Lu Huiyan, Li Weile, Xu Qiang, Yu Wenlong, Zhou Shengsen, Li Zhigang, Zhan Weiwei, Li Weimin, Xu Shanmiao, Zhang Pan, Dong Xiujun, Liang Jingtao, Ge Daqing
State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059, China; Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede 7522 NB, the Netherlands.
State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059, China.
Sci Total Environ. 2024 Jun 25;931:172709. doi: 10.1016/j.scitotenv.2024.172709. Epub 2024 Apr 24.
While significant progress has been achieved in utilizing remote sensing technologies for landslide investigation in China, there remains a notable gap in consolidating information on applicable conditions, application stages, and workflows across various remote sensing methodologies. This paper proposes a comprehensive framework for active landslide detection, incorporating multiple stages and data sources, successfully implemented in a vast region of southwestern China. Furthermore, detailed discussions are provided on the effects of the geometric distortion, land cover type, and various InSAR methods on the accuracy of active landslide identification results. Additionally, the paper delves into the advantages of integrated remote sensing technology in active landslide investigation, encompassing the assessment of current landslide activity status, precise delineation of boundaries, identification of different deformation stages, and determination of damage patterns. Through comprehensive analysis of multisource data, it enhances understanding of the active landslide process, ultimately contributing to the mitigation of casualties and property damage.
虽然中国在利用遥感技术进行滑坡调查方面取得了重大进展，但在整合各种遥感方法的适用条件、应用阶段和工作流程信息方面仍存在显著差距。本文提出了一个用于活动滑坡检测的综合框架，该框架包含多个阶段和数据源，并在中国西南部的广大地区成功实施。此外，还详细讨论了几何畸变、土地覆盖类型和各种干涉合成孔径雷达（InSAR）方法对活动滑坡识别结果准确性的影响。此外，本文还深入探讨了综合遥感技术在活动滑坡调查中的优势，包括评估当前滑坡活动状态、精确划定边界、识别不同变形阶段以及确定破坏模式。通过对多源数据的综合分析，它增进了对活动滑坡过程的理解，最终有助于减少人员伤亡和财产损失。
