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Exploring Shallow Geological Structures in Landslides Using the Semi-Airborne Transient Electromagnetic Method.

Authors :
Wu, Junjie
Xiao, Du
Du, Bingrui
Liu, Yuge
Zhi, Qingquan
Wang, Xingchun
Deng, Xiaohong
Chen, Xiaodong
Zhao, Yi
Huang, Yue
Source :
Remote Sensing. Sep2024, Vol. 16 Issue 17, p3186. 17p.
Publication Year :
2024

Abstract

The Meijiayan landslide in Pengshui County within Chongqing City is a medium-scale soil landslide triggered by the excavation of roadbeds. To delve into the influencing factors and assess the stability of this landslide, it is crucial to meticulously map the subterranean geological framework of the area. Such an analysis lays the groundwork for evaluating and mitigating the risks of future landslide instabilities. In this context, the semi-airborne transient electromagnetic method (SATEM), which is complemented by a receiving system mounted on an aerial platform, stands out as an innovative geophysical exploration technique. This method is adept at conducting swift measurements across complex terrains, making it particularly valuable for areas prone to such geological events. This paper presents the utilization of a cutting-edge loop source SATEM system, which was operationalized via a rotor-based unmanned aerial vehicle (UAV). The system was employed to conduct shallow geological structure detection experiments on the Meijiayan landslide. The SATEM detection outcomes have unveiled fluctuations in the electrical distribution across the upper strata, which are indicative of the subsurface geological boundaries, faults, and areas potentially rich in water within the landslide region. These discoveries affirm the viability of utilizing loop source SATEM for the identification of shallow geological structures in regions susceptible to landslides. The findings indicate that while the landslide is currently in a stable condition, it poses a significant risk of movement, especially during the rainy season, with the potential for landslides to be exacerbated by extreme or sustained rainfall events. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20724292
Volume :
16
Issue :
17
Database :
Academic Search Index
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
179650695
Full Text :
https://doi.org/10.3390/rs16173186