首页|联合无人机光学与机载LiDAR在高位滑坡要素识别中的应用:以川西汶川龙溪沟滑坡为例

联合无人机光学与机载LiDAR在高位滑坡要素识别中的应用:以川西汶川龙溪沟滑坡为例

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高位和高隐蔽性滑坡调查人力难至、效率低下且安全风险大,利用无人机光学和机载LiDAR等航空遥感技术进行调查识别能够有效克服该问题,已成为当前研究应用的热点.目前多数研究与应用以宏观调查和解译为主,针对滑坡拉裂缝、滑坡壁等发育要素的精细化识别和量测研究较少.为进一步细化无人机光学和机载LiDAR识别的滑坡要素解译特征,提高该技术的综合应用效果,本文选取川西地震活跃区的汶川龙溪沟高位滑坡为示范,采用无人机摄影测量、机载LiDAR、解译对比与空间测量以及实地调查复核等方法,提取了 28条拉张裂缝、2条剪切裂缝、8处下挫陡坎、2条滑坡壁、5条前缘边界、5个次级变形体,基于滑坡要素排列组合划分了2个次级滑体、4个变形区.野外验证结果与室内解译高度吻合,证明了该方法的可靠性和准确性.研究成果总结对比滑坡要素在不同数据上的色调、纹理、光谱差异,探索联合无人机光学与机载LiDAR的滑坡要素"色调-纹理-图谱"协同对比提取方法,阐述了高位滑坡"先解译要素再分区组合"的精细识别过程.研究成果可为其他高危高位滑坡的精细化识别研究及防治应用提供技术参考,具有应用推广价值.
Application of Joint UAV Optics and Airborne LiDAR in High Level Landslide Element Identification:A Case Study from the Longxigou Landslide in Wenchuan,Western Sichuan
Investigation of high-level and highly concealed landslides is challenging and difficult to be reached by manpower,with low efficiency and high risks.The use of aerial remote sensing technologies such as drone optics and airborne LiDAR can effectively overcome these problems,and has been extensively applied to today's research.However,currently most of those research and applications focus on macroscopic investigations and interpretations,with only limited research on refined identifications and measurements of the development fac-tors,such as landslide cracks and landslide walls.In order to further refine the interpretation features of the landslide elements based on drone optics and airborne LiDAR recognition,and improve the comprehensive ap-plication of this technology,this study selected the Wenchuan Longxigou high-level landslide in the active area of earthquake in western Sichuan as an example.The methods include drone digital photogrammetry,airborne LiDAR distance measurement,interpretation comparison and spatial measurement,as well as on-site investiga-tion and verification.In total,twenty eight tension cracks,two shear cracks,and eight steep slopes were extrac-ted.Two landslide walls,five leading edge boundaries,and five secondary deformation zones were divided based on the arrangement and combination of the landslide elements into two secondary sliding zones and four deformation zones.The validations are highly consistent with the indoor interpretations,proving the reliability and accuracy of this proposed method.The research results summarized and compared the differences in color tone,texture,and spectrum of landslide elements on different data,explored the collaborative extraction method of'color tone texture map'of landslide elements using unmanned aerial vehicle optics and airborne LiDAR,and elaborated on the fine identification processes of high-level landslides by'interpreting elements first and then zoning and combining'.The results provide technical references for the fine identification and prevention of other high-risk high-level landslides,and have a significant value in the applications.

UVAairborne LiDARhigh level landslideelement identificationLongxigou of Wenchuan

王德富、李永鑫、任娟、范亚军、刘立、罗超

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自然资源部第三地理信息制图院,四川成都 610100

自然资源部数字制图与国土信息应用重点实验室,四川成都 610100

四川省国土空间生态修复与地质灾害防治研究院,四川成都 610036

无人机 机载LiDAR 高位滑坡 要素识别 汶川龙溪沟

四川省自然资源厅地质灾害隐患遥感识别监测及高分遥感应用服务项目自然资源部科技发展司自然资源技术融合与应用示范项目自然资源部四川省滑坡灾害隐患遥感智能防控体系部省合作研究项目

N5100012022001470121204007000204101SCDZRS2023

2024

现代地质
中国地质大学(北京)

现代地质

CSTPCD北大核心
影响因子:1.2
ISSN:1000-8527
年,卷(期):2024.38(2)
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