ISSN 1003-8035 CN 11-2852/P
    吴兴贵,王宇栋,王蓝婷,等. 基于加权信息量模型的云南澜沧县滑坡危险性评价[J]. 中国地质灾害与防治学报,2023,34(0): 1-10. DOI: 10.16031/j.cnki.issn.1003-8035.202210013
    引用本文: 吴兴贵,王宇栋,王蓝婷,等. 基于加权信息量模型的云南澜沧县滑坡危险性评价[J]. 中国地质灾害与防治学报,2023,34(0): 1-10. DOI: 10.16031/j.cnki.issn.1003-8035.202210013
    WU Xinggui,WANG Yudong,WANG Lanting,et al. Hazard assessment of landslides in Lancang County, Yunnan Province based on weighted information value model[J]. The Chinese Journal of Geological Hazard and Control,2023,34(0): 1-10. DOI: 10.16031/j.cnki.issn.1003-8035.202210013
    Citation: WU Xinggui,WANG Yudong,WANG Lanting,et al. Hazard assessment of landslides in Lancang County, Yunnan Province based on weighted information value model[J]. The Chinese Journal of Geological Hazard and Control,2023,34(0): 1-10. DOI: 10.16031/j.cnki.issn.1003-8035.202210013

    基于加权信息量模型的云南澜沧县滑坡危险性评价

    Hazard assessment of landslides in Lancang County, Yunnan Province based on weighted information value model

    • 摘要: 云南澜沧县位于滇西经向构造带中,在构造运动强烈,人类活动日益增加背景下,滑坡灾害发育,人民生命财产受到严重威胁,因此,对该区域进行滑坡危险性评价研究具有重要意义。以澜沧县滑坡数据为基础,选取高程、坡度、坡向、地层岩性、距断层距离,植被覆盖度,距道路距离,降雨量共8个评价因子,构建滑坡危险性评价指标体系。基于熵权法与信息量耦合模型,利用ArcGIS地理空间分析对研究区滑坡危险进行定性、定量评价并分区。结果显示:高危险区,面积占比17.91%,较高危险区占37.91%,中危险区占25.94%,低危险区占18.25%。经检验评价结果合理,加权信息量模型适用于滑坡危险性评价。

       

      Abstract: Lancang county is located in the longitudinal tectonic zone of western Yunnan, where landslides are frequently developed by strong tectonic movement and increasing human activities, thus posing a significant threat to the safety and security of the local population. Therefore, it is of great significance to assess the landslide risk in this area. To construct a landslide risk evaluation index system, data on previous landslides in Lancang county was analyzed, and eight control factors were selected, including elevation, slope, slope direction, stratigraphic lithology, distance from fault, vegetation coverage, distance from road and rainfall. By using the entropy weight method and information coupling value model, the landslide risk in the study area was qualitatively and quantitatively evaluated, and ArcGIS geospatial analysis was used to partition the results. According to the assessment, high-risk areas accounted for 17.91% of the total area, relatively high-risk areas accounted for 37.91%, moderate-risk areas accounted for 25.94%, and low-risk areas accounted for 18.25%.The evaluation results were deemed reasonable, and the entropy weight method and information coupling value model were found to be appropriate for landslide hazard assessment in the region.

       

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