DataSheet1_Rapid Terrain Assessment for Earthquake-Triggered Landslide Susceptibility With High-Resolution DEM and Critical Acceleration.docx

Earthquake ground motion often triggers landslides in mountainous areas. A simple, robust method to quickly evaluate the terrain’s susceptibility of specific locations to earthquake-triggered landslides is important for planning field reconnaissance and rescues after earthquakes. Different approaches have been used to estimate coseismic landslide susceptibility using Newmark’s sliding block model. This model requires an estimate of the landslide depth or thickness, which is a difficult parameter to estimate. We illustrate the use of Newmark sliding block’s critical acceleration for a glaciated valley affected by the 2015 Gorkha earthquake in Nepal. The landslide data came from comparing high-resolution pre- and post-earthquake digital elevation models (DEMs) derived from Spot 6/7 images. The areas where changes were detected provided an inventory of all the landslides triggered by the earthquake. The landslide susceptibility was modeled in a GIS environment using as inputs the pre-earthquake terrain and slope angles, the peak ground acceleration from the 2015 Gorkha earthquake, and a geological map. We exploit the depth information for the landslides (obtained by DEM difference) to apply the critical acceleration model. The spatial distribution of the predicted earthquake-triggered landslides matched the actual landslides when the assumed landslide thickness in the model is close to the median value of the actual landslide thickness (2.6 m in this case). The landslide predictions generated a map of landslide locations close to those observed and demonstrated the applicability of critical acceleration for rapidly creating a map of earthquake-triggered landslides.

地震地面运动常引发山区发生滑坡。针对地震诱发滑坡的特定地点地形敏感性进行快速评估的简便、稳健方法，对于地震后的现场侦察和救援规划具有重要意义。利用 Newmark 滑动块模型估算地震期间滑坡敏感性，已采用多种方法。该模型需要估算滑坡深度或厚度，而这是一个难以估计的参数。本文展示了 Newmark 滑动块模型的临界加速度在受2015年尼泊尔戈尔卡地震影响的冰川山谷中的应用。滑坡数据来源于对比地震前后由 Spot 6/7 图像生成的具有高分辨率的前后地震数字高程模型（DEM）。检测到变化的区域为地震引发的滑坡提供了清单。在地理信息系统（GIS）环境中，利用地震前地形和坡度角、2015年戈尔卡地震的峰值地面加速度以及地质图等数据对滑坡敏感性进行建模。我们利用滑坡的深度信息（通过DEM差分获得）来应用临界加速度模型。当模型中假设的滑坡厚度接近实际滑坡厚度的中位数（本例中为2.6米）时，预测的地震诱发滑坡的空间分布与实际滑坡相匹配。生成的滑坡预测位置图接近观测到的位置，并证明了临界加速度模型在快速创建地震诱发滑坡地图方面的适用性。