Combination of InSAR and neural networks for the deformation monitoring and prediction of Fanjiaping landslide
Traditional methods for monitoring surface deformation of landslides have significant limitations, including small monitoring coverage, difficulty in acquiring information in complex terrains, and high economic costs. Furthermore, the nonlinear and uncertain characteristics of deformation time serie...
Saved in:
| Main Authors: | Wenzheng XU, Shuqiang LU, Zhen LIN, Wangmin ZHOU |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Hydrogeology & Engineering Geology
2025-03-01
|
| Series: | Shuiwen dizhi gongcheng dizhi |
| Subjects: | |
| Online Access: | https://www.swdzgcdz.com/en/article/doi/10.16030/j.cnki.issn.1000-3665.202308028 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Landslide Detection in Long-Term and Low-Coherence Scenario Using Faster Intermittent Stacking InSAR Method
by: Huayan Dai, et al.
Published: (2025-01-01) -
Deformation-Related Data Mining and Movement Patterns of the Huangtupo Landslide in the Three Gorges Reservoir Area of China
by: Zhexian Liao, et al.
Published: (2025-04-01) -
Landslide Detection and Deformation Control Analysis in the Reservoir Area of Wudongde Hydropower Station by InSAR Observations
by: Fan Wen, et al.
Published: (2025-04-01) -
Surface Deformation Monitoring and Prediction of Longtantian Open-Pit Mine Based on SBAS-InSAR and CNN-BiLSTM Techniques
by: Xiaoxiao Zhang, et al.
Published: (2025-01-01) -
Evolution of landslide susceptibility in the Three Gorges Reservoir area over the three decades from 1991 to 2020
by: Jiahui Dong, et al.
Published: (2025-12-01)