Research Progress in landslide Monitoring Based on Time-lapse Resistivity Method

Tao Tao, Peng Han (), Kaiyan Hu, Shuangling Mo, Shuangshuang Li, Wei Gong, Gexue Bai, Ruidong Li, Baofeng Wan and Ning An
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Tao Tao: Southern University of Science and Technology, Department of Earth and Space Sciences
Peng Han: Southern University of Science and Technology, Department of Earth and Space Sciences
Kaiyan Hu: China University of Geoscience, School of Geophysics and Geomatics
Shuangling Mo: Southern University of Science and Technology, Department of Earth and Space Sciences
Shuangshuang Li: Southern University of Science and Technology, Department of Earth and Space Sciences
Wei Gong: Southern University of Science and Technology, Department of Earth and Space Sciences
Gexue Bai: Gansu Institute of Engineering Geology
Ruidong Li: Gansu Institute of Engineering Geology
Baofeng Wan: Gansu Institute of Engineering Geology
Ning An: Gansu Institute of Engineering Geology

A chapter in Proceedings of the 11th Annual Meeting of Risk Analysis Council of China Association for Disaster Prevention (RAC 2024), 2025, pp 35-42 from Springer

Abstract: Abstract Landslides in China are numerous, widely distributed, frequent, and cause significant damage. Monitoring and early warning are critical measures for preventing landslide disasters. As a near-surface monitoring technique, the time-lapse resistivity method can capture the spatiotemporal evolution of the landslide's internal electrical structure, providing valuable data for landslide prevention and stability analysis. This paper aims to review and summarize the research on the time-lapse resistivity method in landslide monitoring and early warning, assess the current progress, explore potential future developments, and provide insights for scientific research and engineering practices in landslide disaster prevention and control.

Keywords: Landslide Disaster Monitoring; Time-lapse Resistivity Method; Electrical Structure (search for similar items in EconPapers)
Date: 2025
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DOI: 10.2991/978-94-6463-946-9_6

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