Facilitating Disaster Management Using SDI

Transcription

1 Facilitating Disaster Management Using SDI A. Mansourian 1, A. Rajabifard 2, M. J. Valadan Zoej 3, I. Williamson 4 1 alimansourian@yahoo.com, 2 abbas.r@unimelb.edu.au, 3 valadanzouj@kntu.ac.ir, 4 ianpw@unimelb.edu.au 1,3 : Faculty of Geodesy & Geomatics Eng., K.N.Toosi University of Technology 2,4 : Center for Spatial Data Infrastructure and Land Administration, Department of Geomatics, The University of Melbourne Keywords: Disaster Management, Disaster response, Decision-Making, Spatial data, SDI Abstract The role of spatial data and related technologies in disaster management has been well-known worldwide. One of the challenges concerned with such a role is access to and usage of reliable, accurate and up-to-date spatial data for disaster management. This is a very important aspect to disaster response as timely, up-to-date and accurate spatial data describing the current situation is paramount to successfully responding to an emergency. This includes information about available resources, access to roads and damaged areas, required resources, and required disaster response operations that should be available and accessible for use in a short period of time. Sharing thisese information between involved parties in disaster management is a challenge to facilitate coordinated disaster response operations. This paper aims to address the role of Spatial Data Infrastructures (SDI) as a framework for facilitating disaster management. It is argued that the design and implementation of an SDI model as a framework and consideration of SDI development factors and issues can assist disaster management agencies to improve the quality of their decision-making and increase efficiency and effectiveness in all levels of disaster management activities. The paper is based on an ongoing research project on the development of an SDI conceptual model for disaster management in Iran. This includes the development of a prototype web-based system which can facilitate sharing, access and use of data in disaster management and particularly disaster response. INTRODUCTION A disaster is defined as a serious disruption of the functioning of a community or a society causing widespread human, material, economic or environmental losses which exceed the ability of the affected community or society to cope using its own resources (ISDR, 2003). Disasters are considered a tragic interruption to the development process. They cause loss of lives, disruption of social networks, and destroy capital investments, consequently diverting development funds to disaster response and recovery which directly affects the development process. According to Pelling (2003), if there could be such a thing like sustainable development, disasters would present a major threat to it or a sign of its failure. Because of the negative impacts of disasters on societies, disaster management has long been recognized by different societies as a cycle of activities (Figure 1) including mitigation, preparedness, response and recovery. It covers all management requirements before, during, and after the occurrence of a disaster. 1 Preparedness Mitigation Disaster Management Response Recovery In brief, mitigation efforts refer to those activities Figure 1: Disaster Management Cycle which reduce the vulnerability of society to the impacts of disasters. Preparedness efforts refer to those activities which make the government and disaster responders prepare for responding to a disaster, if it occurs. Response refers to the activities necessary to address the immediate and short-term effects of a disaster, which focus primarily on

2 the actions necessary to save lives, to protect property, and to meet basic human needs. Relief, rescue, search, fire fighting, permit control, sheltering, evacuation, law enforcement and many others are samples of disaster response activities. Recovery efforts refer to those activities which bring the communities back to normal (such as reconstruction) and they should be toward meeting mitigation and preparedness needs. Following this, spatial data has proven to be crucial for disaster management in such a way that without spatial data, one can not expect effective and efficient disaster management (Cutter et. al, 2003 and Amdahl, 2002). Utilization of spatial data and related technologies in managing the emergency situation at the Word Trade Center on September 11, 2001 (Bruzewicz, 2003 and Donohue, 2002) is a good example which clarifies the important role that spatial data can have in disaster management, particularly the response phase. Geographical Information System (GIS) is the underpinning technology for spatial data processing and analysis with the capability to integrate different spatial datasets -even sometimes being integrated with other Information and Communication Technology (ICT), such as Decision Support Systems (DSS), expert systems, internet, wireless applications, Global Positioning System (GPS), Remote Sensing, and simulators. In this respect, GIS is widely used in mitigation, preparedness, response, and recovery efforts all around the world to create more effective and efficient disaster management using spatial data (Lee & Bui, 2003 and Amdahel, 2002). Although there are worldwide trends on employing spatial data in disaster management, current studies reveal that there are substantial problems in the way in which