The Prediction of Transmission Towers’ Foundation Ground Subsidence in the Salt Lake Area Based on Multi-Temporal Interferometric Synthetic Aperture Radar and Deep Learning

The Prediction of Transmission Towers’ Foundation Ground Subsidence in the Salt Lake Area Based on Multi-Temporal Interferometric Synthetic Aperture Radar and Deep Learning

Displacement prediction of transmission towers is essential for the early warning of transmission network deformation. However, there is still a lack of prediction on the ground subsidence of the tower foundation. In this study, we first used the multi-temporal interferometric synthetic aperture rad...

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Bibliographic Details
Main Authors: Bijing Jin, Taorui Zeng, Taohui Yang, Lei Gui, Kunlong Yin, Baorui Guo, Binbin Zhao, Qiuyang Li
Format: Article
Language:English
Published: MDPI AG 2023-10-01
Series:Remote Sensing
Subjects:
transmission tower
ground subsidence
Salt Lake
displacement prediction
MT-InSAR
deep learning
Online Access:https://www.mdpi.com/2072-4292/15/19/4805

Internet

https://www.mdpi.com/2072-4292/15/19/4805

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