The geological and geographical conditions have made the Himalayas one of the regions most vulnerable to disasters. Northern Pakistan is made up of high-relief Himalayan mountains where landslides are the most frequently occurring catastrophic events. Floods, earthquakes, and landslides occur most often in this region, causing deaths and severe infrastructure damages. The studied area is experiencing significant landslide events triggered by destructive seismic activity, extreme seasonal rainfalls, and human activities. In this study, landslide susceptibility mapping is proposed using an integrated model of information value method by optimizing its capabilities and overcoming its limitations to enhance both precision and accuracy of the results. This approach quantifies and estimates the probability of landslide occurrence using statistical principles and techniques. Seven distinct landslide causative factors, including slope angle, distance to stream, drainage density, distance to road, land cover, normalized difference vegetation index, lithology, and distance to faults were evaluated to determine the areas at risk for future slope movements. A reliable landside inventory from a spatial database combined with ground-truthing field surveys was prepared for evaluating the relationship between the landslides and their causative factors. The accuracy and efficiency of the developed model are evaluated using sensitivity analysis of the receiver operator curve (ROC). The ROC-validated results showed an accuracy of 0.845 for model prediction rate and an accuracy of 0.837 for model success rate, indicating that the model is reliable to produce landslide susceptibility map. The results showed the reasonable efficiency of the applied method for assessing landslide susceptibility in the study area and applicable to other regions with similar geomorphological conditions.

地质和地理条件使喜马拉雅山成为最容易遭受灾害的地区之一。巴基斯坦北部是由高起伏的喜马拉雅山脉组成，其中滑坡是最常发生的灾难性事件。该地区最常发生洪水，地震和山体滑坡，导致人员伤亡和严重的基础设施破坏。该研究区域正在经历由破坏性地震活动，极端季节性降雨和人类活动引发的重大滑坡事件。在这项研究中，通过使用信息价值方法的集成模型，通过优化滑坡敏感性和克服其局限性以提高结果的准确性和准确性，提出了滑坡敏感性地图。这种方法使用统计原理和技术来量化和估计滑坡发生的可能性。对七个不同的滑坡成因进行了评估，包括坡度角度，到溪流的距离，排水密度，到公路的距离，土地覆盖，归一化差异植被指数，岩性和到断层的距离，以确定有可能发生未来斜坡运动的区域。通过评估空间滑坡及其致病因素之间的关系，准备了一个来自空间数据库并结合地面实地调查的可靠的陆边清单。使用接收器操作员曲线（ROC）的灵敏度分析评估开发模型的准确性和效率。ROC验证的结果显示，模型预测率的准确度为0.845，准确度为0。837为模型成功率，表明该模型可生成滑坡敏感性图。结果表明，该方法在研究区评估滑坡敏感性的方法是合理的，并且适用于其他具有相似地貌条件的地区。