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Remote Sensing
Volume 18
Issue 12
10.3390/rs18121961
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Landslide Deformation Remote Monitoring in Alpine Mountains Using UAV Photogrammetry and Infrared Thermography: A Case Study in Wumeng Mountain Region, China

by
Cong Zhao
1,
Meng Wang
1,*,
Yueping Yin
2,
Yongbo Tie
3,
Sainan Zhu
2,
Jingtao Liang
1,
Su Zhang
1,
Jianguo Feng
1,
Ban Song
1 and
Xueqing Li
1
1
Evaluation and Utilization of Strategic Rare Metals and Rare Earth Resource Key Laboratory of Sichuan Province, Sichuan Institute of Comprehensive Geological Survey, Chengdu 610081, China
2
China Geological Survey, China Institute of Geo-Environment Monitoring, Beijing 100081, China
3
Chengdu Center of China Geological Survey, Chengdu 611734, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2026, 18(12), 1961; https://doi.org/10.3390/rs18121961 (registering DOI)
Submission received: 17 April 2026 / Revised: 9 June 2026 / Accepted: 10 June 2026 / Published: 12 June 2026
(This article belongs to the Special Issue Advances in GIS and Remote Sensing Applications in Natural Hazards)
Versions Notes

Abstract

Land surface temperature (LST) is crucial for understanding winter landslide evolution. This study combines Unmanned Aerial Vehicle (UAV) photogrammetry and infrared thermography (IRT) to monitor winter landslides in China’s Wumeng Mountain region. Using the Yangjiazhai landslide—induced by underground coal mining—as a case study, we demonstrate significant correlations between IRT-detected LST anomalies and surface cracks: (1) cracks with elevated temperatures are likely connected to subsurface goaf zones; (2) excessively widened cracks show no thermal anomalies due to enhanced air convection. The research reveals that key landslide components have distinct LST signatures, governed by differential soil–rock moisture and crack networks. For accurate high-altitude winter LST acquisition, UAV thermal surveys should be conducted under overcast, fog-free conditions to reduce solar interference. This validates UAV visible–infrared fusion for extracting landslide boundaries, cracks, slumping zones, bedrock patterns, and moisture distribution. The methodology establishes a new pathway for investigating winter landslide deformation and instability, confirming IRT’s operational viability in high-altitude alpine regions.
Keywords: landslide deformation; alpine mountain; remote monitoring; UAV; infrared thermography landslide deformation; alpine mountain; remote monitoring; UAV; infrared thermography

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MDPI and ACS Style

Zhao, C.; Wang, M.; Yin, Y.; Tie, Y.; Zhu, S.; Liang, J.; Zhang, S.; Feng, J.; Song, B.; Li, X. Landslide Deformation Remote Monitoring in Alpine Mountains Using UAV Photogrammetry and Infrared Thermography: A Case Study in Wumeng Mountain Region, China. Remote Sens. 2026, 18, 1961. https://doi.org/10.3390/rs18121961

AMA Style

Zhao C, Wang M, Yin Y, Tie Y, Zhu S, Liang J, Zhang S, Feng J, Song B, Li X. Landslide Deformation Remote Monitoring in Alpine Mountains Using UAV Photogrammetry and Infrared Thermography: A Case Study in Wumeng Mountain Region, China. Remote Sensing. 2026; 18(12):1961. https://doi.org/10.3390/rs18121961

Chicago/Turabian Style

Zhao, Cong, Meng Wang, Yueping Yin, Yongbo Tie, Sainan Zhu, Jingtao Liang, Su Zhang, Jianguo Feng, Ban Song, and Xueqing Li. 2026. "Landslide Deformation Remote Monitoring in Alpine Mountains Using UAV Photogrammetry and Infrared Thermography: A Case Study in Wumeng Mountain Region, China" Remote Sensing 18, no. 12: 1961. https://doi.org/10.3390/rs18121961

APA Style

Zhao, C., Wang, M., Yin, Y., Tie, Y., Zhu, S., Liang, J., Zhang, S., Feng, J., Song, B., & Li, X. (2026). Landslide Deformation Remote Monitoring in Alpine Mountains Using UAV Photogrammetry and Infrared Thermography: A Case Study in Wumeng Mountain Region, China. Remote Sensing, 18(12), 1961. https://doi.org/10.3390/rs18121961

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