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Short-term displacement prediction for newly established monitoring slopes based on transfer learningOACSTPCD

中文摘要

This study makes a significant progress in addressing the challenges of short-term slope displacement prediction in the Universal Landslide Monitoring Program,an unprecedented disaster mitigation program in China,where lots o…查看全部>>

Yuan Tian;Yang-landuo Deng;Ming-zhi Zhang;Xiao Pang;Rui-ping Ma;Jian-xue Zhang

Institute of Remote Sensing and Geographical Information Systems,Peking University,Beijing 100871,China Beijing Key Laboratory of Spatial Information Integration and Its Applications,Beijing 100871,ChinaInstitute of Remote Sensing and Geographical Information Systems,Peking University,Beijing 100871,China Beijing Key Laboratory of Spatial Information Integration and Its Applications,Beijing 100871,ChinaInstitute of Public Safety Research,Department of Engineering Physics,Tsinghua University,Beijing 100084,China China Institute of Geo-Environment Monitoring,Beijing 100081,China Technology Innovation Center for Geohazard Monitoring and Risk Early Warning,Ministry of Natural Resources,Beijing 100081,ChinaInstitute of Remote Sensing and Geographical Information Systems,Peking University,Beijing 100871,China Beijing Key Laboratory of Spatial Information Integration and Its Applications,Beijing 100871,ChinaInstitute of Remote Sensing and Geographical Information Systems,Peking University,Beijing 100871,China Beijing Key Laboratory of Spatial Information Integration and Its Applications,Beijing 100871,ChinaInstitute of Remote Sensing and Geographical Information Systems,Peking University,Beijing 100871,China Beijing Key Laboratory of Spatial Information Integration and Its Applications,Beijing 100871,China

地质学

LandslideSlope displacement predictionTransfer learningIntegrated datasetTransformerPre-trained modelUniversal Landslide Monitoring Program(ULMP)Geological hazards survey engineering

《China Geology》 2024 (2)

P.351-364,14

funded by the project of the China Geological Survey(DD20211364)the Science and Technology Talent Program of Ministry of Natural Resources of China(grant number 121106000000180039–2201)。

10.31035/cg2024053

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