Heavy rains since early July 2020 have caused flooding in the Kyushu area. The Kuma River overflowed due to heavy rain. The river itself located in Kumamoto Prefecture right in the Hitoyoshi city. Disaster shelter is one of the most important requirements for those evacuated in the event of a disaster. It is used to analyze the supply and demand of the shelter based on the distance from the point of application to the disaster evacuation shelter, using the P-median model. As a result, the demand for evacuation shelters in the city of Hitoyoshi is 48%, which indicates that the demand for evacuation centers in case of disaster is about half. In this study, the location-allocation method was used in ArcGis 10.6 to determine the supply-demand ratio for Hitoyoshi. These data are expected to be used to optimize the operation of shelters in the Hitoyoshi area, an area prone to disasters for future urban development. This allows evacuation or disaster safety planners to develop tools for their area during floods and provides a way to predict when an event will occur and when roads will become unsafe for the residents during the future evacuation process. When a natural disaster happens again in the future, the demand and supply of disaster evacuation shelters should be assessed to determine their total capacity.

Improving urban walkability is critical to the long-term development of cities. Although previous studies have demonstrated a relationship between the built environment and walking, an approach that can control the exploration of different functional areas has not yet been discussed. In this study, built environment features include density, design, diversity, destination accessibility, and distance to transit. Geodetector and regression methods were used to investigate the impact of the built environmental features on pedestrian volume in different functional areas of Kumamoto City. It was found there were various dominant features for the different functional areas in the city, including the city center (diversity, design, and density), local hubs (destination accessibility, density, and distance to transit), living hubs (density, design, and distance to transit), UPA (diversity, design, and distance to transit), UCA (density, density, and design), and NPA (density). Additionally, population density and land use diversity in the overly dense population area were negatively related to pedestrian volume. This study complements research on pedestrians and the built environment in different functional areas, and provides advice for the urban planners and government of Kumamoto City.

Natural disasters are one of the things that have risks and hazards to the population. This study aims to simulate the flood hazard and calculate its impact on the Hitoyoshi area, Japan residential areas. Hitoyoshi was chosen as the case study because the area experienced a catastrophic flood in 2020 that destroyed the city. The calculation of the impact of this study is also based on mapping the area based on land function, damage to buildings, and building materials, especially in areas affected by floods in the city of Hitoyoshi, Kumamoto. The results of this study indicate how much risk will be caused by flooding, especially in the Hitoyoshi area, with simulations carried out in ArcGIS software. In addition, the simulated hazard map is overlaid with buildings to determine the impact caused by the Hitoyoshi Area. This research aims to provide input for the Japanese institution in increasing the risk of natural disasters against floods, especially in the Hitoyoshi area, in dealing with future disasters. Simulations carried out in areas that have been affected by flooding by making a hazard map and validating it to prove the accuracy of the data are expected to be used and applied in several other countries besides Japan.

One of the most water-related disasters is flooding induced by heavy rain. According to several model experiments and an analysis of historical data, such natural disasters will become more common in the future. In recent years, torrential rain and flooding have caused significant damage to agricultural land, homes, and human life in numerous Japanese towns. We used the Hitoyoshi City in Kumamoto Prefecture, Japan, as a case study for the area’s flood event in July 2020. This study uses machine learning to study spatial analysis of the city of Hitoyoshi after the 2020 flood disaster. Assessments such as flood hazards, exposure, and susceptibility are critical components of total flood risk assessment. In addition, this study also uses several driving factors for mapping the scenario to the evacuation center, how the impact of flooding on the residential environment, and changes to land use in the Hitoyoshi area. For land-use planners, estimating the quickly flooded region using distinct land use profiles is quite important. It aids in the analysis of flood losses and the allocation of resources for recovery and restoration.