Decoding network patterns for urban disaster prevention by comparing Neihu district of Taipei and Sumida district of Tokyo

Abstract

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”.

Assessing the Impact of Temporary Housing Sites on Urban Socio-spatial Performance: The Case of the Central Italy Earthquake

“…Despite it being diffused prevalently out of the humanitarian context, its potential in informing and supporting different disaster management tasks has been confirmed by many previous studies. The scientific literature presents examples related to almost all the phases of the disaster management cycle: from disaster prevention and mitigation [16], to emergency response [17], housing relief [18], infrastructure [19] and economic [20] as well as housing recovery [13]. The latter proves that Space Syntax offers novel opportunities for assessing the long-term outcomes of housing recovery plans (i.e., via the quantification of changes in levels of street network resilience and centrality of a given settlement) as it helps understanding the indirect effects of alterations to urban form.…”

Flood risk of today and tomorrow

“…From the perspective of urban planners, space syntax is a method used to organise the urban network as quantitative data, a pattern, and a pattern of movement (Hillier, 2009). Space syntax is a popular method for generating risk maps of any natural disaster scenarios (Pezzica, Valerio et al, 2019), such as earthquakes (Cutini, 2013), hurricanes (Carpenter, 2013), landslides (Castillo, 2013) and flood hazards (Abshirini and Koch, 2017;Chang and Lee, 2018;Gil and Steinbach, 2008). In risk mapping, space syntax is often used to show the effectiveness of the evacuation route, the deployment of rescue teams and the ideal placement of emergency service units (Penchev, 2016).…”

“…In risk mapping, space syntax is often used to show the effectiveness of the evacuation route, the deployment of rescue teams and the ideal placement of emergency service units (Penchev, 2016). Chang and Lee (2018) created a hazard risk map by analysing the effectiveness of road networks and the capacity of emergency shelters. They used space syntax to evaluate the spatial configuration of roads as the effectivity value of the road network (Chang and Lee, 2018).…”

“…Chang and Lee (2018) created a hazard risk map by analysing the effectiveness of road networks and the capacity of emergency shelters. They used space syntax to evaluate the spatial configuration of roads as the effectivity value of the road network (Chang and Lee, 2018). The risk map generated in this study is the result of the spatial syntax method.…”

“…The present research created risk maps using space syntax for evacuation in flood hazard scenarios. Notably, this research used the research methods of Chang and Lee (2018). However, this research differs from that of Chang and Lee (2018) in terms of its focus and the study case.…”