Data Collection and Data Processing Methods for Creating Grid-Based Flood Hazard Maps

As global climate change continues to appear, damage caused by natural disasters such as localized torrential rains in which a large amount of rain falls in a local area for a short period of time and powerful typhoons accompanied by heavy rains occurs frequently. In addition, as residential buildings and industrial assets are spread due to urbanization and industrialization, damage to human life and property due to flooding is also increasing in downtown areas. In a situation where the increase in water-related disasters and the intensity of torrential rains show different probabilistic characteristics from the past, it is necessary to study various disaster prevention measures to minimize the risk of water-related disasters. Recently, the use of geospatial information is increasing to preemptively respond to various disasters. There are administrative districts and grids for spatial units. Currently, a database is built and used based on administrative districts. However, in the case of administrative districts, the shape and size are irregular, and the boundary is adjusted according to the change of time, so that the shape and size of the space unit is changed. There is a limitation in that it cannot provide an organic spatial unit because it can be changed. In order to solve this problem, a method of expressing information through a grid having a certain shape and size is attracting attention. When analyzing grid-based spatial information, spatial expression units are detailed, information distortion is minimized during data fusion and analysis, and the intuitive visualization of regional risk information can be considered. Therefore, in this study, we are going to introduce data collection and data processing methods for disaster information necessary to create a grid-based flood risk map.