Early Identification and Dynamic Stability Evaluation of High-Locality Landslides in Yezhi Site Area, China by the InSAR Method

Baoqin Lian, Daozheng Wang (), Xingang Wang and Weijia Tan
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Baoqin Lian: State Key Laboratory of Continental Dynamics, Department of Geology, Northwest University, Xi’an 710069, China
Daozheng Wang: State Key Laboratory of Continental Dynamics, Department of Geology, Northwest University, Xi’an 710069, China
Xingang Wang: State Key Laboratory of Continental Dynamics, Department of Geology, Northwest University, Xi’an 710069, China
Weijia Tan: College of Geological Engineering and Surveying, Chang’an University, Xi’an 710054, China

Land, 2024, vol. 13, issue 5, 1-20

Abstract: In mountainous regions, high-locality landslides have the characteristics of a latent disaster process with a wide disaster range, which can easily cause large casualties. Therefore, early landslide identification and dynamic stability evaluation are significant. We first used multi-temporal synthetic aperture radar data to detect potential landslides at Yezhi Site Area during the 2015–2020 period, identifying and mapping a total of 18 active landslides. The study area was found to have an average deformation rate between −15 and 10 mm/y during the period. Then, time series and spatiotemporal deformation characteristics of landslides were examined using interferogram stacking and small baseline interferometry techniques. The results show that the majority of the landslide deformations detected exhibit a periodic variation trend, and the study area was in a slow deformation state before 2017. Finally, combined with detection results, Google Earth optical images, and field investigations, it is concluded that the main factors affecting the time series deformation and spatial distribution of landslides in the study area are rainfall, geological factors, and engineering activities. The results of this study provide valuable technical references and support for early identification and dynamic stability evaluation of regional active landslides in complex terrain, especially for high-locality landslides.

Keywords: InSAR; high-locality landslides; time series deformation; small baseline interferometry; early identification (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2024
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