基于加权信息量模型的云南澜沧县滑坡危险性评价

吴兴贵; 王宇栋; 王蓝婷; 丁梓逸

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

doi: 10.16031/j.cnki.issn.1003-8035.202210013

昆明理工大学公共安全与应急管理学院，云南昆明　650093

详细信息

作者简介:
吴兴贵（1997-），女，重庆南川人，硕士，安全工程专业。E-mail：2839666766@qq.com

通讯作者:
王宇栋（1973-），男，云南昆明人，博士，副教授，主要研究地灾规划，大数据挖掘与安全可视化。E-mail：584772219@qq.com

计量
- 文章访问数: 44
- HTML全文浏览量: 31
- PDF下载量: 28
- 被引次数: 0
出版历程
- 收稿日期: 2022-10-11
- 录用日期: 2023-05-04
- 修回日期: 2023-04-11
- 网络出版日期: 2023-05-19

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

Faculty of Public Safety and Emergency Management, Kunming University of Science and Technology, Kunming　650093

摘要

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。
- 滑坡 /
- 熵权法 /
- 信息量模型 /
- 危险性评价 /
- 澜沧县
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.
- landslide /
- Entropy weight method /
- Information volume model /
- Risk assessment /
- Lancang County

HTML全文

图 1 研究区位置与滑坡灾害点分布

Figure 1. Location of the study area and distribution of landslide hazard sites

下载: 全尺寸图片幻灯片

图 2 滑坡危险评价因子分级图

Figure 2. Classification diagram of landslide risk evaluation factors

下载: 全尺寸图片幻灯片

图 3 指标分级与滑坡相对点密度柱状图

Figure 3. Histogram of indicator classification and relative point density of landslide

下载: 全尺寸图片幻灯片

图 4 滑坡危险性分区图

Figure 4. Landslide hazard zoning map

下载: 全尺寸图片幻灯片

图 5 危险性评价结果的ROC曲线

Figure 5. FIG. 5 ROC curve of hazard assessment results

下载: 全尺寸图片幻灯片

表 1 数据来源

Table 1. Summary of Data source

数据名称	数据来源	数据名称	数据来源
滑坡灾害点	澜沧县地质灾害详查	DEM数据	地理空间数据云
地质图	全国地质资料馆	降雨量	中国气象数据网
道路数据	91卫图助手	植被覆盖数据	地理空间数据云

下载: 导出CSV

表 2 指标统计计算结果

Table 2. Statistical calculation results of indicators

因子	因子二级属性	滑坡点个数	栅格数量	信息量I_i	相对点密度D_i	归一化X_i	Hi	Wi
高程/m	492～1 099	20	1 224 511	−0.076	0.927	0.196	0.921	0.174
	1 099～1 366	33	2 536 591	−0.303	0.738	0.156
	1 366～1 623	54	2 684 074	0.133	1.142	0.241
	1 623～1 910	58	1 991 079	0.503	1.653	0.350
	1 910～2 530	6	1 268 180	−1.315	0.269	0.057
坡度/（°）	0～10	24	1 453 076	−0.065	0.937	0.171	0.984	0.034
	10～20	75	3 730 552	0.132	1.141	0.208
	20～30	47	3 223 642	−0.189	0.827	0.151
	30～40	20	1 114 820	0.018	1.018	0.186
	>40	5	182 345	0.442	1.556	0.284
坡向	北	18	1 267 813	−0.216	0.806	0.102	0.967	0.072
	东北	38	1 404 853	0.429	1.535	0.195
	东	9	1 199 159	−0.853	0.426	0.054
	东南	14	1 116 898	−0.341	0.711	0.090
	南	29	1 195 808	0.319	1.376	0.175
	西南	25	1 283 120	0.101	1.106	0.140
	西	14	1 112 242	−0.336	0.714	0.091
	西北	24	1 124 542	0.192	1.211	0.154
地层岩性	松散岩（土）体	3	91 136	0.625	1.868	0.306	0.911	0.197
	软弱岩层	7	197 943	0.697	2.007	0.329
	较软弱岩层	30	2 174 744	−0.245	0.783	0.128
	较坚硬岩层	128	6 776 327	0.070	1.072	0.176
	坚硬岩层	3	464 285	−1.003	0.367	0.060
距断裂距离/m	0～1 000	44	1 912 260	0.267	1.306	0.282	0.971	0.065
	1 000～2 000	29	1574 153	0.044	1.046	0.226
	2 000～3 000	16	1 187 454	−0.268	0.765	0.165
	3 000～4 000	8	917 368	−0.703	0.495	0.107
	>4 000	74	4 113 200	0.021	1.021	0.220
植被覆盖度	0～0.19	33	900 995	0.732	2.079	0.329	0.897	0.228
	0.19～0.45	45	1 291 011	0.682	1.978	0.313
	0.45～0.66	38	1 846 666	0.155	1.168	0.185
	0.66～0.84	41	2 895 125	−0.219	0.804	0.127
	0.84～0.1	14	2 770 638	−1.249	0.287	0.045
距道路距离/m	0～500	19	480 354	0.809	2.245	0.358	0.950	0.111
	500～1 000	11	458 280	0.309	1.362	0.217
	1 000～1 500	7	433 124	−0.086	0.917	0.146
	1 500～2 000	6	413 798	−0.195	0.823	0.131
	>2 000	128	7 918 879	−0.086	0.917	0.146
降雨量/mm	1 212.3～1 313.2	41	1 166 233	0.691	1.995	0.356	0.947	0.119
	1 313.2～1 382.0	35	1 524 128	0.265	1.303	0.233
	1 382.0～1 435.2	27	1 962 908	−0.248	0.781	0.139
	1 435.2～1 485.8	38	2 637 049	−0.201	0.818	0.146
	1 485.8～1 545.5	30	2 414 117	−0.349	0.705	0.126