disaster-related information are collected, accessed, displayed, and disseminated (SNDR, 2002). Such problems become more serious in disaster response, with its dynamic and time-sensitive nature. The dynamic and time-sensitive nature of disaster response calls for timely and rapid data collection in order to update decision-makers about the status of emergency situations for their proper decision-making followed by rapid and proper responding operations. But existing problems with data collection and access affect directly the decision-making process and consequently the disasterresponse quality. In addition, required spatial datasets are available most of the time but often difficult to access and disseminate due to different problems such as institutional barriers, unawareness about their existence, or inappropriate accessing network (Donohue, 2002; SNDR, 2002; Lee & Bui, 2003). Also there are different reports indicating spatial data are available and accessible but not integratable with each other as well as different problems on the interoperability of systems (Jain & McLean, 2003). All of these directly affect the effectiveness and efficiency of the disaster response process. It is suggested that Spatial Data Infrastructure (SDI) as an innovation in spatial data management can provide an appropriate environment in which spatial datasets are always available and accessible as well as integratable for use in disaster management, particularly disaster response. With this in mind, this paper aims to describe the development of an SDI conceptual model and a prototype web-based system that facilitate spatial data collection, access, dissemination, and usage for proper disaster management. This is based on an ongoing research and case study in Iran which investigates the role of SDI in disaster management with emphasize on the response phase, and is also based on experience of other countries in utilizing spatial data for disaster management (particularly Australia and its GeoInsight project: GeoInsight, 2002; GeoInsight, 2001). DISASTER RESPONSE COMMUNITY The variety of tasks in disaster response call for various skills and resources. Resources consist of equipment, materials, facilities, and funding, and together with people are used for affairs such as search, relief, rescue, debate removal, sheltering, medical services, fire fighting, and lifeline repairing. Different organizations own skilled people and resources that are required for disaster response and hence must share their skills, abilities and resources based on requirements. Therefore, disaster response usually calls for the cooperative efforts of a broad range of organizations such as Police, Fire, and Medical Departments, Red Cross (or Red Crescent) Society, and Utility (Water, Communication, Gas, Electricity, Sewage) Companies. 2

3 From a jurisdictional perspective, those organizations that are involved in disaster response may come from different jurisdictional levels including, local, state, national and international levels depending on the size and type of disaster. Also, with respect to the nature of involved organizations, they may be categorized as governmental and non-governmental organizations, military departments, private sector, etc. With this in mind, there are four categories of organizations which are involved in emergency management and include (Hodgkinson, 1991; Tierney, 1989 and Dynes, 1970): Group I: existing organizations that during an emergency perform the same tasks as they do in normal times. They simply do more of them during an emergency. Fire and Medical Departments as well as Police department are some examples; Group II: existing organizations which are small and fairly inactive outside emergency situations, but they increase in size during emergencies and become involved in activities. The Red Cross, The Red Crescent and voluntary organizations are some examples; Group III: existing organizations that retain their pre-emergency structure in terms of membership and management but commence those emergency-related tasks which they are not familiar with. Social Services Departments and Mental Health Services fall into this category; and Group IV: private citizens who work together in pursuit of collective goals relevant to actual or potential emergencies but whose organization has not become institutionalized. As a cooperative effort, in order to remove chaos and conflicts, disaster response should be coordinated as well. Coordination is generally conducted through an Emergency Operation Center (EOC) where representatives from different participating and involved organizations in disaster response are gathered and is based on information sharing between involved organizations with each other and with EOC. SPATIAL DATASETS FOR DISASTER RESPONSE Required spatial datasets for disaster response can be categorized as base maps or fundamental layers and emergency layers. A base map consists of datasets such as geodetic points, roads, buildings, and height points that are required as the base for mapping other data layers including emergency data layers. Emergency data layers consist of those datasets that are required for disaster response such as hospitals, fire stations, police stations, utility networks, disaster area, permit control, and burning areas. Some of the features of base maps may be customized, value-added or edited during emergency situations by disaster