Comprehensive study of landslides through the integration of multi remote sensing techniques: Framework and latest advances

被引:0
|
作者
Cheng Zhong
Hui Li
Wei Xiang
Aijun Su
Xianfeng Huang
机构
[1] China University of Geosciences,Three Gorges Research Center for Geo
[2] China University of Geosciences,hazard
[3] China University of Geoscience,Planetary Research Institute
[4] China University of Geosciences,Faculty of Engineering
[5] Wuhan University,Three Gorges Research Center for Geo
来源
Journal of Earth Science | 2012年 / 23卷
关键词
landslide; remote sensing; TGRG; framework; integration;
D O I
暂无
中图分类号
学科分类号
摘要
Detecting the timing and amount of deformation is critical for understanding the physical causes and eventually warning of possible landslide hazards. Monitoring of deformation of structures and ground surface displacements during landslides can be accomplished by using different types of systems and techniques. Besides geotechnical or physical techniques, remote sensing techniques can be classified as satellite techniques, photogrammetric techniques, geodetic techniques, ground based techniques, and so on. To study and govern growing geological disasters in China, especially in the Three Gorges area, Three Gorges Research Center for Geo-hazard (TGRG) is establishing an infra structure to effectively and comprehensively analyze the mechanism of landslide deformation, focused on the Huangtupo landslide, using of various advanced monitoring systems and techniques. In this article, the framework and latest advances of integration of multi remote sensing techniques in the infrastructure are presented. Different remote sensing techniques, data processing and integrating methods, and the latest results are discussed in detail. At last, reviews on current work and suggestions for further work are put forward.
引用
收藏
页码:243 / 252
页数:9
相关论文
共 50 条
  • [31] Integration of Remote Sensing and Machine Learning for Precision Agriculture: A Comprehensive Perspective on Applications
    Wang, Jun
    Wang, Yanlong
    Li, Guang
    Qi, Zhengyuan
    AGRONOMY-BASEL, 2024, 14 (09):
  • [32] Security through integration: Towards a comprehensive framework for development and certification
    Marquet, B
    Rossi, A
    Cosquer, FJN
    CERTIFICATION AND SECURITY IN E-SERVICES: FROM E-GOVERNMENT TO E-BUSINESS, 2003, 127 : 183 - 188
  • [33] Advances in Monitoring Crop and Soil Nutrient Status: Proximal and Remote Sensing Techniques
    Fischer, Pedro Tomas Bulacio
    Carella, Alessandro
    Massenti, Roberto
    Fadhilah, Raudhatul
    Lo Bianco, Riccardo
    HORTICULTURAE, 2025, 11 (02)
  • [34] Remote sensing techniques in the investigation of aeolian sand dunes: A review of recent advances
    Zheng, Zhijia
    Du, Shihong
    Taubenboeck, Hannes
    Zhang, Xiuyuan
    REMOTE SENSING OF ENVIRONMENT, 2022, 271
  • [35] Remote sensing techniques in the investigation of aeolian sand dunes: A review of recent advances
    Zheng, Zhijia
    Du, Shihong
    Taubenböck, Hannes
    Zhang, Xiuyuan
    Remote Sensing of Environment, 2022, 271
  • [36] Automated Landslides Detection for Mountain Cities Using Multi-Temporal Remote Sensing Imagery
    Chen, Zhong
    Zhang, Yifei
    Ouyang, Chao
    Zhang, Feng
    Ma, Jie
    SENSORS, 2018, 18 (03)
  • [37] Feature based remote sensing image registration techniques: a comprehensive and comparative review
    Misra, Indranil
    Rohil, Mukesh Kumar
    Moorthi, S. Manthira
    Dhar, Debajyoti
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2022, 43 (12) : 4477 - 4516
  • [38] A Comprehensive Review on Water Quality Parameters Estimation Using Remote Sensing Techniques
    Gholizadeh, Mohammad Haji
    Melesse, Assefa M.
    Reddi, Lakshmi
    SENSORS, 2016, 16 (08)
  • [39] A comprehensive review of remote sensing techniques for monitoring Ulva prolifera green tides
    Geng, Xiaomeng
    Li, Huiru
    Wang, Le
    Sun, Weidong
    Li, Yize
    FRONTIERS IN MARINE SCIENCE, 2025, 12
  • [40] Remote Sensing Techniques for Detecting Internal Solitary Waves: A comprehensive review and prospects
    Meng, Junmin
    Zhang, Hao
    Sun, Lina
    Wang, Jing
    IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE, 2024, 12 (04) : 46 - 78