基于信息量模型与Logistic回归模型耦合的山西吕梁市地质灾害易发性评价研究
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摘要
吕梁市位于山西省西部,近年来由于资源过度开采以及人类工程活动的加剧,引发了大量地质灾害,呈现出加剧趋势。所以,对吕梁市地质灾害进行易发性评价具有十分重要的现实意义。本文选取坡向、高程、道路、水系、工程岩组、坡体形态、坡度、植被、起伏度为评价指标,采用信息量法与Logistic回归耦合模型对吕梁市进行地质灾害易发性评价,并依据偏似然比检验结果检验指标的相关性,消除了因子间共线性影响。结果表明:耦合模型与信息量模型评价结果总体上一致,但是耦合模型的评价分区结果与灾害点的分布情况更加吻合;灾害高易发区多集中在750～1 500 m高程内、黄土地区以及距道路、水系1 km范围内。因此,本文基于耦合模型的评价结果,将吕梁市地质灾害易发性等级分为高易发区、中易发区、低易发区和不易发区,通过易发性等级区划为吕梁市减灾防灾工作提供了一定的参考。
Lyuliang City is located in the west of Shanxi Province and is rich in mineral resources. Due to the overexploitation of resources and the aggravation of human engineering activities in recent years, a large number of geological disasters have been triggered, showing an aggravating trend. Therefore, it is of great practical significance to evaluate the vulnerability of geological hazards in Lyuliang City. In this paper, slope direction, elevation, road, water system, engineering rock group, slope shape, slope, vegetation and fluctuation are selected as evaluation indexes. The information content method and Logistic regression coupling model are used to evaluate the vulnerability of geological hazards in Lyuliang City. The correlativity of the indexes is tested according to the results of the partial likelihood ratio test, and the collinearity between the factors is eliminated. The results indicate that the evaluation results of the coupling model and the information quantity model are consistent on the whole, but the evaluation results of the coupling model are more consistent with the distribution of disaster points; the disaster-prone areas are mostly concentrated in the 750～1 500 m elevation, the loess area and 1 km away from the road and water system. Therefore, we divide the geological hazard susceptibility grade of Lyuliang City into high-susceptible area, middle-susceptible area, low-susceptible area and non-susceptible area according to coupling model-based evaluation, which provides a certain reference for disaster reduction and prevention in Lyuliang City.
Lyuliang City is located in the west of Shanxi Province and is rich in mineral resources. Due to the overexploitation of resources and the aggravation of human engineering activities in recent years, a large number of geological disasters have been triggered, showing an aggravating trend. Therefore, it is of great practical significance to evaluate the vulnerability of geological hazards in Lyuliang City. In this paper, slope direction, elevation, road, water system, engineering rock group, slope shape, slope, vegetation and fluctuation are selected as evaluation indexes. The information content method and Logistic regression coupling model are used to evaluate the vulnerability of geological hazards in Lyuliang City. The correlativity of the indexes is tested according to the results of the partial likelihood ratio test, and the collinearity between the factors is eliminated. The results indicate that the evaluation results of the coupling model and the information quantity model are consistent on the whole, but the evaluation results of the coupling model are more consistent with the distribution of disaster points; the disaster-prone areas are mostly concentrated in the 750～1 500 m elevation, the loess area and 1 km away from the road and water system. Therefore, we divide the geological hazard susceptibility grade of Lyuliang City into high-susceptible area, middle-susceptible area, low-susceptible area and non-susceptible area according to coupling model-based evaluation, which provides a certain reference for disaster reduction and prevention in Lyuliang City.
引文
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[13] 阮沈勇,黄润秋. 基于GIS的信息量法模型在地质灾害危险性区划中的应用[J]. 成都理工大学学报,2001,28(1):89- 92.
[14] 廖芸婧. 安微省歙县地质灾害易发性区划与气象预警研究[D]. 成都:成都理工大学,2015.
[2] 国土资源部.县(市)地质灾害调查与区划基本要求实施细则(修订稿)[Z]. 北京:国土资源部,2006.
[3] LEE S. Application of Logistic regression model and its validation for landslide susceptibility mapping using GIS and remote sensing date[J]. International Journal of Remote Sensing,2005,26(7):1477- 1491.
[4] GUZZETTI F,CARRARA A,CARDINALI M,et al. Landslide hazard evaluation:a review of current techniques and their appalication in a muli-scale study,Central Italy[J]. Geomorphology,1999,31(1):181- 216.
[5] 许冲,戴福初,姚鑫. 基于GIS的汶川地震滑坡灾害影响因子确定性系数分析[J]. 岩石力学与工程学报,2010,29(S1):2972- 2981.
[6] 刘明学,陈祥,杨珊妮,等. 基于逻辑回归模型和确定性系数的崩滑流危险性区划[J]. 工程地质学报,2014,22(6):1250- 1256.
[7] 范强,巨能攀,向喜琼,等. 基于结果验证的信息量法地质灾害易发性评价——以贵州省为例[J]. 工程地质学报,2014,22(3):65- 68.
[8] 徐为,李铁峰,胡瑞林,等. 基于GIS的哀牢山戛洒镇小流域滑坡易发性评价[J]. 水文地质工程地质,2011,38(5):110- 114.
[9] 胡凯衡,崔鹏,赵本山. 基于聚类和最大似然法的汶川灾害泥石流滑坡易发性评价[J]. 中国水土保持学报,2012, 24(1):12- 18.
[10] 刘洋,唐川,冯毅,基于AHP—信息量法的地质灾害危险性评价[J]. 地球与环境,2013,41(2):173- 179.
[11] 邓辉,何政,伟陈晔. 信息量模型在山地环境地质灾害危险性评价中的应用——以四川泸定县为例[J]. 自然灾害学报,2014,23(2):67- 76.
[12] 许冲,徐锡伟. 逻辑斯回归模型在玉树地震滑坡危险性评价中的应用与检验[J]. 工程地质学报,2012,20(3):326- 333.
[13] 阮沈勇,黄润秋. 基于GIS的信息量法模型在地质灾害危险性区划中的应用[J]. 成都理工大学学报,2001,28(1):89- 92.
[14] 廖芸婧. 安微省歙县地质灾害易发性区划与气象预警研究[D]. 成都:成都理工大学,2015.