response organizations in order to be used as specific emergency data layers for analysis and decision-making. Some of these data layers should be collected and maintained up-to-date before occurrence of disasters (such as roads, hospitals, fire stations) but already all of the data layers need to be collected or updated after occurrence of a disaster in the aftermath of an emergency situation (closed roads, damaged area, burning/burnt area, and permit control). As was highlighted before, due to the dynamic and time-sensitive nature of emergency situations, in the aftermath of an emergency, data collection must be done regularly and in a rapid way to reflect the latest emergency situation for decision-makers. Because of the nature of disasters together with the variety of required data layers for disaster response, no individual organization can collect and keep up-to-date all of its required spatial data layers before and particularly in the aftermath of disasters by itself. Also just one organization (being assigned as responsible for data collection) cannot collect and update all of the required data layers for all involved organizations. Therefore, collecting and updating datasets for disaster response either before or in the aftermath of emergency should be done jointly and through partnerships among all involved organizations. Such collaboration and data sharing is necessary for coordinated response activities too. 3

4 A PROPOSED MODEL FOR SHARING SPATIAL DATASETS Group I and Group II of involved organizations in disaster management together consist of most of the involved organizations in disaster response. It means most of the involved organizations: either do in an emergency situation, what they really do in their everyday business (like Fire and Medical Departments), or emphasize on some specific area of their everyday tasks in emergency situation (like Utility Companies), or their everyday business concerns to preparedness efforts such as training voluntary bodies and providing required resources for disaster response, and employing them in emergency situations (like Red Crescent Society). These organizations are logically and potentially the producer and provider of up-to-date disasterrelated spatial datasets during their everyday business and during an emergency situation. If the results of such data production and updating efforts are physically recorded in appropriate databases, the required spatial datasets for disaster response is always available to the producer. If these data are shared and exchanged, then datasets are accessible to the wider disaster management community. In order for this data exchange to occur however, appropriate data standards and interoperability models need to be implemented by stakeholders so that data can be utilized within different systems. This brings the concept of partnerships in spatial data production and sharing to the fore. Through a partnership effort, it is possible to have the required spatial data for disaster management always available and accessible for use. Such participation can resolve the problem with availability, access and usage of spatial data for disaster management and particularly disaster response. Research relevant to collaborative efforts in spatial data production, sharing, and exchange however shows that there are different technical, institutional, political, and social issues that create barriers for such participation (Nedovic-Budic and Pinto, 1999; McDougall et al., 2002; Rajabifard and Williamson, 2003). Therefore, by creating an environment in which such issues are taken into consideration and resolved and consequently the access of decision-makers and disaster responders (people) to spatial data is facilitated, the concept of partnership in data production, sharing and exchange can become a reality. In this direction, Spatial Data Infrastructure (SDI, as an initiative in spatial data management) with related concepts and models, can be used as a framework for creating such an environment and consequently, facilitating disaster response. ROLE OF SDI IN DISASTER MANAGEMENT The growing need to organize data across different disciplines and organizations and also the need to create multi-participant, decision-supported environments has resulted in the concept of spatial data infrastructure (SDI). SDI is an initiative intended to create an environment that will enable a wide variety of users to access, retrieve and disseminate spatial data in an easy and secure way. In principle, SDIs allow the sharing of data, which is extremely useful, as it enables users to save resources, time and effort when trying to acquire new datasets by avoiding duplication of expenses associated with generation and maintenance of data and their integration with other datasets. SDI is also an integrated, multi-leveled hierarchy of interconnected SDIs based on collaboration and partnerships among different stakeholders. With this in mind, many countries are developing SDIs to better manage and utilize their spatial data assets by taking a perspective that starts at a local level and proceeds through state, national and regional levels to the global level. These activities have resulted in different models being suggested for facilitating SDI development. As illustrated in Figure 2, an SDI encompasses the policies, access networks and data handling facilities (based on the available technologies), standards, and human resources necessary for the effective collection, management, access, delivery and utilization of spatial data for a specific jurisdiction or community. 4

