我国西南地区地质灾害频发,为了探索该区域地质灾害的分布特征,以内江市为研究区,利用遥感卫星影像及地理国情监测数据,从自然地理、生态条件和基础地质3个方面建立生态地质环境评价指标体系。采用层次分析法(AHP)和二元Logistic回归模型分别确定各评价指标的主、客观权重,再用最小信息熵求出两者的综合权重,在GIS支持下建立地质灾害评价模型,对内江市地质灾害进行风险性评价分级;并通过高权重评价因子与历史地质灾害点的空间结构分析,揭示其空间分布特征及规律。评估结果表明:①内江市地质灾害中高易发区主要分布在西部低山区,占全区总面积的28.93%;②海拔和坡度是导致地质灾害发生的主要影响因子,在海拔较高、坡度较陡地区,且山区公路两旁极易发生地质灾害,沉寂式构造线附近地层相对稳定。
Abstract
In an attempt to probe into the distribution of geological disasters in southwest China where geological disasters happen frequently, we built an index system for assessing the eco-geological environment of Neijiang City as a case study based on remotely sensed images and geographical monitoring data. The index system includes factors of natural geography, ecological condition, and fundamental geology. Furthermore, the subjective weight and objective weight of each index were determined by analytic hierarchy process (AHP) and dichotomous Logistic regression model; and the combinatorial weight was synthesized according to minimum relative information entropy principle. The evaluation model of geological hazard was hence established with the support of GIS to evaluate the risk of geological disasters in Neijiang City. The distribution characteristics and laws of geological disaster was acquired by spatial analysis using higher weight coefficients and the corresponding historical geological disaster points. Results show that the low mountainous area in the west of Neijiang, which accounts for 28.93% of the total area, is highly susceptible to geological disasters. Altitude and slope gradient are major influential factors that induce geological disasters; geological disasters are highly prone to occur in high-altitude and steep-slope areas on both sides of highway, whereas in the adjacent of quiet tectonic line the geological formation is relatively stable.
关键词
地质灾害 /
风险性评估 /
层次分析法(AHP) /
Logistic回归模型 /
最小信息熵 /
内江市
Key words
geological disaster /
risk assessment /
analytic hierarchy process (AHP) /
Logistic regression model /
minimum information entropy /
Neijiang City
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基金
深圳国际合作研究项目(GJHZ20160229194322570);中科院西部之光项目(2016-QNXZ-A-5)
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