Spatial and temporal prediction of ground subsidence in mining areas considering seasonal characteristics

Intelligent Remote Sensing for Disaster Prevention and Mitigation | Views:633Downloads:5157CSCD:0

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Spatial and temporal prediction of ground subsidence in mining areas considering seasonal characteristics
“In the field of predicting ground subsidence in mining areas, experts have proposed the SFF PredRNN model, which provides effective data support for the prevention and control of subsidence disasters in mining areas.”
- role：First author第一作者
- Affiliation：
  School of Geophysics and Geomatics, China University of Geosciences, Wuhan430074, China
- Email：xwguo@cug.edu.cn
- Introduction：郭骁玮，研究方向为InSAR地面沉降监测及智能预测。E-mail： xwguo@cug.edu.cn
GUO Xiaowei
* ,
- role：Corresponding author通信作者
- Affiliation：
  School of Geophysics and Geomatics, China University of Geosciences, Wuhan430074, China
- Email：taochen@cug.edu.cn
- Introduction：陈涛，研究方向为遥感地学应用。E-mail： taochen@cug.edu.cn
CHEN Tao
*
Vol. 28, Issue 11, Pages: 3016-3031(2024)
DOI：10.11834/jrs.20243488
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