5 Viewing the core components of SDIs, Rajabifard et al. (2002) suggest that different categories of components can be formed based on the different nature of their interactions within the SDI framework. Considering the important and fundamental role between people and data as one category, a second category can be considered consisting of the main technological components: the access networks, policy and standards. The nature of these two categories is very dynamic due to the changes occurring in communities (people) and their needs, as well as their ongoing requirement for different sets of data. Additionally, with the rapid development of technology, the need for the mediation of rights, restrictions and responsibilities between people and data are also constantly subject to change. This suggests People Dynamic Access Network Policy Standard Figure 2: SDI Components (Rajabifard et al, 2002) an integrated SDI cannot be composed of spatial data, value-added services and end-users alone, but instead involves other important issues regarding interoperability, policies and networks. According to this view, anyone (data users through to producers) wishing to access datasets must utilize the technological components. With this in mind and according to the issues described earlier regarding collaboration of involved organizations in spatial data production and sharing for disaster response, it can be concluded that SDI is an appropriate framework for facilitating disaster response and disaster management. This is due to the fact that SDI can define the relation between people and data and can create an environment in which people can access, retrieve, and disseminate data, based on SDI s core component and relevant models (Figure 3). By designing an SDI model for a disaster management community, and by utilizing relevant information and communication technologies (ICT) in disaster management, it is possible to have better decision-making and increase the efficiencies and effectiveness of all level of disaster management activities from mitigation to preparedness, response and recovery phases. The result of such quality decision-making can then directly contribute to the sustainable development of the jurisdiction or community in terms of social, economical and environmental development (Figure 3). Planning Data Better Decision-Making in Disaster Management (Improved efficiency and effectiveness) Preparedness Risk Assessment & Communications Mitigation Disaster Management Response Spatial Data Infrastructure Management Recovery Institutional Framework Figure 3: SDI to Facilitate Disaster Management Within this framework, it should also be noted that the challenge of designing, building, implementing, and maintaining an SDI draws on many different disciplines and requires examination of different factors and issues relating to the conceptual, technical, socio-technical, political, institutional and financial perspectives (Rajabifard and Williamson, 2003). Therefore, it is essential that the decision-makers in the disaster management community understand the significance of these factors and also the importance of human and societal issues, which contribute to the success of SDI developments. It is note-worthy that these factors and issues should be considered in the long-term in order to achieve sustainable and ongoing development of SDIs for disaster management. In this respect, a research project is being conducted in Iran, with the aim of developing a system based on SDI to check the improvement and facilitation of disaster management (particularly in the 5

6 response phase) by such a framework. As part of this project a case study has been designed and conducted in Tehran, the capital of Iran. PILOT PROJECT: A CASE STUDY Iran is a disaster prone country and very vulnerable to different natural disasters including earthquake, flood, drought, landslide, desertification, deforestation and storms. The recent Bam (2003) earthquake which claimed more than 40,000 lives and over 30,000 injured with more than 80% of the city severely damaged and the social infrastructure totally destroyed (IRSC, 2004) is just one of many examples that describe the vulnerability of Iran especially in urban and rural areas to disasters, particularly earthquakes. Tehran, the capital of Iran, is a megalopolis of about 8 million inhabitants, which a sever earthquake is presumed for it. Studies show a strong earthquake caused by activity of the Ray Fault (one of the faults which pass through Tehran) will bring the largest damage in history to Tehran, including huge damage to buildings, urban facilities and human casualty (JICA and CEST, 2000). It is another example that describes Iran s vulnerability to disasters. During the last decade, the Ministry of Interior (MOI) has been appointed to be responsible for disaster management in Iran, with cooperation of different governmental, non-governmental and military organizations, particularly in terms of reducing disasters and their impacts. Although considerable effort has been undertaken, many activities still remain to be done in terms of effective and efficient use of new technologies, tools, innovations, and concepts to improve disaster management services in Iran. Spatial data