شهر امن - پرفیلد ابزار مبتنی بر GIS برای حمایت از تصمیم گیری در توسعه شهری و حفاظت از زیرساخت
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|18755||2013||14 صفحه PDF||سفارش دهید|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Technological Forecasting and Social Change, Available online 5 October 2013
This paper presents a system for analysis of municipal Critical Infrastructures, which offers integrated tools for target analysis, hazard scenario simulations and spatial analysis within a remotely accessible Web-based Geographic Information System. The system has been applied to research conducted in the city of Gdansk with the aid of blast attack, chemical leakage and flood hazard scenarios, as well as a spatial density algorithm, which highlights events in which the proximity of infrastructures influences their susceptibility to a single attack. The paper also discusses the way in which the tools provided by the system aim to assist in the processes of infrastructure vulnerability assessment, mitigating discovered risks as well as strategic planning of city development.
The importance of infrastructures in the proper functioning of a city cannot be overestimated. Ever since the dawn of the industrial era, a well developed infrastructure decided the success or failure of a city's economic growth . The natural consequence of infrastructure development was the creation of local clusters of interconnected services and companies . This local concentration of different infrastructure sectors did not come into wider attention until the second half of the XX century, when the aftermath of World War II saw a decentralization of urban areas in the United Kingdom . However, this was mainly a local trend. Globally the rapid evolution of telecommunication networks has led to the creation of a new type of infrastructure which controls access to all sorts of goods and services via software mechanisms such as passwords or biometric judgments . The internet itself has been designed, in accordance with the post-war paradigms, as a dispersed network able to withstand a direct physical attack . However, while the entire network may be resistant to most types of hazards, a local malfunction of several nodes (caused e.g. by a power shortage) may be enough to disconnect a small city, the consequences of which may be quite severe . By the end of the last century the impact of technological development on modern municipalities has become so great that certain types of infrastructure have been recognized as essential to the proper functioning of a city. The first formal definition of Critical Infrastructure was produced by the United States government in Executive Order 13010 issued in 1996. The document defines Critical Infrastructures as “independent, mostly privately-owned, man-made systems that function collaboratively and synergistically to produce and distribute a continuous flow of essential goods and services”. The provided services must be vital enough so that “incapacity or destruction” of one of the infrastructures would have a “debilitating impact” on citizen security . This definition was later expanded in the USA National Strategy on Homeland Security (NSHS), published in 2002. This document not only contains a list of Critical Infrastructure sectors, but also makes a distinction between Critical Infrastructures and key assets, which are defined as individual targets whose “destruction would not endanger vital systems, but could create local disaster or profoundly damage” the “morale and confidence” of citizens. Such assets would include historical attractions (national, state, and local monuments and icons) and other localized facilities with destructive potential or of high value to a community such as schools, courthouses and bridges . Three years later, in Europe the Green Paper on the European Programme for Critical Infrastructure Protection (EPCIP) provided the definitions of Critical Infrastructures on different levels (e.g. National and European), the definition of their threats (a “threat” being any person, activity, or event with the potential to cause harm to a system or operational environment — the primary types of threats include natural disasters, accidental threats and threats of intentional or malicious nature ) as well as the role of their owners and operators. Both these documents also contain lists of Critical Infrastructure sectors. These, in general, are largely similar and consist of Energy, Water, Food, Public Health, Financial, Transport, and Chemical industry, Telecommunications and Research facilities . The successful protection of Critical Infrastructure is a complex process, encompassing the events occurring before a threat is identified, the time during a crisis and its aftermath. Consequently, the main phases of Critical Infrastructure emergency management are referred to as Preparedness, Mitigation, Response and Recovery. As the naming indicates, the first phase involves threat identification, assessment of risk and planning of response actions, as well as training of emergency services . The next phase concentrates on attempts to prevent hazards from developing into disasters, as well as reducing the effects of disasters when they occur. Mitigatory measures may involve structural means such as perimeter fencing or flood dykes, or non-structural measures such as legislation (e.g. regulating evacuation or methods of alarming the public), land-use planning (e.g. the designation of non-essential land to be used as flood zones) and insurance . The Response phase takes place immediately after a disaster strikes, and includes the mobilization of necessary emergency services and first responders in the affected area. A well rehearsed emergency plan developed as part of the preparedness phase is paramount to the efficiency of the search and rescue efforts, as the fatality rates increase dramatically after the initial 72 h after impact . The efforts of the final phase aim to restore the affected area to its original state, and involve rebuilding destroyed assets and repair of other essential infrastructures . In the last decade the issue of Critical Infrastructure protection has received a lot of attention from researchers worldwide. Soon after the events of 9/11, it was proposed that the security of Critical Infrastructure could be improved by development of existing supervisory control and data acquisition systems (SCADA) . However, it soon transpired that the rising protection costs stemming from the quick evolution of existing as well as new threats, e.g. related to cyber security, make it impossible to completely secure any given infrastructure . Later research suggested that Critical Infrastructures should not be analyzed individually, but rather as a network of distributed interdependent systems . The tight interconnections between these systems could, in a worst-case scenario, lead to a cascading failure . Evidence supporting this theory could be found in the wake of crises such as Hurricane Katrina . In consequence, new models and methods of Critical Infrastructure risk analysis have been proposed, including probabilistic models , graph models , economical models  and , agent-based models  and network models , as well as empirical approaches . A common characteristic of all the aforementioned methodologies is that they have been developed for use by professional analysts. The task of constructing an analysis and presenting results in a meaningful way rests on the user. The available tools also relatively seldom ,  and  consider the geographical location of infrastructures as a factor affecting their security. This study aims to prove that modern technology in the form of a well-proven vulnerability assessment methodology coupled with a user-friendly Geographic Information System (GIS) and tools for Geovisual Analytics may help in significantly enhancing the security of Critical Infrastructures in medium as well as small cities which need to cope with a very limited budget for infrastructure protection. The responsibility for protecting Critical Infrastructures may be subject to local legislation, but most often it lies on the owner and/or operator. Most often at least one of these roles is attributed to a local municipality. However, municipalities often lack the expertise and resources necessary to ascertain appropriate level of protection to the right infrastructures, many of which are used in ways that were not foreseen during their development . Thus, successful management of risk for a large number of different types of Critical Infrastructure with variable resistance to various types of threats requires support from dedicated tools employing specialistic knowledge from many branches in support of integrated analysis and comparison of different types of municipal infrastructure.
