重庆万州龙驹坝地区滑坡灾害易发性分析

发布时间：2018-06-28 23:55

本文选题：滑坡易发性 + ArcGIS　；参考：《人民长江》2017年10期

【摘要】：基于对重庆市万州区龙驹坝地区地质灾害详细调查数据的综合分析,开展了滑坡灾害易发性区划评价研究。首先,通过对区内滑坡影响因子的提取分析,采用粗糙集方法,得到了控制滑坡易发性的三大类6个主要分项指标;进而,将各评价因子根据滑坡发育情况进行属性状态划分,得到相应的计算数值。最后选取BP神经网络模型评价方法,经过样本区数据选取、神经网络训练、易发性计算评价得出区内易发性结果,并利用Arc GIS的分类功能将滑坡的易发性分为4个级别:低易发区、中易发区、高易发区、极高易发区。结果表明:极高和高易发区主要分布在地质构造核部,与实际调查情况相符。研究结论对区内地质灾害防治工作具有实际意义。
[Abstract]:Based on the comprehensive analysis of the detailed investigation data of geological hazards in Longjuba area, Wanzhou District, Chongqing, the evaluation of the susceptibility of landslide hazards was carried out. First of all, by extracting and analyzing the influencing factors of landslide in the region, using rough set method, three main categories and six main sub-indexes are obtained to control the vulnerability of landslide, and then, according to the development of landslide, the evaluation factors are classified according to the attribute state. The corresponding calculated values are obtained. Finally, the BP neural network model evaluation method is selected. Through the sample area data selection, the neural network training, the vulnerability calculation evaluation results are obtained. According to the classification function of Arc, the susceptibility of landslide can be divided into four grades: low, middle, high and very high prone areas. The results show that the extremely high and high prone areas are mainly distributed in the core of geological structure, which is consistent with the actual investigation. The conclusions are of practical significance to the prevention and control of geological disasters in the area.
【作者单位】：中国地质大学(武汉)地质调查研究院;中国地质大学(武汉)工程学院;
【基金】：国家自然科学基金项目“顺层岩质滑坡宏观变形-启滑过程的能量学解析”(41572256) 长江上游宜昌-江津小流域龙驹坝幅地质灾害调查项目(12120113007600)
【分类号】：P642.22

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