and related technologies can considerably improve disaster management; however initial studies show that they are not yet effectively and efficiently used in disaster management, particularly for disaster response in Iran. Such inconsideration causes response to disasters particularly large ones being followed by inappropriate use of resources, inappropriate distribution of responding people, long time response lasting, etc. In this respect and based on what has been descried earlier, in order to gain easier access to spatial data an appropriate SDI can be used to facilitate disaster management particularly in the response phase. Therefore the current research is conducted to investigate the role of SDI in disaster management, with emphasize on the response phase. Two important outputs through this research are: an SDI conceptual model as a framework to facilitate the development of an infrastructure for disaster management; and a Web-based system as a tool for data sharing, data exchange and data analysis using an SDI conceptual model. The first output is to create an environment in which spatial data can be better available, accessible and used more properly to facilitate decision-making and the second output is to create appropriate software and tools for accessing and analyzing data. As described before, developing SDI for disaster management requires different technical, sociotechnical, financial, institutional, and political factors to be met, which creates a multidisciplinary environment for the research. In this regard, this research takes six phase steps for the case study. Figure 4 illustrates the overall structure of the case study. To date stage 5 of the research has been carried out and the final stage is underway. According to Figure 4, the research began with a literature review on different theories, relevant to the research with emphasis on disaster management, SDI, GIS, ICT, and organizational behavior. With this background the research continued with assessing the disaster management community of Iran and relevant organizations with respect to spatial data. In this assessment, based on current SDI models, factors that influence spatial data sharing, and factors that influence participation of organizations in SDI development (Kevaney, 1995; McDougall et al., 2002; and Rajabifard and Williamson, 2003), the disaster management community of Iran was evaluated. Basic organizational 6

7 behavior model (Robbins et. al, 1994) was recognized as an appropriate framework and was utilized in this assessment. According to basic organizational behavior model, the disaster management community consists of three tiers including individual (people), group (involved organizations in disaster management) and organizational system (disaster management community). Literature review; SDI, GIS, ICT, information system, organizational behavior 1 Assessing disaster management community and relevant organizations with respect to spatial information Developing initial SDI conceptual model 2 3 System development for disaster management 4 Conducting a pilot project 5 6 Developing/Qualifying SDI conceptual model for disaster management Feedback Figure 4: The Overall Structure of Research As a result of the assessment, the initial conceptual model for SDI was developed. The conceptual model included establishing data framework; developing standards for data collection, storing, and sharing; developing access network specifications; policy considerations; and identifying responsible organizations for data collection and updating before and in the aftermath of emergencies followed by establishing required guidelines for data collection and updating based on standards. According to the results of assessment and initial SDI conceptual model, a prototype web-based system with GIS functionalities was developed as a tool for data updating, sharing, and analysis and consequently facilitation of decision-making process based on the SDI concept. Based on the initial SDI conceptual model and developed prototype system, a pilot project with cooperation from twelve organizations in the disaster management community was conducted to respond to an assumed earthquake disaster. The main aims of conducting the pilot project were: to demonstrate the application and advantages of spatial data and related technologies for disaster management and consequently increasing the awareness of disaster management community in this respect. Such awareness would help the research project and proposed models being supported by disaster management community; to demonstrate the advantages of SDI for disaster management community and to get their support to commit to long term development of SDI; and to use the feedback of the pilot project for qualifying the developed SDI conceptual model and design and development of prototype accessing network. In this pilot, a maneuver scenario was defined with which involved organizations could experience a coordinated disaster response based on spatial data sharing and analysis. Prior to conducting the maneuver, required spatial datasets were collected from different organizations. They were prepared based on developed SDI standards and integrated with the system. Also, training about the system and its usage, and individual responsibilities on collecting and updating datasets was carried out. During the maneuver, each organization updated its own spatial datasets within responding operations, and shared them with the disaster response community. Therefore each individual responding organization had access to required spatial datasets to integrate and analyze their datasets using GIS functionalities to support their own decision-making for disaster response. 7

