GIS-Based Roughness Derivation for Flood Simulations: A Comparison of Orthophotos, LiDAR and Crowdsourced Geodata
GIS-Based Roughness Derivation for Flood Simulations: A Comparison of Orthophotos, LiDAR and Crowdsourced Geodata
复制标题
基于 GIS 的洪水模拟粗糙度推导：正射影像、LiDAR 和众包地理数据的比较
作者：
Helen Dorn;M. Vetter;B. Höfle
洪水等自然灾害是一种全球现象，对人类构成严重威胁。洪水模拟是灾害控制的应用，用于制定适当的防洪措施。充分的模拟不仅需要地球表面的几何形状，还需要其粗糙度，以及地表物体的粗糙度。通常，洪泛区粗糙度是基于从正射影像图得出的土地利用/土地覆盖图。本研究分析了基于不同数据集（正射影像图、激光雷达数据、官方土地利用数据、开放街道地图数据和欧洲环境署土地覆盖数据）的粗糙度图绘制方法在洪水模拟中的适用性。基于对象的图像分析应用于正射影像图和激光雷达栅格数据，以生成能够进行粗糙度参数化的土地覆盖图。激光雷达点云内的垂直植被结构被用于绘制额外的洪泛区粗糙度图。进一步的粗糙度图从官方土地利用数据、开放街道地图和欧洲环境署土地覆盖数据集中得出。基于一种高程数据但使用不同的粗糙度图进行了六种不同的洪水模拟。水动力数值模型的结果包括流速和水深信息，由此计算出额外的属性——洪水强度。基于从激光雷达数据和开放街道地图数据得出的粗糙度图的结果具有可比性，而其他数据集的结果则有显著差异。
Natural disasters like floods are a worldwide phenomenon and a serious threat to mankind. Flood simulations are applications of disaster control, which are used for the development of appropriate flood protection. Adequate simulations require not only the geometry but also the roughness of the Earth’s surface, as well as the roughness of the objects hereon. Usually, the floodplain roughness is based on land use/land cover maps derived from orthophotos. This study analyses the applicability of roughness map derivation approaches for flood simulations based on different datasets: orthophotos, LiDAR data, official land use data, OpenStreetMap data and CORINE Land Cover data. Object-based image analysis is applied to orthophotos and LiDAR raster data in order to generate land cover maps, which enable a roughness parameterization. The vertical vegetation structure within the LiDAR point cloud is used to derive an additional floodplain roughness map. Further roughness maps are derived from official land use data, OpenStreetMap and CORINE Land Cover datasets. Six different flood simulations are applied based on one elevation data but with the different roughness maps. The results of the hydrodynamic–numerical models include information on flow velocity and water depth from which the additional attribute flood intensity is calculated of. The results based on roughness maps derived from LiDAR data and OpenStreetMap data are comparable, whereas the results of the other datasets differ significantly.