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Copyright of Journal of The Planner & Development is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

CityZones is an online tool to support when computing risk zones in a city, which is performed by mathematically evaluating the emergency response capability of an urban area using real data. The tool allows users to define polygonal Areas of Interest (AoI) on a map, which are categorised into low, medium, and high-risk levels. As urban emergencies in general will typically demand the assistance of hospitals (to attend victims), firefighters (for rescue operations and damages reduction), policemen (to control and manage critical situations), and even metro stations (for evacuation), the risk zones within an AoI will be computed according to the distances to such existing infrastructure, which is extracted from the OpenStreetMap database. The coordinates of an AoI are defined at the client-side and submitted to a server as a regular or irregular polygon, which is then stored in a GeoJSON file along with the computed classifications for further processing according to a multi-tier pipeline. Adopting a configurable square-based mathematical model to compute distances and relative risk levels, the risk zones are computed on-demand and exported to CSV files to be used by any application, with an additional representation for web-based visualisation. Moreover, as a practical exploitation of the computed maps, the CityZones tool also suggests ideal positions for sensors-based Emergency Detection Units (EDUs) within an AoI according to the chosen positioning algorithm, assuming that the computed risk zones indicate how severe an undetected emergency would be. While the CityZones tool is not intended to provide a mitigation approach at all, since it does not have knowledge about current emergency situations, it stands as a valuable pre-mitigation tool to be used in the planning phase of emergency management in smart cities, bringing an important contribution for practical applications in this area.

In order to scientifically evaluate the emergency management capacity of major cities in China, this paper studies the input and output index data of cities in emergency management. Firstly, the urban emergency management evaluation system is established according to the emergency investment funds, the proportion of emergency investment funds in GDP, the number of emergency personnel, the number of accidents, the number of deaths, and the loss of funds and so on. Then, a super-efficiency DEA urban emergency management capability evaluation model based on the weight constraint of the order relation analysis method (G1 method) is constructed to achieve a reasonable combination of subjective and objective assignments. Finally, the emergency management data of 36 major cities in China are selected for effectiveness evaluation, and the cities with the most effective emergency input relative to accident output are obtained, and the rank reversal problem existing in the traditional DEA model is discussed. The results show that the super efficiency DEA with weight constraint of G1 method proposed in this paper not only considers the subjective information of decision-makers, but also realizes the objective assignment, which can effectively solve the problem of rank reversal and achieve the effective and credible ranking of urban emergency management ability. [ABSTRACT FROM AUTHOR]

Urban disasters and the practice of emergency management present obvious cross-regional characteristics given the increasing complexity of urban development and operating systems. Currently, strengthening urban emergency management cooperation and integrating heterogeneous emergency organization resources comprise the basic trends and common requirements to manage urban disasters. This study uses the collapse of the Xinjia Hotel in Quanzhou, Fujian Province, China, on March 7, 2020, as an example to construct an urban cross-regional emergency cooperation network and thereby clarify the mode and mechanism of urban cross-regional emergency cooperation. The structural characteristics of the overall network of urban cross-regional emergency cooperation and the cooperation network of different emergency function modules are examined based on the research framework of "Integration of the emergency cooperation–Modularization of the emergency cooperation." Moreover, we explore the resource flow and interaction between the emergency organizations of different jurisdictions in urban cross-regional emergency cooperation. Further, the effect of each emergency module on the formation of cross-regional emergency cooperation is discussed. Thus, this study proposes optimization countermeasures from three aspects: system construction, organization coordination, and mechanism design. This research provides a new exploration of the urban cross-regional emergency cooperation between different types of emergency organizations, which is helpful for effective decision-making under different situations. [ABSTRACT FROM AUTHOR]

Natural disasters happen without warning; it is normally impossible to predict when they will occur, but it is necessary that rescue services reach the disaster site and manage the emergency. This paper proposes an innovative methodology to summarize seismic effects on road, building, and land factors in urban areas. The existing road network is modelled through the graph theory: the arcs represent the main infrastructures, while the nodes represent both the primary strategic buildings and the intersections between the main roads. Therefore, the quantitative approach takes into account the existing road network, the focal areas that play a strategic role during emergency, and their relationship with buildings and territory. The results enable the identification of the minimum urban structure (MUS) with total connectivity at maximum availability. These structures were composed of the paths that will be the priority choice for emergency vehicles after an earthquake. The proposed approach has been implemented to identify the MUS in a medium-size Italian urban center (Pomezia) in the event of a critical earthquake. The methodology is easy to apply and could represent an ideal tool in the preliminary phase of analysis of an urban road network to define new city plans through targeted territorial design, to facilitate decision makers in investment choices, to increase the road network consistency, and to implement emergency plans after natural disasters. [ABSTRACT FROM AUTHOR]