8 Based on the results of the pilot project and the initial SDI conceptual model, the actual SDI conceptual model for disaster management was developed. Feedback of the results of the pilot project also will be used for design and development of a functioning system according to the prototype system. Based on the SDI conceptual model and proposed system, different maneuvers are going to be conducted to qualify the developed SDI conceptual model. The double-ended arrow in Figure 4 illustrates this matter. Following the results of organizational assessment, SDI Conceptual Model, and prototype webbased system have been described. The results of the pilot project have been described in the conclusion. ORGANIZATIONAL ASSESSMENT Results of organizational assessment showed that development of SDI for disaster response in Iran is a matter of social, technical and technological, political, institutional and economical challenges. There are various social challenges that were identified as aspects that need to be emphasized in order to facilitate the SDI initiative. The first is the need to increase peoples awareness of the value of spatial data for disaster response and in everyday business of organizations (responsible organizations in disaster management affairs) at policy, management and operational level (based on organizational pyramid model: Petch and Reeve, 1999). Other challenges include skill formation (working with and interpreting GIS and GPS data) and cultural issues in the use and sharing of spatial data. Increasing the awareness is a key factor in developing SDI for disaster response as it affects other factors in any three levels of disaster management community (people as individual level, involved organizations as group level, and disaster management community as organizational level). Having a clear strategic plan with respect to disaster management and spatial data is essential but currently neither exists at the group level nor at the organizational level of disaster management community. Also, clear regulations and policies are required at both group and organizational level to exist that clarify the custodianship of datasets, access policies, and dissemination policies in the context of copyright and privacy rules as well as security considerations. In addition, policies are required with respect to inclusion of private and academic sector and appropriate use of their capabilities in terms of spatial data. These are also other challenges that should be considered in the context of social challenges. With respect to technical and technological challenges, several areas were identified as needing emphasis including: development of appropriate standards that support applicability of organizations datasets in GIS environment with respect to disaster response requirements, providing the interoperability of systems of organizations and integratability of their datasets with each other; increasing the technological capabilities of individual organizations and the disaster management community particularly with respect to space technologies (GIS, GPS, remote sensing, laser-scanning, LIDAR, thermal imagery, etc.),telemetry and telematics solutions (for lifeline networks, control traffic, and tracking vehicles), networking, and communication facilities; and equipping Emergency Operation Center with required hardware and software for data analysis and facilitating decision-making. In terms of institutional challenges, four main areas were identified as needing emphasis: establishing a formal structure for GIS and spatial data affairs at group and organizational level of disaster management community; 8

9 establishment of good relationships between organizations for data sharing by appropriate agreements that respond to needs of organizations and increase their willingness to participate; establishment of appropriate relationships between governmental, private and academic sectors to better utilize their capabilities; and including those organizations and groups (e.g. national mapping agencies) that can provide required data for disaster response. With respect to political challenges many factors affect participation of organizations in SDI initiative such as the current political environment of the country, ministry of Interior, and other involved organizations; interest of national mapping agencies and the historical relationship between organizations. Finally, financial resources are required as important support for SDI initiative in the context of economic factors. SDI CONCEPTUAL MODEL As was described earlier the five core components of SDI establish the relation between people and data through technological components (standards, policy and access network) (Figure 2). In light of standards and policy components, producers can produce data free of duplication of effort and share them to be accessible and applicable for users (including value-adders and end-users). Value-adders can access and enrich data for end-users, other value-adders, and their own use; and end-users can easily access and use data during their business. This is done through the