In this study, we performed routes network transport and emergency shelters capacity rate analyses to determine the accessibility and efficacy of urban patterns, and established a quantitative method for supplying priorities for actions of »Sendai Framework for Disaster Risk Reduction 2015-2030». By comparing two case studies, we used Space Syntax to develop two important indicators, Rn and CR, to present geographic information and hazard risk in a physical environment. This research also found potential function of Rn and decoded some patterns for urban planners or decision makers as follows: The most efficient configuration of the road network was not in the old areas of these two case studies because the several turns decreased the connectivity of the networks. And the CR indicator shown other findings about the quality of public facilities and services as follows: The service capacity of the emergency shelters was surveyed to indicate a higher correlation of residents population and preparedness security for disaster management. Therefore, with finding some risks that had not been encountered before, we addressed this proposed method is feasible and reliable to enhance the disaster preparedness for action regarding the 4th priority of "Sendai Framework for Disaster Risk Reduction 2015-2030".
Chang, H. W., & Lee, W. I. (2018). Decoding network patterns for urban disaster prevention by comparing Neihu district of Taipei and Sumida district of Tokyo. In MATEC Web of Conferences (Vol. 169). EDP Sciences. https://doi.org/10.1051/matecconf/201816901044