日本地球惑星科学連合2025年大会

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セッション記号 H (地球人間圏科学) » H-DS 防災地球科学

[H-DS07] 地すべりおよび関連現象

2025年5月30日(金) 10:45 〜 12:15 102 (幕張メッセ国際会議場)

コンビーナ:王 功輝(京都大学防災研究所)、齋藤 仁(名古屋大学 大学院環境学研究科)、千木良 雅弘(公益財団法人 深田地質研究所)、今泉 文寿(静岡大学農学部)、座長:齋藤 仁(名古屋大学 大学院環境学研究科)、Wei Li(ChangAn University)

11:45 〜 12:00

[HDS07-11] Integration of Remote Sensing Technologies and 3D Modeling for Comparative Analysis of Rock Slope Failures: A Case Study of Yusuihsi and Guanghua Slopes in Taiwan

*HSIEN-LI KUO1、GUAN-WEI LIN1、TING-YU LIN2、Che-HSIN LIU3、CHUNG-RAY CHU3、CHIH-HSIN CHANG3、CHING-WEEI LIN1、Hongey CHEN3 (1.Department of Earth Sciences, National Cheng Kung University、2.Disaster Prevention Research Center, National Cheng Kung University,、3. National Science and Technology Center for Disaster Reduction)

キーワード:landslide monitoring, rock slope stability, remote sensing integration, three-dimensional modeling

The comprehensive study analyzed two significant rock slopes in Taiwan using integrated remote sensing technologies. At Yusuihsi slope, which ultimately failed, monitoring revealed peak velocities of 0.22-0.60 m/d and accelerations of 0.006-0.034 m/d² before collapse, with rainfall significantly influencing movement patterns. In contrast, the Guanghua slope, which underwent deformation without failure, exhibited maximum velocities of 0.17 m/d and accelerations of 0.003 m/d². Through advanced Landslide Thickness Inversion techniques applied to LiDAR-derived DEMs, we developed a detailed 3D conceptual model of the Guanghua slope, dividing it into four distinct blocks: head, northern body, southern body, and toe. The model revealed varying landslide thickness from less than 10 meters at the head to 55 meters in the body, with the southern body identified as having the highest potential failure volume. The study established critical thresholds for failure prediction (0.2 m/d velocity and 0.015 m/d² acceleration) and proposed seven different failure scenarios based on block characteristics and interactions. This research demonstrates the effectiveness of integrating optical satellite imagery and LiDAR technology for landslide monitoring and emphasizes the importance of site-specific geological characteristics in developing tailored monitoring strategies. The findings provide a robust scientific framework for landslide risk assessment and early warning system development, contributing to more effective disaster prevention and mitigation strategies.