ISSN 1003-8035 CN 11-2852/P
    马明明,伍尚前,谢猛,等. 基于决策树分类的铁路沿线桉树提取及滑坡隐患识别−以贵广高铁广西段为例[J]. 中国地质灾害与防治学报,2024,35(0): 1-9. DOI: 10.16031/j.cnki.issn.1003-8035.202305047
    引用本文: 马明明,伍尚前,谢猛,等. 基于决策树分类的铁路沿线桉树提取及滑坡隐患识别−以贵广高铁广西段为例[J]. 中国地质灾害与防治学报,2024,35(0): 1-9. DOI: 10.16031/j.cnki.issn.1003-8035.202305047
    MA Mingming,WU Shangqian,XIE Meng,et al. Extraction of eucalyptus trees along railway lines based on decision tree classification and identification of potential landslides: A case study along Guangxi section of the Guizhou-Guangxi railway[J]. The Chinese Journal of Geological Hazard and Control,2024,35(0): 1-9. DOI: 10.16031/j.cnki.issn.1003-8035.202305047
    Citation: MA Mingming,WU Shangqian,XIE Meng,et al. Extraction of eucalyptus trees along railway lines based on decision tree classification and identification of potential landslides: A case study along Guangxi section of the Guizhou-Guangxi railway[J]. The Chinese Journal of Geological Hazard and Control,2024,35(0): 1-9. DOI: 10.16031/j.cnki.issn.1003-8035.202305047

    基于决策树分类的铁路沿线桉树提取及滑坡隐患识别以贵广高铁广西段为例

    Extraction of eucalyptus trees along railway lines based on decision tree classification and identification of potential landslides: A case study along Guangxi section of the Guizhou-Guangxi railway

    • 摘要: 桉树因生长习性特殊,会导致土壤的肥料和养分流失,引发土地退化,造成滑坡等地质灾害。广西地区气候条件适宜,区域内铁路沿线种植有大量桉树,致使铁路沿线存在滑坡隐患。为了对铁路沿线的滑坡隐患进行超前识别,本文以贵南高铁广西段为例,基于Landsat9 OLI、GF-7影像和DEM数据,使用决策树分类算法提取铁路沿线1 km缓冲区内桉树种植范围,再综合地形地貌等因素进行分析,识别出滑坡隐患。研究结果表明:1)本文构建的决策树分类算法较其他方法来说,分类精度有所提升,总体分类精度平均值达到87.19%,Kappa系数平均值达到0.80,表明该方法在研究区内能有效的提取出桉树的范围;2)贵南高铁广西段沿线大量种植桉树,桉树林呈片状分布在山丘地区,铁路沿线1 km缓冲区内桉树种植面积约为14.48 km2;3)研究区内桉树的种植对铁路的桥梁、路基和隧道口存在一定影响,本文识别出的滑坡隐患共33处,经过现场核查准确率达到86.84%。通过以上方法可有效地对铁路沿线桉树种植范围进行提取,综合地质因素后可做到滑坡隐患的超前识别,提高了铁路的行车安全。

       

      Abstract: The unique growth characteristics of Eucalyptus can result in the depletion of soil nutrient and fertilizers, leading to land degradation and geological hazards like landslides. The Guangxi region in China has suitable climatic conditions, and numerous Eucalyptus are strategically planted along railway lines, posing the risk of potential landslides. To proactively identify potential landslides along railway lines, this study takes the Guangxi section of the Guizhou-guangxi high-speed railway as a case study. Based on Landsat 9 OLI, GF-7 imagery, and DEM data, a decision tree classification algorithm is employed to extract the planting areas of Eucalyptus within a 1 km buffer zone along the railway. Then, comprehensive analysis incorporating terrain and landforms factors is conducted to identify potential landslides hazards. The research findings show that: 1) compared to other methods, the decision tree classification algorithm conducted in this study improves the classification accuracy, with an overall average classification accuracy of 87.19% and an average Kappa coefficient of 0.80, indicating that this method can effectively extract the range of Eucalyptus in the study area; 2) A large number of eucalyptus are planted along the Guangxi section of the Guinan high-speed railway, with eucalyptus distributed in patches in hilly areas. The eucalyptus planting area within the 1 km buffer zone along the railway is approximately 14.48 km2; 3) The planting of Eucalyptus in the study area has a certain impact on the bridges, emban kments, and tunnel entrances of the railway. A total of 33 potential landslides were identified in this study, with an accuracy rate of 86.84% through field verification. The above method can effectively extract the planting range of eucalyptus along the railway line, and combined with geological factors, it can proactively identify potential landslides, enhancing the safety of railway operation.

       

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