Coastal and riverine flooding is one of the most common environmental hazards that affect billions of people worldwide. A coupled hydrologic and coastal storm surge simulation is required to develop an improved understanding of the individual and collective mechanisms that can cause flooding within watersheds. These simulations are dependent on an accurate digital elevation model (DEM); however, it is a challenge to include numerical model resolution as fine as contemporary DEMs due to the enormous computational cost. Therefore, significant vertical features (VFs) such as roadbeds, levees, railroads, and natural ridges must be identified and considered in developing the model representation of the DEM since the VFs can affect flow propagation. PyVF is an open-source program to extract significant VFs from a high-resolution, bare-earth, LiDAR-derived DEM automatically. This paper introduces the methods and shows the automated extraction of VFs for a coastal, urban, mountain and beach area.

沿海和河流洪水是影响全球数十亿人的最常见的环境危害之一。需要进行耦合的水文和沿海风暴潮模拟，以更好地了解可能导致流域内洪水的个体和集体机制。这些模拟依赖于精确的数字高程模型（DEM）；然而，由于巨大的计算成本，将数值模型分辨率与当代 DEM 一样精细是一项挑战。因此，在开发 DEM 的模型表示时，必须识别和考虑重要的垂直特征 (VF)，例如路基、堤坝、铁路和天然山脊，因为 VF 会影响水流传播。PyVF 是一个开源程序，用于从高分辨率、裸露的地球、激光雷达衍生的 DEM 自动。本文介绍了这些方法并展示了沿海、城市、山区和海滩地区的 VF 的自动提取。