下载: 导出CSV

表 3 分区统计结果

Table 3. Statistical results of zoning

危险性等级	面积/km²	面积比例/%	滑坡点 /个	滑坡点比例/%	滑坡相对点密度
高危险区	1549.72	17.91	84	49.12	2.74
较高危险区	3280.77	37.91	63	36.84	0.97
中危险区	2244.93	25.94	19	11.11	0.43
低危险区	1579.76	18.25	5	2.92	0.16

下载: 导出CSV

参考文献(19)

[1]	李益敏,袁静,蒋德明,等. 基于GIS的西南高山峡谷区滑坡风险性评价—以怒江州泸水市为例[J]. 西北师范大学学报(自然科学版),2021,57(6):94 − 102. [LI Yimin,YUAN Jing,JIANG Deming,et al. Risk assessment of landslide disasters in alpine canyon area based on GIS:Taking Lushui City,Nujiang Prefecture as an example[J]. Journal of Northwest Normal University (Natural Science),2021,57(6):94 − 102. (in Chinese with English abstract)
[2]	屠水云,张钟远,付弘流,等. 基于CF与CF-LR模型的地质灾害易发性评价[J]. 中国地质灾害与防治学报,2022,33(2):96 − 104. [TU Shuiyun,ZHANG Zhongyuan,FU Hongliu,et al. Geological hazard susceptibility evaluation based on CF and CF-LR model[J]. The Chinese Journal of Geological Hazard and Control,2022,33(2):96 − 104. (in Chinese with English abstract) doi: 10.16031/j.cnki.issn.1003-8035.2022.02-12
[3]	杨华阳,许向宁,杨鸿发. 基于证据权法的九寨沟地震滑坡危险性评价[J]. 中国地质灾害与防治学报,2020,31(3):20 − 29. [YANG Huayang,XU Xiangning,YANG Hongfa. The Jiuzhaigou co-seismic landslide hazard assessment based on weight of evidence method[J]. The Chinese Journal of Geological Hazard and Control,2020,31(3):20 − 29. (in Chinese with English abstract) doi: 10.16031/j.cnki.issn.1003-8035.2020.03.03
[4]	管新邦. 云南省滑坡地质灾害危险性评价研究[D]. 北京: 中国矿业大学（北京） GUAN Xinbang. Study on risk assessment of landslide geological hazards in Yunnan Province[D]. Beijing: China University of Mining & Technology, Beijing. （in Chinese with English abstract）
[5]	孙长明,马润勇,尚合欣,等. 基于滑坡分类的西宁市滑坡易发性评价[J]. 水文地质工程地质,2020,47(3):173 − 181. [SUN Changming,MA Runyong,SHANG Hexin,et al. Landslide susceptibility assessment in Xining based on landslide classification[J]. Hydrogeology & Engineering Geology,2020,47(3):173 − 181. (in Chinese with English abstract)
[6]	温鑫,范宣梅,陈兰,等. 基于信息量模型的地质灾害易发性评价—以川东南古蔺县为例[J]. 地质科技通报,2022,41(2):290 − 299. [WEN Xin,FAN Xuanmei,CHEN Lan,et al. Susceptibility assessment of geological disasters based on an information value model:A case of Gulin County in Southeast Sichuan[J]. Bulletin of Geological Science and Technology,2022,41(2):290 − 299. (in Chinese with English abstract)
[7]	申怀飞,董雨,杨梅,等. 基于AHP与信息量法的甘肃省滑坡易发性评估[J]. 水土保持研究,2021,28(6):412 − 419. [SHEN Huaifei,DONG Yu,YANG Mei,et al. Assessment on landslide susceptibility in Gansu Province based on AHP and information quantity method[J]. Research of Soil and Water Conservation,2021,28(6):412 − 419. (in Chinese with English abstract) doi: 10.13869/j.cnki.rswc.2021.06.034
[8]	孙滨,祝传兵,康晓波,等. 基于信息量模型的云南东川泥石流易发性评价[J]. 中国地质灾害与防治学报,2022,33(5):119 − 127. [SUN Bin,ZHU Chuanbing,KANG Xiaobo,et al. Susceptibility assessment of debris flows based on information model in Dongchuan,Yunnan Province[J]. The Chinese Journal of Geological Hazard and Control,2022,33(5):119 − 127. (in Chinese with English abstract) doi: 10.16031/j.cnki.issn.1003-8035.202204003