access network component, which provides a physical environment for dissemination of data and access for use. The five core components of SDI and their relationships (Figure 2) can also be regarded as a conceptual model as it describes a system in generic terms without reference to particular implementations (Davies, 2003). With this in mind, the SDI conceptual model for disaster response was developed by expanding and clarifying each of the core components of SDI with respect to the results of organizational assessment (Figure 5). As Figure 5 shows, with respect to people, three categories were identified including data providers, data analyzers, and end-users (decision-makers and field staffs) and for each category responsible organizations and their responsibilities were clarified. Standards, interoperability, metadata standards, data quality standards, and process standards were identified as disaster response requirements with respect to spatial data to support the reliability, currency, interoperability, integratability and accuracy of datasets as well as interoperability of systems that are used during disaster response. SDI development model, institutional arrangements, standards, access, financing, and influencing partnership (including environmental factors, capacity factors, and SDI organization; Rajabifard and Williamson, 2003) were identified as six important factors in the context of policies. Access mechanism, network mechanism and response time were also identified as three main factors with respect to accessing network. With respect to data, scale and resolution, content, capture (tools and mechanisms), access and analysis tools, database management, and metadata were identified as important factors and each one was clarified. 9

10 People Standards Policy Accessing Network Data Interoperability Metadata Process standards Data quality Scale & Resolution Data provider Institutional arrangement SDI Model Content Capture Data analyzer Access Standards Access and Analysis tools End-user Influencing partnership Financing Databases management Metadata Access mechanism Network mechanism Response time Figure 5: Schematic presentation of SDI conceptual model for disaster response PROTOTYPE SYSTEM FOR DISASTER MANAGEMENT BASED ON SDI Figure 6, illustrates an overall picture of the community and the linkage between developed systems as well as their databases to the Emergency Operation Center (EOC) database via a network. This structure has been used as a base to design the web-based system for disaster management. As Figure 6 illustrates, based on technical and institutional capacity of the disaster management community, the system was designed using a centralized data model. Within this model, each organization has a database containing its required datasets for everyday business as well as disaster response (This database may be a central database and within the internal network of organizations). There is also a database in the EOC where the representatives of involved organizations can gather to coordinate disaster response. The EOC Database contains base maps as well as fundamental required datasets for disaster management. Each of the involved organizations is responsible for updating one or more datasets within the EOC database before and after a disaster. Each organization can then utilize required datasets from the EOC database for their own use. This demonstrates the important concept of partnerships in producing and updating datasets, as well as the concept of sharing datasets, which allows each organization to work on a common database. As Figure 6 shows, all of the organizations are connected to the EOC database through inter- or intranet. This is the network that organizations can use for data sharing and access their own required datasets. The ability of all parties to have access to information that describes a current emergency situation through the development of the EOC database will enable a more coordinated response to disasters. Within this environment, the process of producing, updating, accessing and using spatial data is 10

11 carried out based on an SDI framework. This framework defines standards (data standard, metadata standard, system interoperability, etc.), policies (partnership, accessing rules, funding, etc.), people (training, cultures etc.), access network, and data framework. EOC SDI Environment LAN (WEB) EOC WAN (WEB) Police Department Fire Department Medical Service Communication Company Electricity Company Red Crescent Society Other Org. (Gas, water, ) Figure 6: Overall Picture of a Web-Based System to Facilitate Disaster Management Using an SDI Environment Based on this overall picture of disaster management community, a technical and architectural design was carried out as a prototype to serve the community and it was qualified based on the feedback of the maneuver. Figure 8 illustrates the technical architecture design of the prototype system. It is based on a web-based GIS for data input, access and analysis both in the EOC and within each of the involved organizations. The system was designed based on a combined model of thick-client and thin-client (two different architectural models for developing web-based GIS). As Figure 8 illustrates, each of the involved organizations has their own database including their relevant datasets that are regularly updated by organizations and used for daily activities