Abstract
Abstract. Geological disasters such as landslides and debris flows pose a serious threat to human life and property. To mitigate this risk, monitoring and early warning systems are essential. However, monitoring high-angle landslide areas can be challenging due to the steep and complex terrain, making it difficult to carry out large-scale and refined deformation measurements using existing methods. This paper proposes a method to measure the large-scale deformation of landslide bodies based on nap-of-the-object photogrammetry. The method uses UAVs to acquire high-resolution 3D models of steep and high landslide areas at multiple time periods. Then, 3D model matching is employed to obtain accurate variation information for terrain deformation measurement. To obtain fine 3D models, a terrain-adaptive nap-of-the-object photogrammetric flight planning is applied to design the optimal photographic positions and directions for capturing ultra-high-resolution images. The images are processed using photogrammetric principles and technologies to produce fine 3D models. For terrain deformation measurement, an algorithm is proposed to obtain 3D correspondences by fusing DEM differential and 3D model texture matching. The 3D points variation vectors are then calculated, and the large-scale deformation measurement results of the landslide body can be derived after the vectors are aggregated. Experiments were conducted on the Lijiebeishan landslide in Gansu Province, western China. The results showed that the proposed deformation measurement method was highly effective in accurately detecting areas with displacement greater than 5 cm, and the large-scale deformation trend is consistent with GNSS predictions. In conclusion, the proposed method is an effective way to measure the large-scale deformation of landslide bodies in high-angle landslide areas, providing a valuable tool for monitoring and early warning systems.
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