Shaking table test study of accumulation layer landslide under earthquake action

Ma, Kun; Zhang, Yongmou; Wu, Honggang; Ji, Zhiyang; Ren, Jiankai; Yu, Lintao; Zhou, Xinlu

doi:10.1007/s12517-021-08631-w

Cited by 1 publication

(1 citation statement)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Many studies investigated factors affecting landslide development through various means, such as physical tests [13][14][15][16], numerical simulations [17][18][19], and statistical methods [20,21]. At present, the most effective method has not yet been established because the characteristics of landslides and influencing factors vary from region to region.…”

Section: Introductionmentioning

confidence: 99%

Improving the Understanding of Landslide Development in Alpine Forest Regions Using the InSAR Technique: A Case Study in Xiaojin County China

Zhou,

Guo,

Huang

et al. 2023

Applied Sciences

View full text Add to dashboard Cite

Employing a small baseline subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) and hotspot analysis, this study identified 81 potential landslides in a 768.7 km2 area of Xiaojin county, eastern Tibetan Plateau. Subsequent time-series deformation analysis revealed that these potential landslides are in the secondary creep stage. The newly identified landslides were compared to a landslide inventory (LI), established through field surveying, in terms of causative factors, including altitude, slope, relief amplitude, distance to river, distance to road, and slope curvature. From the comparison, the InSAR technique showed the following advantages: (1) it identified 25 potential landslides at high altitudes (>3415 m) in addition to the low-altitude landslides identified through the field survey. (2) It obtained approximately 37.5% and 70% increases in the number of potential landslides in the slope angle ranges of 20°–30° and 30°–40°, respectively. (3) It revealed significant increases in potential landslides in every relief amplitude bin, especially in the range from 58 m to 92 m. (4) It can highlight key geological factors controlling landslides, i.e., the stratigraphic occurrence and key joints as the InSAR technique is a powerful tool for identifying landslides in all dip directions. (5) It reveals the dominant failure modes, such as sliding along the soil–rock interface and/or interfaces formed by complicated combinations of discontinuities. This work presents the significant potential of InSAR techniques in gaining deeper knowledge on landslide development in alpine forest regions.

show abstract