Deformation prediction for the Yuka mining area based on LICSBAS using a velocity-neighborhood spatial algorithm combined with a temporal graph convolutional network (T-GCN)

It is becoming increasingly vital to assess the risks of geological disasters associated with mining activities. However, most existing methods solely evaluate the deformation of individual points in mining areas without accounting for the overall deformation of an entire working face; additionally,...

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Veröffentlicht in:	IEEE journal of selected topics in applied earth observations and remote sensing S. 1 - 16
Hauptverfasser:	Jia, Hongguo, Yang, Yang, Wang, Zhiwei, Zeng, Xin, He, Yujun, Bai, Zhenghang, Liu, Yuchen
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	IEEE 2025
Schlagworte:	Accuracy Comets Data mining Deep learning Deformable models Deformation Geology LiCSBAS Mining area monitoring Monitoring Predictive models SAR Spatiotemporal phenomena T-GCN Time series analysis
ISSN:	1939-1404, 2151-1535
Online-Zugang:	Volltext
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