Predicting the Potential of Rainfall Disaster Risk using Cellular Automata in Small Urban Declining Areas

Abstract

Purpose: In declining cities, it is vulnerable to disaster risks due to the complex reasons such as aging of the buildings, decreases in population and slowly development of infrastructure. When making regeneration plans for declining areas, it is necessary to analyze and predict disaster risks. Therefore, this paper aims to predict the potentials of disaster risks in small-scale declining areas in cities that show risks in the future. Method: This study predicts potential of disaster risk by using cellular automata. By simulating the heavy rainfall disaster using RCP scenarios, 10-year unit change simulation results for heavy rainfall disaster risk are acquired. After simulating disasters that affect to the heavy rainfall disaster, we applied cellular automata to obtain a 10-year unit disaster risk potential. Result: By considering the yearly change values of disaster risk elements in small-scale urban regeneration regions, this study suggests a prediction method of disaster risk potential simulation for heavy rainfall. Our research contributes to the analysis and forecasting of disaster risks in aging small declining areas settings. We expect that the suggested model would be helpful to identify disaster risks and prioritize urgent areas in small decline cities in the future.