Kinematics and mechanism analysis of Tangjiawan landslide on the Xinshi—Jinyang Highway in Sichuan Province - Qiang CHENG; Xingquan ZHOU; Xiao ZHANG (Zhongguo dizhi zaihai yu fangzhi xuebao)
Studying the kinematics of landslides is crucial for analyzing failure mechanism and designing remedial measures. This paper focuses on the Tandjiawan landslide that occurred during a highway construction. Five periods of high-resolution digital orthophoto maps (DOM) were generated using unmanned aerial vehicle (UAV)- based photogrammetry, spanning both pre- and post- landslide conditions. Two successive UAV orthophotos were treated as observation periods, and corresponding features were identified in both images to establish monitoring points. Furthermore, two-dimensional displacement vectors were then computed by comparing orthographic images from each observation period based on these corresponding features. The analysis of kinematics and failure mechanism were conducted in conjunction with geological surveys and inclinometer measurements. The findings reveal that there was no significant deformation in the landslide area before the engineering construction of the highway (1st observation period). After construction, during the second observation period (March 15, 2021, to June 6, 2021), the third observation period (June 6, 2021, to September 8, 2021), and the fourth observation period (September 8, 2021, to November 3, 2021), the average deformation rates of the main sliding area of the landslide were 53.0 mm/day, 103.2 mm/day and 62.5 mm/day, respectively. By the fifth observation period (November 3, 2021, to January 3, 2022), the deformation rates had trended towards zero. The deposition of spoil at the rear of the landslide during the second observation period was the direct triggering factor, and rainfall facilitated the development of landslide deformation. As the rainy season ended and the front-end loading increased, the landslide deformation rate gradually decreased. This paper demonstrates that multi-period UAV photogrammetry can provide spatiotemporal surface deformation information for landslide areas, serving as an effective tools for landslide deformation monitoring.