[1]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(06):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(06):412-419.
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基于AHP与信息量法的甘肃省滑坡易发性评估

《水土保持研究》[ISSN:1005-3409/CN:61-1272/P] 卷: 28 期数: 2021年06期 页码: 412-419 栏目: 出版日期: 2021-10-10
Title:
Assessment on Landslide Susceptibility in Gansu Province Based on AHP and Information Quantity Method
文章编号:
1005-3409(2021)06-0412-08
作者:
申怀飞，董 雨，杨 梅，施采琦，杨欣柯
(许昌学院 城市与环境学院，河南 许昌 461000)
Author(s):
SHEN Huaifei，DONG Yu，YANG Mei，SHI Caiqi，YANG Xinke
(School of Urban and Environmental Sciences，Xuchang University，Xuchang，Henan 461000，China)
关键词:
地质学;  易发性评估;  层次分析法;  信息量法;  甘肃省
Keywords:
geology;  susceptibility assessment;  analytic hierarchy process(AHP);  information value method;  Gansu Province
分类号:
P954
文献标志码:
A
摘要:
甘肃省是我国滑坡灾害频发地区之一，该地居民的生命财产和生态环境遭受威胁，为降低该省受灾程度，提高人们对滑坡灾害的防范意识，对甘肃省滑坡灾害防治提供理论依据，该文参考国内外滑坡灾害风险评估指标及方法，分别从甘肃省地理环境、地质情况、人类活动等方面选取10项滑坡灾害风险影响指标，基于层次分析法与信息量模型得到的各指标权重值及信息量值，对该省滑坡易发性进行综合评估，得到结果如下:极高易发区面积占研究区总面积的4.336%，滑坡灾害密度达12.870; 高易发区面积占15.243%，滑坡灾害密度达9.392; 中易发区面积占47.544%，滑坡灾害密度达2.041; 低易发区面积占32.875%，滑坡灾害密度为0.074; 极低易发区面积占0.003%，滑坡灾害密度为0。甘肃省大部分区域滑坡易发性较小，滑坡灾害易发性空间分布呈现集中分布特征，主要集中在东南部地区，且多位于人口密度较高、交通线较密集地区。
Abstract:
Gansu Province is one of the areas where landslide disasters occur frequently in China，and the lives，property and ecological environment of residents in this area are threatened. In order to reduce the disaster degree of the province，improve people's awareness of landslide disaster prevention，and provide theoretical basis for landslide disaster prevention in Gansu Province，we selected ten landslide disaster risk impact indicators from the geographical environment，geological conditions，human activities and other aspects of Gansu Province，and comprehensively evaluated the landslide susceptibility of Gansu Province based on the AHP and information quantity value of each indicator obtained by using the analytic hierarchy process and information quantity model throught referring to the risk assessment indicators and methods of landslide disasters at home and abroad. The results are as follows. The area of extremely high prone area accounted for 4.336% of the total area of the study area，and the density of landslide disaster was 12.870. The area of high prone area accounted for 15.243%，and the density of landslide disaster was 9.392. The area of middle prone area was 47.544%，and the density of landslide disaster was 2.041. The area of low-prone area accounted for 32.875%，and the density of landslide disaster was 0.074. The area of extremely low prone area accounted for 0.003%，and the density of landslide disaster was 0. The landslide vulnerability is relatively small in most regions of Gansu Province，and the spatial distribution characteristics of landslide disaster vulnerability are concentrated. Landslide disaster vulnerability mainly concentrate in the southeast region，and most of landslide disaster vulnerabilities are located in the areas with high population density and dense transportation lines.

参考文献/References:

