Surface Micro-Relief Evolution in Southeast Tibet Based on InSAR Technology
Based on 143 Sentinel-1A images from January 2020 to December 2022, this study used SBAS-InSAR technology to monitor the surface deformation of the tailings pond and analyzed and predicted the surface deformation laws in southeast Tibet. Overall, the surface deformation of the tailings pond was significant and there were many areas where the deformation was uneven. The typical subsidence areas were mainly located in the northern part of the right tailings pond and the southern part of the left tailings pond. From a temporal perspective, the subsidence in the tailings pond showed a certain periodic downward fluctuation. Specifically, cumulative subsidence from January to September each year displayed a clear downward trend, reaching its maximum around September. This was followed by a slight uplift in October and November, after which a notable downward trend resumed from December until the following September. Based on spatial scale analysis, the changes in the tailings pond were relatively stable before May 2020. After that, the northern part of the right tailings pond showed a sinking trend, while the southern part exhibited uplift, and the central part remained relatively stable. Conversely, the southeastern part of the left tailings pond showed an uplifting trend, while the northern, central, and western parts experienced subsidence. Based on the Holt–Winters exponential smoothing model, we predicted the cumulative subsidence for 10 monitoring points in 2023. The northern part of the right tailings pond is expected to continue showing a significant subsidence trend in 2023. A prominent subsidence center is projected to emerge in the central part of the left tailings pond, and we should strengthen monitoring to avoid the disaster risk in the mining area.
Authors
- Z. Jiang (ORCID: https://orcid.org/0000-0002-2227-098X)
- Zhanwen Han (ORCID: https://orcid.org/0000-0001-9204-7778)
- Qunou Jiang
- Liang Cheng (ORCID: https://orcid.org/0000-0002-4491-6681)
- Gesangzhuoma
Institutions
- Beijing Forestry University (CN)
- Nanjing University (CN)
Publication Details
- Journal
- Land
- Published
- 2025-02-28
- DOI
- https://doi.org/10.3390/land14030503
- Primary Topic
- Synthetic Aperture Radar (SAR) Applications and Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- National Key Research and Development Program of China