基于GIS与信息量模型的汶川次生地质灾害危险性评价

5·12汶川大地震诱发了大量滑坡、崩塌、泥石流等次生地质灾害，对人民群众的生命财产和社会经济的发展形成了严重威胁.针对次生地质灾害危险性评价，选取重灾区汶川县作为研究区域，利用遥感与地理信息技术的空间数据管理和空间数据分析平台，获取了研究区的次生地质灾害信息，分析了研究区内次生地质灾害与各影响因子，包括地形地貌、地层岩性、水系、地震断裂之间的相关性特征，并结合信息量法模型进行次生地质灾害危险性评价.高度、中度和轻度危险区的面积分别为1 130.196 km2、1 739.584 km2、1 213.219 km2.本次地震触发次生地质灾害的分布具有集群式分布的特点，即断裂带及其附近地区地质灾害集中发育，而远离断裂带区地质灾害很快衰减，呈零星分布；从灾害发育的区域特征分析，汶川县震后次生地质灾害呈现出北部和东部重、西部和南部轻的特点.所得研究结果与实际情况较吻合，表明地理信息系统结合信息量模型能够快速、有效地对次生地质灾害的空间分布以及危险性作出评价. 

Hazard Evaluation of Secondary Geological Disaster Based on GIS and Information Value Method

5·12 Wenchuan earthquake triggered a series of secondary landslides, landslides, debris flows, and other geological disasters, which posed a major threat to peoples' lives and property and socio-economic development. For risk assessment of secondary geological hazards in the area, the worst-hit Wenchuan County was selected as the study area. Remote sensing and geographic information technology spatial data management and spatial data analysis platform have been applied to gain relevant information, to make a correlative analysis between secondary geological disasters in the study area and the topography, lithology, hydrology, earthquake rupture. In addition, information value method has been used to evaluate the risk of secondary geological disasters. It is found that the area of high risk, moderate risk and low risk is 1 130.196 km2, 1 739.584 km2, 1 213.219 km2 respectively. The distribution of secondary geology disaster triggered by earthquake has the colony type distribution characteristic featured with a concentrated development of geological disasters in the fault zone and the nearby regions and a quick decay and the fragmentary distribution farther away form the fault zone areas. Analysis also shows that risk of secondary geological disaster in north and east areas of Wenchuan is heavy, while that in the west and south areas is light, which is coincident with the reality. The study further demonstrates that the geographical information system combined with information value model can quickly and effectively evaluate the spatial distribution and risk of secondary geological disasters.