Automatic Detection and Calculation of Mining Subsidence in Large-Scale Interferograms With Transformer-CNN Model

Automatic Detection and Calculation of Mining Subsidence in Large-Scale Interferograms With Transformer-CNN Model

Coal mining operations trigger geological hazards including ground subsidence, surface fracturing, and landslides, endangering resident safety and infrastructure in mining regions. To address this, rapid large-scale detection and precise quantification of mining-induced subsidence are critical. Ther...

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Bibliographic Details
Main Authors: Hongdong Fan, Jialin Xin, Tao Lin, Jun Wang
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Convolutional neural network (CNN)
interferometric synthetic aperture radar (InSAR)
mining subsidence
transformer
Online Access:https://ieeexplore.ieee.org/document/11027530/
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