[1] 张俊.三峡库区万州区滑坡灾害风险评估研究[D].武汉:中国地质大学，2016.
[2] 石菊松.基于遥感和地理信息系统的滑坡风险评估关键技术研究[D].北京:中国地质科学院，2008.
[3] Wicaksono Y S，Sihombing F，Indra T L. Landslide susceptibility map of Bogor Area using analytical hierarchy process[J]. IOP Conference Series: Earth and Environmental Science，2020，538(1):1-10.
[4] Batista E F，Larissa D，Kormann A. Methodologies of economic measurement and vulnerability assessment for Application in Landslide Risk Analysis in a Highway Domain Strip: A case study in the Serra Pelada Region(Brazil)[J]. Sustainability，2019，11(21):1-22.
[5] Ram P，Gupta V，Devi M，et al. Landslide susceptibility mapping using bivariate statistical method for the hilly township of Mussoorie and its surrounding areas，Uttarakhand Himalaya[J]. Journal of Earth System Science，2020，129(1):1-18.
[6] Dikshit A，Sarkar R，Pradhan B，et al. Spatial landslide risk assessment at Phuentsholing，Bhutan[J]. Geosciences，2020，10(4):1-16.
[7] Fressard M，Thiery Y，Maquaire O. Which data for quantitative landslide susceptibility mapping at operational scale? Case study of the Pays d'Auge plateau hillslopes(Normandy，France)[J]. Natural hazards and earth system sciences，2014，14(3):569-588.
[8] Mousavi S M，Omidvar B，Ghazban F，et al. Quantitative risk analysis for earthquake-induced landslides—Emamzadeh Ali，Iran[J]. Engineering Geology，2011，122(3-4):191-203.
[9] Mandal B，Mandal S. Analytical hierarchy process(AHP)based landslide susceptibility mapping of Lish river basin of eastern Darjeeling Himalaya，India[J]. Advances in Space Research，2018，62(11):3114-3132.
[10] Kayastha P，Dhital M R，Smedt F D. Application of the analytical hierarchy process(AHP)for landslide susceptibility mapping: A case study from the Tinau watershed，west Nepal[J]. Computers & geosciences，2013，52(MAR.):398-408.
[11] 吴树仁，石菊松，张春山，等.地质灾害风险评估技术指南初论[J].地质通报，2009，28(8):995-1005.
[12] 向喜琼.区域滑坡地质灾害危险性评价与风险管理[D].成都:成都理工大学，2005.
[13] 常建娥，蒋太立.层次分析法确定权重的研究[J].武汉理工大学学报:信息与管理工程版，2007，29(1):153-156.
[14] 朱良峰，吴信才，殷坤龙，等.基于信息量模型的中国滑坡灾害风险区划研究[J].地球科学与环境学报，2004，26(3):52-56.
[15] 孙强，张泰丽，伍剑波，等.基于GIS与层次分析法的龙溪流域滑坡风险评价[J].华东地质，2018，39(3):227-233.
[16] 廖祥东，黄锐，杨连旗，等.十堰市某滑坡风险分析评价[J].资源环境与工程，2020，34(3):388-395.
[17] Saleem N，Huq M E，Twumasi N Y D，et al. Parameters derived from and/or used with digital elevation models(DEMs)for landslide susceptibility mapping and landslide risk assessment:a review[J]. Isprs International Journal of Geo-Information，2019，8(12):1-27.
[18] 陈香，王瑞.福建省滑坡灾害风险管理决策系统构建[J].灾害学，2016，31(2):47-52.
[19] 裴艳茜，邱海军，胡胜，等.“一带一路”地区滑坡灾害风险评估[J].干旱区地理，2018，41(6):1225-1240.
[20] 冯立，张茂省，张成航，等.四川虹口黑泥湾滑坡风险性评估[J].西北地质，2014，47(3):165-176.
[21] 黎志恒，文宝萍，贾贵义，等.甘肃省白龙江流域滑坡分布规律及其主控因素[J].兰州大学学报:自然科学版，2015，51(6):768-776.
[22] 彭令，牛瑞卿，赵艳南，等.区域滑坡灾害风险评估:以长江三峡库区秭归县为例[J].吉林大学学报:地球科学版，2013，43(3):891-901.
[23] 乔建平，王萌，吴彩燕.汶川8.0级地震灾区滑坡风险评估方法[J].灾害学，2016，31(1):55-59.
[24] 彭令，徐素宁，彭军还.多源遥感数据支持下区域滑坡灾害风险评价[J].吉林大学学报:地球科学版，2016，46(1):175-186.
[25] 蓝天助，何永强，毕永辉.甘肃南部某滑坡地质灾害危险性评估[J].山西建筑，2015，41(15):59-60.
[26] 熊俊楠，朱吉龙，苏鹏程，等.基于GIS与信息量模型的溪洛渡库区滑坡危险性评价[J].长江流域资源与环境，2019，28(3):700-711.
[27] 樊晓一，乔建平，陈永波.层次分析法在典型滑坡危险度评价中的应用[J].自然灾害学报，2004，13(1):72-76.
[28] 刘力维，程传周.基于GIS的滑坡泥石流风险评估及其应用[J].地理空间信息，2014，12(3):8-10.
[29] 陈齐.基于GIS的闽江上游滑坡敏感性评价研究[D].福州:福建师范大学，2016.

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备注/Memo

收稿日期:2020-10-24 修回日期:2020-11-07
资助项目:河南省教育厅人文社会科学研究项目(2020-ZZJH-426); 河南省高等学校重点科研项目(21A170019); 许昌学院优秀青年骨干教师项目; 许昌学院重点科研项目(2020ZD004)
第一作者:申怀飞(1979—)，男，河南淅川县人，博士，副教授，主要从事资源环境遥感及3S综合应用研究。E-mail:hfshen329@163.com

更新日期/Last Update: 2021-10-10