In this study, Dempster–Shafer theory (DST) is integrated into a geographic information system to model vulnerability of the land surface to earthquake events in northwestern Kermanshah Province, Iran, to predict where damage is most likely to occur. DST has never been used to spatially model earthquake vulnerability. To achieve this, data layers for several environmental attributes—aspect, elevation, lithology, slope angle, land use, distance from river courses, distance from roads, and distance from faults—were compiled in ArcGIS 10.2.2 software. Using membership functions, fuzzy maps were generated for each parameter. These fuzzy maps provided input data for the DST model. The predicted values were analyzed and compared at three confidence levels to determine the effectiveness of the model. The results are that 11.14%, 14.14%, and 17.18% (95%, 99%, and 99.5% confidence levels, respectively) of the study area are predicted to be susceptible to earthquakes based on receiver operating characteristic curves. The results also show that, according to the area under the curve (AUC) values (0.967, 0.828, and 0.849 for 95%, 99%, and 99.5% confidence levels, respectively), DST model generates earthquake zoning maps with high accuracy. Therefore, this model can be used for generating earthquake zoning maps with confidence levels that best suit the economic conditions and significance of the region.

在这项研究中，将Dempster–Shafer理论（DST）集成到地理信息系统中，以对伊朗西北部克尔曼沙赫省的地表脆弱性进行地震建模，以预测最可能发生破坏的地方。DST从未用于对地震脆弱性进行空间建模。为此，在ArcGIS 10.2.2软件中编译了几种环境属性的数据层-高度，高程，岩性，坡度角，土地使用，距河道的距离，距道路的距离以及距断层的距离。使用隶属函数，为每个参数生成模糊图。这些模糊图为DST模型提供了输入数据。对预测值进行分析，并在三个置信度水平上进行比较，以确定模型的有效性。结果是11.14％，14.14％和17.18％（95％，根据接收器的工作特性曲线，分别预测研究区域的99％和99.5％的置信度容易受到地震的影响。结果还表明，根据曲线下面积（AUC）值（95％，99％和99.5％的置信度分别为0.967、0.828和0.849），DST模型可以生成高精度的地震分区图。因此，该模型可用于生成具有最适合该地区经济条件和重要性的置信度的地震分区图。分别为5％的置信度），DST模型可生成高精度的地震分区图。因此，该模型可用于生成具有最适合该地区经济条件和重要性的置信度的地震分区图。分别为5％的置信度），DST模型可以生成高精度的地震分区图。因此，该模型可用于生成具有最适合该地区经济条件和重要性的置信度的地震分区图。