测绘通报 ›› 2024, Vol. 0 ›› Issue (1): 12-18.doi: 10.13474/j.cnki.11-2246.2024.0103

• 地质灾害探测与隐患识别 • 上一篇    下一篇

知识图谱驱动下的多源遥感滑坡隐患识别

李永鑫1,2, 王德富1, 马志刚3, 范亚军1, 杨本勇1,2, 刘立1,2, 罗超1   

  1. 1. 自然资源部第三地理信息制图院, 四川 成都 610100;
    2. 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;
    3. 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
  • 收稿日期:2023-06-16 出版日期:2024-01-25 发布日期:2024-01-30
  • 通讯作者: 王德富。E-mail:497333919@qq.com
  • 作者简介:李永鑫(1986—),男,硕士,高级工程师,主要从事测绘遥感技术应用工作。E-mail:317307006@qq.com
  • 基金资助:
    四川省地质灾害隐患遥感识别监测及高分遥感应用服务项目(N5100012022001470);四川省重点研发计划(2022YFS0450);四川省自然资源厅科研项目(KJ-2023-024)

Multi-source remote sensing landslide hazard identification method driven by knowledge graph

LI Yongxin1,2, WANG Defu1, MA Zhigang3, FAN Yajun1, YANG Benyong1,2, LIU Li1,2, LUO Chao1   

  1. 1. The Third Geoinformation Mapping Institute of Ministry of Natural Resources, Chengdu 610100, China;
    2. Key Laboratory of Digital Mapping and Homeland Information, Ministry of Natural Resourcess, Chengdu 610100, China;
    3. Sichuan Academy of Territorial Space Ecorestoration and Geohazard Prevention, Chengdu 610036, China
  • Received:2023-06-16 Online:2024-01-25 Published:2024-01-30

摘要: 遥感技术在地质灾害防治领域发挥着重要作用,随着航天航空技术的发展,更多的遥感数据可被获得并有效地运用于地质灾害体的识别,尤其在滑坡隐患识别中广为应用。综合利用InSAR和光学遥感数据开展地质灾害隐患识别是近期研究的热点。传统识别过程完全依靠解译人员的工作经验,其主观性较强,无固定的识别逻辑遵循。本文基于SBAS-InSAR与光学卫星影像,通过分析滑坡隐患识别过程,构建滑坡识别知识图谱和识别提取矩阵模型。在知识图谱逻辑驱动下对“光学遥感+InSAR”组合识别的滑坡隐患进行区域空间特征分析,为滑坡广域识别提供了具有半定量化提取指标意义的参考执行方案,实现了滑坡隐患识别从完全主观到半定量化的识别过程。试验表明,本文方法可为相关研究和工程实际应用提供借鉴,具有一定的应用价值。

关键词: 滑坡隐患, InSAR, 光学影像, 知识图谱, 遥感识别

Abstract: Remote sensing technology plays an important role in the field of geological disaster prevention and control. With the development of aerospace technology, more remote sensing data can be obtained and effectively applied to the identification of geological hazard bodies, especially in the identification of landslide hazards. Comprehensive use of InSAR and optical remote sensing data to identify geological hazards is a hot topic in recent research. The traditional recognition process relies entirely on the work experience of interpreters, with strong subjectivity and no fixed recognition logic to follow. Based on SBAS-InSAR and optical satellite imagery, this paper analyzes the process of landslide hazard identification, and constructs the Knowledge graph and identification extraction matrix model of landslide identification. Under the logic drive of the Knowledge graph, the regional spatial characteristics of landslide hazards identified by the combination of “optical remote sensing+InSAR” are analyzed, providing a reference implementation scheme with the significance of semi quantitative extraction of indicators for landslide wide area identification, and realizing the identification process of landslide hazards from completely subjective to semi quantitative. Experiments show that this method can provide reference for relevant research and practical engineering applications, and has certain application value.

Key words: landslide hazards, InSAR, optical imaging, knowledge graph, remote sensing recognition

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