نتیجه گیری انگلیسی
Geographical concentration of Critical Infrastructures is an important issue that governments are becoming increasingly aware of. Legislative measures are being taken in order to mitigate some of the negative impact of clustering. The United States Congress, for instance, recognized the need to prevent future concentration of Critical Infrastructure in the aftermath of hurricane Katrina. The first relevant policy it passed was the Energy Policy Act which states that new liquefied natural gas import terminals should be facilitated in diverse ports . However, laws like this do not yet deal with concentration of infrastructures from different sectors. They will not prevent scenarios similar to the recent terrorist attack in Oslo, in which a single determined individual equipped with a car bomb made of fertilizer and fuel oil has succeeded in disrupting the operations of several institutions. While the current legislation in the form of NSHS and EPCIP will not prevent the creation of such clusters, they may be identified and analyzed with the aid of appropriate software. This research has shown that the application of a dedicated GIS to the analysis of Critical Infrastructure even on a very basic level helps to identify often overlooked issues such as the spatial concentration of infrastructures from different sectors. The presented system offers tools which have been designed for specific purposes related to modeling and spatial analysis of different types of hazards in urban regions. The algorithms employed by these tools operate in a spatial context and produce thematic layers representing either the outcome of a possible hazard (in the case of models) or the results of spatial risk analysis. On the basis of the type of produced analysis, each algorithm may be applied to different phases of the emergency management process. In particular, the hazard simulation algorithms may be applied to creation of hazard scenarios during the Preparedness phase, mapping of identified threats in the Response phase as well as simulating the geographical impact of threats during the Mitigation phase. The integrated CARVER2™ module enables an analyst to identify weaknesses in the defense of Critical Infrastructures by means of target analysis with the use of data available in the city databases. By employing quantitative methods of analysis to a set of standard attributes, the tool allows for comparing dissimilar types of infrastructure using the same standards and aims to assist the user in making decisions regarding investments in countermeasures. The computed criticality scores are stored in the system geodatabase and may be used for further analysis e.g. of the spatial distribution of infrastructure vulnerability. This algorithm helps to identify “clusters” of infrastructures highly susceptible to a specific type of attack. Because such groups of objects may be a much more attractive target than any single infrastructure on its own, their identification should be a priority in strategic planning of resource allocation for security and attack prevention. In the Critical Infrastructure emergency management process, the algorithm is meant to be used during the Mitigation phase. The SafeCity GIS not only allows for remote execution of diverse analysis algorithms, but also enables rapid dissemination of their results between different parties. For example, an analysis of the possible outcomes of a flood hazard performed by a remote analyst may be readily accessed by rescue services on their way to the affected area. However, in case an official may not be authorized (or qualified) to use the system, the SafeCity GIS also allows for quick creation of an image file containing selected elements (e.g. thematic layers) of the produced analyses. Due to the application of Visual Analytics, the visualizations provided by the developed algorithms convey more information, which should enable quicker decision making. This in turn should increase the amount of time available for taking decisive actions. By providing a central, easy to use hub for storage and analysis of Critical Infrastructure data, the system aims to avoid some of the common bottlenecks blocking the adoption of planning support GIS. In particular, even if public services are aware of the availability of a planning support system, they often either lack the experience to make full use of the system, or simply have no intentions of using it . Because the software was built with the direct involvement of municipalities and rescue services, most of these obstacles should be removed. The sample deployment of the system in the city of Gdansk has shown that applying modern Open Source technology to processing of existing data in cooperation with prospective users results in a cost-effective solution which municipalities are eager to use. This way the system constitutes an invaluable asset in Critical Infrastructure protection, improving synergy between authorities and providing complex support in different phases of the hazard management process. It should be pointed out that the use of both the presented software and methodology is in no way limited to the described case of the City of Gdansk, but may be easily applied to any town situated in Poland, in Europe or quite likely any other part of the world which possesses a basic IT infrastructure. This, in particular, applies to small and medium-sized towns which cannot afford an extensive infrastructure security policy. The outcome of the presented study shows that the quality of Critical Infrastructure protection in such cities may be substantially improved at virtually no additional costs. It should be stressed, however, that although such software offers great help in strategic planning, it will not replace an experienced analyst who understands that eventual investments in countermeasures must be carefully balanced because an antagonist may not necessarily attack the optimal target .