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    薛强, 张茂省, 董英, 孟晓捷, 郭小鹏, 冯卫, 洪勃, 王涛, 刘文辉, 田中英, 张戈, 卢娜. 基于DEM和遥感的黄土地质灾害精细化风险识别——以陕北黄土高原区米脂县为例[J]. 中国地质, 2023, 50(3): 926-942. DOI: 10.12029/gc20220801001
    引用本文: 薛强, 张茂省, 董英, 孟晓捷, 郭小鹏, 冯卫, 洪勃, 王涛, 刘文辉, 田中英, 张戈, 卢娜. 基于DEM和遥感的黄土地质灾害精细化风险识别——以陕北黄土高原区米脂县为例[J]. 中国地质, 2023, 50(3): 926-942. DOI: 10.12029/gc20220801001
    XUE Qiang, ZHANG Maosheng, DONG Ying, MENG Xiaojie, GUO Xiaopeng, FENG Wei, HONG Bo, WANG Tao, LIU Wenhui, TIAN Zhongying, ZHANG Ge, LU Na. Refinement risk identification of loess geo-hazards based on DEM and remote sensing——Taking Mizhi County in the Loess Plateau of Northern Shaanxi as an example[J]. GEOLOGY IN CHINA, 2023, 50(3): 926-942. DOI: 10.12029/gc20220801001
    Citation: XUE Qiang, ZHANG Maosheng, DONG Ying, MENG Xiaojie, GUO Xiaopeng, FENG Wei, HONG Bo, WANG Tao, LIU Wenhui, TIAN Zhongying, ZHANG Ge, LU Na. Refinement risk identification of loess geo-hazards based on DEM and remote sensing——Taking Mizhi County in the Loess Plateau of Northern Shaanxi as an example[J]. GEOLOGY IN CHINA, 2023, 50(3): 926-942. DOI: 10.12029/gc20220801001

    基于DEM和遥感的黄土地质灾害精细化风险识别——以陕北黄土高原区米脂县为例

    Refinement risk identification of loess geo-hazards based on DEM and remote sensing——Taking Mizhi County in the Loess Plateau of Northern Shaanxi as an example

    • 摘要:
      研究目的 黄土高原是中国地质灾害最严重的地区之一,精细化识别地质灾害隐患,掌握地质灾害风险底数,是有效精准防控黄土地质灾害的关键。
      研究方法 本文以陕北黄土高原区米脂县为例,基于2 m×2 m精度DEM数据识别崩塌滑坡易发坡段,采用0.2 m分辨率遥感数据识别危险坡段,以自然村为单元实地调查危险坡段并评价其风险,通过递进的方式开展了黄土地质灾害隐患识别、调查和评价,构建了县域尺度黄土地质灾害精细化风险识别技术方法体系。
      研究结果 结果表明:(1)米脂县共识别坡度大于40°、坡高大于20 m的崩塌滑坡易发坡段44716个,识别有威胁对象的危险坡段4198个;(2)通过风险识别、实地调查和评价,摸清了米脂县地质灾害隐患风险底数,米脂县共发育地质灾害风险点4406处,其中极高风险点11处、高风险点304处、中风险点1451处、低风险点2640处;(3)DEM和遥感识别风险点3880处,占风险点总数的88.06%,识别正确率92.42%;(4)2022年7—8月,米脂县人口居住区共有36处地质灾害风险点发生灾情或险情,全部位于本次风险识别范围之内,其中极高风险2处、高风险28处、中风险5处、低风险1处,极高风险点发生灾险情比例为18.18%,高风险点发生灾险情比例为9.21%,风险识别结果得到了有效验证。
      结论 研究成果显著减轻了米脂县地质灾害造成的损失,为黄土地质灾害有效精准防控提供了科学依据。

       

      Abstract:
      This paper is the result of geo-hazards survey engineering.
      Objective The Loess Plateau is one of the regions with the most serious geo-hazards in China. The key to effectively and accurately prevent and control the loess geo-hazards is to precisely identify the hidden geo-hazards dangers and thoroughly understand the number of geo-hazards risks.
      Methods This paper takes Mizhi County in the Loess Plateau region of northern Shaanxi as an example to perform the identification,investigation and evaluation of the hidden loess geo-hazards dangers step by step,and establish the system of refined risk identification technology method for the loess geo-hazards at the county level. The DEM data with resolution of 2 m×2 m is used to identify the slopes prone to induce collapses and landslides. The remote sensing data with resolution of 0.2 m is applied to identify the dangerous slopes. The natural village is taken as the unit to investigate the dangerous slopes and evaluate their risks.
      Results The results show that: (1) A total of 44716 landslide-prone slopes with inclination degree greater than 40° and height larger than 20 m and 4198 dangerous slopes with threatening objects were identified. (2) Through risk identification,field investigation and evaluation,the total number of geo-hazard risks in Mizhi County was thoroughly understand. There are 4406 geo-hazards risks,including 11 extremely high risks,304 high risks,1451 medium risks and 2640 low risks. (3) A number of 3880 risks accounting for 88.06% of the total risks were identified by the DEM and remote sensing with the identification accuracy of 92.42%. (4) From July to August 2022,36 geo-hazards risks occurred,which are within the scope of this risk identification including 2 extremely high risks,28 high risks,5 medium risks and 1 low risk. The proportion of disasters located at extremely high risks is 18.18%,and the proportion of disasters occurred at high risks is 9.21%. The results of risk identification have been effectively verified.
      Conclusions The research results significantly reduced the losses caused by geo-hazards in Mizhi County,and provided scientific references for effectively and accurately preventing and controlling the loess geo-hazards.

       

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