Abstract: In order to address the difficulties in data acquisition encountered in the field survey during the risk assessment of single landslide, the authors in this research proposed a collaborative evaluation method integrating UAV and InSAR technologies. And a case study of Mukua landslide in Yongshan County was chosen. On the basis of regional geological data and field investigations, unmanned aerial vehicle (UAV) photogrammetry was used to obtain high-precision digital elevation model (DEM), digital orthophoto map (DOM) and 3D reality models, and they were used to extract information on landslide morphology, scale and spatial distribution of the hazard-affected bodies. The surface deformation was detected, and the deformed areas and movement trends of landslides were identified, based on Interferometric Synthetic Aperture Radar (InSAR). The numerical simulation was conducted using high-precision UAV-derived ground models, and landslide geological hazard risk assessment was carried out combined with the distribution of hazard-bearing bodies. The results showed that the risk assessment of related factors such as geological environment, landslide basic features, and triggering conditions extracted by this method has good applicability. The calculated total risk value of the landslide area under various scenarios exceeded the average property loss of the landslide in Yongshan County, and the risk level was high, which was consistent with the verification results. By synergistically analyzing InSAR-derived deformation data with UAV-based 3D modeling, this study effectively integrated multi-source remote sensing information. The key factors were selected, including geological environment, landslide characteristics, and triggering conditions, to establish a risk assessment method specifically tailored for individual landslides. The proposed method proved to be scientifically sound and highly applicable, and could offer significant technical support for geological hazard investigation and evaluation research.