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Yao, Sheng, He, Yi, Zhang, Lifeng, Yang, Wang, Chen, Yi, Sun, Qiang, Zhao, Zhan'ao, Cao, Shengpeng (2023) A ConvLSTM Neural Network Model for Spatiotemporal Prediction of Mining Area Surface Deformation Based on SBAS-InSAR Monitoring Data. IEEE Transactions on Geoscience and Remote Sensing, 61. 1-22 doi:10.1109/tgrs.2023.3236510

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Reference TypeJournal (article/letter/editorial)
TitleA ConvLSTM Neural Network Model for Spatiotemporal Prediction of Mining Area Surface Deformation Based on SBAS-InSAR Monitoring Data
JournalIEEE Transactions on Geoscience and Remote Sensing
AuthorsYao, ShengAuthor
He, YiAuthor
Zhang, LifengAuthor
Yang, WangAuthor
Chen, YiAuthor
Sun, QiangAuthor
Zhao, Zhan'aoAuthor
Cao, ShengpengAuthor
Year2023Volume61
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
DOIdoi:10.1109/tgrs.2023.3236510Search in ResearchGate
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Mindat Ref. ID15698966Long-form Identifiermindat:1:5:15698966:6
GUID0
Full ReferenceYao, Sheng, He, Yi, Zhang, Lifeng, Yang, Wang, Chen, Yi, Sun, Qiang, Zhao, Zhan'ao, Cao, Shengpeng (2023) A ConvLSTM Neural Network Model for Spatiotemporal Prediction of Mining Area Surface Deformation Based on SBAS-InSAR Monitoring Data. IEEE Transactions on Geoscience and Remote Sensing, 61. 1-22 doi:10.1109/tgrs.2023.3236510
Plain TextYao, Sheng, He, Yi, Zhang, Lifeng, Yang, Wang, Chen, Yi, Sun, Qiang, Zhao, Zhan'ao, Cao, Shengpeng (2023) A ConvLSTM Neural Network Model for Spatiotemporal Prediction of Mining Area Surface Deformation Based on SBAS-InSAR Monitoring Data. IEEE Transactions on Geoscience and Remote Sensing, 61. 1-22 doi:10.1109/tgrs.2023.3236510
In(2023) IEEE Transactions on Geoscience and Remote Sensing Vol. 61. Institute of Electrical and Electronics Engineers (IEEE)

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