[9]	杜国梁,杨志华,袁颖,等. 基于逻辑回归-信息量的川藏交通廊道滑坡易发性评价[J]. 水文地质工程地质,2021,48(5):102 − 111. [DU Guoliang,YANG Zhihua,YUAN Ying,et al. Landslide susceptibility mapping in the Sichuan-Tibet traffic corridor using logistic regression-information value method[J]. Hydrogeology & Engineering Geology,2021,48(5):102 − 111. (in Chinese with English abstract)
[10]	王夏林,严宝文. 基于熵权的可拓理论在地灾危险性评价中的应用[J]. 人民长江,2012,43(21):70 − 74. [WANG Xialin,YAN Baowen. Application of entropy weight based extension theory in risk assessment of geological hazards[J]. Yangtze River,2012,43(21):70 − 74. (in Chinese with English abstract) doi: 10.3969/j.issn.1001-4179.2012.21.019
[11]	周苏华,付宇航,徐智文,等. 基于主客观赋权法的福建省地质灾害易发性评价[J]. 安全与环境学报,2022:1 − 12. [ZHOU Suhua,FU Yuhang,XU Zhiwen,et al. Evaluation of geological disaster susceptibility in Fujian Province based on subjective and objective weighting method[J]. Journal of Safety and Environment,2022:1 − 12. (in Chinese)
[12]	KHATUN M,HOSSAIN A T M S,SAYEM H M,et al. Landslide susceptibility mapping using weighted-overlay approach in rangamati,Bangladesh[J]. Earth Systems and Environment,2023,7(1):223 − 235. doi: 10.1007/s41748-022-00312-2
[13]	CHEN W,CHAI H C,SUN X Y,et al. A GIS-based comparative study of frequency ratio,statistical index and weights-of-evidence models in landslide susceptibility mapping[J]. Arabian Journal of Geosciences,2016,9(3):204. doi: 10.1007/s12517-015-2150-7
[14]	刘福臻,王灵,肖东升,等. 基于模糊综合评判法的宁南县滑坡易发性评价[J]. 自然灾害学报,2021,30(5):237 − 246. [LIU Fuzhen,WANG Ling,XIAO Dongsheng,et al. Evaluation of landslide susceptibility in Ningnan County based on fuzzy comprehensive evaluation[J]. Journal of Natural Disasters,2021,30(5):237 − 246. (in Chinese with English abstract)
[15]	向喜琼,黄润秋. 地质灾害风险评价与风险管理[J]. 地质灾害与环境保护,2000,11(1):38 − 41. [XIANG Xiqiong,HUANG Runqiu. Risk assessment and risk management for slope geohazards[J]. Journal of Geological Hazards and Environment Preservation,2000,11(1):38 − 41. (in Chinese with English abstract)
[16]	崔阳阳. 基于不同评价单元的滑坡易发性评价方法研究—以陕西省洛南县为例[D]. 西安: 西安科技大学 CUI Yangyang. Study on evaluation method of landslide susceptibility based on different evaluation units— a case study of Luonan County, Shaanxi Province[D]. Xi'an: Xi’an University of Science and Technology. （in Chinese with English abstract）
[17]	汤国安, 刘学军, 闾国年. 21世纪高等院校教材数字高程模型及地学分析的原理与方法[M]. 21世纪高等院校教材数字高程模型及地学分析的原理与方法, 2005 Tang Guoan, Liu Xuejun, Lu Guonian. Principles and Methods of Digital Elevation Model and Geoscience Analysis of University Textbooks in 21st Century [M]. Principles and Methods of Digital Elevation Model and Geoscience Analysis of University Textbooks in 21st Century, 2005. （in Chinese ）
[18]	朱晓霞,张力,杨树文. 降雨引发的兰州黄土滑坡时空规律分析和临界降雨量预测[J]. 中国地质灾害与防治学报,2019,30(4):24 − 31. [ZHU Xiaoxia,ZHANG Li,YANG Shuwen. Characteristics of rainfall-induced loess landslides and their threshold rainfall in Lanzhou[J]. The Chinese Journal of Geological Hazard and Control,2019,30(4):24 − 31. (in Chinese with English abstract) doi: 10.16031/j.cnki.issn.1003-8035.2019.04.04
[19]	韩玲,张庭瑜,张恒. 基于IOE和SVM模型的府谷镇滑坡易发性分区[J]. 水土保持研究,2019,26(3):367 − 372. [HAN Ling,ZHANG Tingyu,ZHANG Heng. Landslide susceptibility mapping based on IOE and SVM model in Fugu town[J]. Research of Soil and Water Conservation,2019,26(3):367 − 372. (in Chinese with English abstract)