The M7.8 Nepal earthquake on 25 April 2015 and its aftershocks triggered thousands of landslides. Understanding correlations between the landslide occurrences and landslide conditioning factors is essential to generate a landslide susceptibility map. This study considers the two most reliable inventory data: landslide inventory 1 (LI-1) and landslide inventory 2 (LI-2). The LI-1 contains 1,352 landslide polygons, and the LI-2 contains 4,000 landslide points. The centroid locations of LI-1 were also considered as additional point inventory data for the statistical analyses. The landslide area percentage and landslide number density are computed for important factors such as slope angle, slope roughness, aspect, peak ground acceleration (PGA), distance to epicenter, distance to rivers and roads, Normalized Difference Vegetation Index (NDVI), land use and land cover, and mean annual precipitation. The cumulative percentage curves and the areas under the curve (AUC) are also compared for all the considered factors. PGAs of the main shock and two major aftershocks, distance to epicenter, slope angle, distance to river, and NDVI have relatively stronger correlations with the landslide occurrence than other factors. It is found that the LI-1 polygons have weaker correlations with the factors than LI-1 points and LI-2 points do because the LI-1 does not distinguish debris from scarps.

在中号2015年4月25日的7.8级尼泊尔地震及其余震引发了数千起滑坡。了解滑坡发生与滑坡条件因素之间的相关性对于生成滑坡敏感性图至关重要。本研究考虑了两个最可靠的清单数据：滑坡清单1（LI-1）和滑坡清单2（LI-2）。LI-1包含1,352个滑坡多边形，LI-2包含4,000个滑坡点。LI-1的质心位置也被认为是用于统计分析的其他点清单数据。计算滑坡面积百分比和滑坡数量密度是重要因素，例如坡度角，坡度，坡度，峰值地面加速度（PGA），到震中的距离，到河流和道路的距离，归一化植被指数（NDVI），土地利用和土地覆盖，以及年平均降水量。还比较了所有考虑因素的累积百分比曲线和曲线下面积（AUC）。与其他因素相比，主震和两次余震的PGA，到震中的距离，倾斜角，到河的距离和NDVI与滑坡发生的相关性相对较强。发现LI-1多边形与因子的相关性比LI-1点和LI-2点弱，因为LI-1不能区分碎屑和陡坡。NDVI与滑坡发生的相关性高于其他因素。发现LI-1多边形与因子的相关性比LI-1点和LI-2点弱，因为LI-1不能区分碎屑和陡坡。NDVI与滑坡发生的相关性高于其他因素。发现LI-1多边形与因子的相关性比LI-1点和LI-2点弱，因为LI-1不能区分碎屑和陡坡。