak leaf-shaped" debris flows, which are common on the slopes of key towns. The combination of easily collapsible and slidable engineering geological rock groups and dip-slope structures is the key to the formation of geohazards in the study area. Geophysical exploration targeting disaster-controlling structures is an important support for geohazard identification.