Climate change is leading to more and more extreme weather events such as heavy rainfall and flooding. This technical report deals with the question of how rescue commanders can be better and faster provided with current information during flood disasters using Unmanned Aerial Vehicles (UAVs), i.e. during the flood in July 2021 in Central Europe, more specifically in Erftstadt / Blessem. The UAVs were used for live observation and regular inspections of the flood edge on the one hand, and on the other hand for the systematic data acquisition in order to calculate 3D models using Structure from Motion and MultiView Stereo. The 3D models embedded in a GIS application serve as a planning basis for the systematic exploration and decision support for the deployment of additional smaller UAVs but also rescue forces. The systematic data acquisition of the UAVs by means of autonomous meander flights provides high-resolution images which are computed to a georeferenced 3D model of the surrounding area within 15 minutes in a specially equipped robotic command vehicle (RobLW). From the comparison of high-resolution elevation profiles extracted from the 3D model on successive days, changes in the water level become visible. This information enables the emergency management to plan further inspections of the buildings and to search for missing persons on site.
翻译:这份技术报告涉及如何在洪水灾害期间,即2021年7月中欧(更具体地说,在Erftstadt/Blesseem)发生水灾期间,利用无人驾驶航空飞行器(无人驾驶航空飞行器),即2021年7月中欧(更具体地说,在Erftstadt/Blaxem)发生水灾期间,更好、更快地向救援指挥官提供最新信息的问题。无人驾驶航空飞行器一方面用于现场观察和定期检查洪水边缘,另一方面用于系统获取数据,以便利用来自运动和多视气流的结构计算3D模型。地理信息系统应用中嵌入的3D模型是系统探索和决定支持部署更多小型无人驾驶航空飞行器(无人驾驶飞行器)的规划基础,但也有救援部队。通过自主的中途飞行系统获取无人驾驶航空飞行器的数据提供了高分辨率图像,这些图像在15分钟内用于现场观察和定期检查洪水边缘地带的地理参照3D模型,在特别装备的机器人指挥飞行器(RObLW)中进行系统采集数据。从连续从3D模型中提取的高分辨率高分辨率升射图的比较后,对水层建筑物进行了更深入的搜索,从而可见地点进行了搜索。