[1]郭长宝,等.基于证据权模型的川藏铁路加查--朗县段滑坡易发性评价[J].山地学报,2019,(02):240-251.[doi:10.16089/j.cnki.1008-2786.000418]
　GUO Changbao,TANG Jie,et al.Landslide Susceptibility Assessment Based on WOE Model along Jiacha-Langxian County Section of Sichuan -Tibet Railway, China[J].Mountain Research,2019,(02):240-251.[doi:10.16089/j.cnki.1008-2786.000418]
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基于证据权模型的川藏铁路加查--朗县段滑坡易发性评价()
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《山地学报》[ISSN:1008-2186/CN:51-1516]

卷:
期数:
2019年02期
页码:
240-251
栏目:
山地灾害
出版日期:
2019-04-25

文章信息/Info

Title:
Landslide Susceptibility Assessment Based on WOE Model along Jiacha-Langxian County Section of Sichuan -Tibet Railway, China
文章编号:
1008-2786-(2019)2-240-12
作者:
郭长宝1;  2; 唐 杰3; 吴瑞安1; 任三绍1
1.中国地质科学院地质力学研究所, 北京 100081; 2.活动构造与地壳稳定性评价重点实验室, 北京 100081; 3.中国地质大学(北京)地球科学与资源学院, 北京 100083
Author(s):
GUO Changbao1;  2;  TANG Jie3;  WU Ruian1;  REN Sanshao1
1. Institute of Geomechanics, Chinese Academy of Geological Sciences, Beijing 100081, China; 2. Key Laboratory of Active Tectonics and Crustal Stability Assessment, Beijing 100081, China; 3. China University of Geosciences, Beijing 100083, China;
关键词:
川藏铁路;  滑坡;  易发性评价;  地理信息系统;  证据权模型
Keywords:
Sichuan-Tibet Railway;  landslide;  susceptibility assessment;  geographic information system;  weight of evidence model
分类号:
P642.22
DOI:
10.16089/j.cnki.1008-2786.000418
文献标志码:
A
摘要:
川藏铁路加查至朗县段地处西藏自治区东南部,该区新构造活动强烈,地质构造复杂且历史强震频发,一系列大型-巨型滑坡在该区密集分布。本文基于滑坡遥感解译和野外地质灾害调查,建立了川藏铁路加查-朗县段的滑坡空间数据库,选取高程、坡度、坡向、平面曲率、地层岩性、距河流距离、距断裂带距离、距道路距离、植被归一化指数(NDVI)以及年平均降雨量等10个滑坡影响因子,基于ArcGIS软件平台和证据权模型,进行滑坡易发性评价。根据滑坡易发性指数(LSI)的分布特征,结合野外地质调查的认识,将研究区内的滑坡易发程度划分为4个级别,即极高易发区、高易发区、中易发区和低易发区,分别占研究区总面积的17.43%、22.64%、32.21%和27.72%。分析表明,极高易发区和高易发区主要分布在人类工程活动较多的研究区西南部,沿着雅鲁藏布江及其支流呈带状分布,中、低易发区主要分布在植被覆盖率较高、人类工程活动相对较少的东北部。极高易发区和高易发区内发育的滑坡数量约占已调查识别滑坡总数的88%,研究结果与已知滑坡的分布情况较吻合,采用成功率曲线对易发性评价结果进行检验,正确率达到了83%,具有较高的精度。易发性评价结果较好地反映了研究区内滑坡发育分布现状,可以为该区重大工程规划建设和防灾减灾提供理论指导和参考依据。
Abstract:
The Jiacha to Lang County section of Sichuan-Tibet Railway is located in the southeast of Tibet, China, where the neotectonic activities are intense. Lots of large-huge scale landslides are distributed in the study area with complex geological structures and high frequent historical strong earthquakes. Based on remote sensing interpretation and field investigation, the landslides spatial database was established along Jiacha to Lang County section of Sichuan-Tibet Railway. Adopting the ArcGIS software and the Weight Of Evidence model(WOE), 10 impact factors were selected to evaluate landslide susceptibility, such as elevation, slope degree, slope aspect, planform curvature, lithology, distance to rivers, distance to fault zones, distance to roads, normalized difference vegetation index(NDVI)and annual average rainfall. According to the distribution characteristics of landslide susceptibility index(LSI)and field investigation results, the study area was classified into four zones with different landslide susceptibility level: landslide extremely high-prone area, landslide high-prone area, landslide moderate-prone area, and landslide low-prone area, and each level zonation accounted for 17.43%, 22.64%, 32.21% and 27.72% of the study area individually. The research result showed that the landslide extremely high-prone area and high prone-area were mainly distributed in the southwestern part of the study area with more human engineering activities along the Yarlung Zangbo River, and the landslide moderate-prone area and low-prone area were mainly distributed in the northeastern part with high vegetation coverage and less human engineering activities. The number of landslides in landslide extremely high-prone areas and high-prone areas accounted for about 88% of the total landslides that had been investigated and identified. The research results were in good agreement with the distribution of known landslides. The success rate curve(ROC)was used to check the evaluation results, and the accuracy rate reached 83%. The landslide susceptibility evaluation results obtained in this paper better reflect the distribution and development of landslides in the study area, which can provide theoretical guidance and references for the planning and construction of major project and disaster prevention and mitigation.

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备注/Memo

备注/Memo:
收稿日期(Received date):2017-07-05; 改回日期(Accepted date):2019-02-10
基金项目(Foundation item):中国地质调查局项目(DD20190319,20190505,12120113038000); 国家自然科学基金项目(41731287,41877279)。[China Geological Survey Project(DD20190319,20190505,12120113038000); National Natural Science Foundation of China(41731287,41877279)]
作者简介(Biography):郭长宝(1980-),男,山东日照人,博士,副研究员,主要研究方向:工程地质与地质灾害。[GUO Changbao(1980-),male,born in Rizhao, Shandong province, Ph.D.,associate professor,specialized in engineering geology and geological hazards] E-mail:guochangbao@163.com
更新日期/Last Update: 2019-03-30