Using internet open-source data for spatio-temporal characteristic assessments of urban waterlogging risks: A case study in Hanoi, Vietnam

In the context of climate change and rapid urbanization, waterlogging due to rainstorms is becoming more frequent and serious in developing countries, thereby posing increasing threats to the sustainable development strategies of the cities. One of the important means of solving this problem lies in elucidating the spatio-temporal distribution characteristics of waterlogging events. We applied the spatial analysis and statistical toolboxes implemented in ArcGIS with internet op`en-source data to assess the waterlogging risks in each area of Hanoi, Vietnam, for the period of 2012–2018. The results show that Hoan Kiem District had the highest waterlogging risk, followed by Dong Da, Ba Dinh, Thanh Xuan, Cau Giay, Hai Ba Trung, and Hoang Mai Districts. Similar to the urban surface expansion affected by urbanization, the risks are densely distributed in the city center and have the tendency to expand into suburban areas at locations surrounding the ring roads, the radial axis roads, and traffic intersections. At the same time, the frequency of waterlogging has a certain dependence on space, which means that the locations of urban waterlogging events were not randomly distributed. These results represent an important analytical step in urban waterlogging management to prevent and control urban waterlogging.