and responding to disasters. Each of the involved organizations (clients) can also access the EOC database through a web-based system. The web-based system is based on five core components including user interface for clients to access and analyze data, web server and application server for getting the clients request and sending it to map server, map server for data analysis and query based on clients request, data server for retrieving data from a database and serving them to map server for analysis, and database that includes spatial data. Figure 7 illustrates the core components of web-base system and their relation with each other. User Interface (Client) H TML, ActiveX, Request Map Web Server & Application Server HTTP Translate Map Server Data Server Database GIS Analysis Engine Spatial and Aspatial Data Figure 7: Core Components of Web-Based System and Their Relations 11

12 These core components are categorized in three tires including presentation, logic and data tiers (Figure 8). In presentation tier which relates to client side, the user interface is based on a webbrowser and is developed based on ActiveX controls. ActiveX control, which is developed by Microsoft and based on OLE standards, is a modular piece of software that performs tasks and communicates information to other programs and modules over the internet/intranet. Using ActiveX controls together with programming languages such as C++ and Visual Basic a user interface for each client, based on its own GIS analysis requirements was developed. As Figures 7 and 8 illustrate, the involved organizations (clients) send their request to a web-server (in logic tier) via web-browser. Then web-server sends it to map servers via application server (as translator between web server and map server). In this design, several map servers have been considered. Therefore, the system has the capability of responding to concurrent requests from different clients. For example, if the first request from one of the clients regarding getting a part of specific dataset from EOC database is time consuming for the first map server to process, the second request from another client can be processed by other map server. The request is checked in terms of the permission of user to access the requested dataset and security considerations. Then it is sent to data servers which serves the requested dataset from the EOC database and sends it to the client as Figure 8 shows. A replicate mechanism has been considered in the system. Based on this mechanism when a dataset is updated by a client in its own database, it is replicated in EOC database, based on defined criteria in the SDI model. Because different clients have access to the database, particular attention needs to be attended for maintaining the security of the database. It is conducted using security elements that have been considered in the system. These elements control the access to databases. There is also an access record element that records the details of access to databases consisting of client IP, time of access, kind of request, etc. This is metadata about different accesses which can be referred in anytime and be reviewed if it is required. In Emergency Operation Center (EOC), representatives of organizations have access to EOC database through another web-based system which can be based on a Local Area Network (LAN). Having access to EOC database, EOC is aware of the latest status of emergency situation for general planning, coordinating the response process, and controlling the situation. For the EOC and each of the clients databases, one or two mirror databases have been suggested as a backup version. These mirror database(s) consists of the same data that exist in its relevant original database. Any change in the original in terms of producing and updating a dataset is replicated and recorded as backup in a mirror database in real time. If there is any problem with the original database, its mirror becomes active automatically. With such a design, the system is always operational and it doesn t stop due to database damage. The mirror database(s) should be located far from their originals (and each other if more than one mirror exists) for security reasons. According to Figure 8 the system can be improved by employing Mobile GIS technology, in such a way that the field staff relevant to involved organizations can update the current situation of emergency in their own organizations databases using a Mobile GIS system. They can also have access to EOC database and their organizations database for field operations. 12

13 Mirror s Clients s Presentation Tire (User/Client) Web-Based GIS Logic Tire (Server Level) Data Tire 1 2 Client 1 (Police) Other Software/ Tools Client 2 (Fire Dep.) Other Software/ Tools Web Browser Web Browser Request Exchange Web Server Application Server Connectors (CGI extensions) Mirror Mirror LAN (Web GIS) 3 Client 3 (Gas Com.) Other Software/ Tools Web Browser Application Server EOC 4 Client 4 (Medical Ser.) Other Software/ Tools Web Browser Map Servers MS 1 MS 2 MS n Security c3 c2 c4 c5 EOC c6 n Client n (Other Org.) Other Software/ Tools Web Browser Permission Security Replicate Access Record DS 1 Data Servers DS 2 DS 2 c1 cn Some of the Selected Datasets Access Record Mobile GIS Permission / Security/ Access Record Web Server - Map Server Wireless Communication Gateway Services -.. C1 C2 Cm Field Staff as Clients Figure 8: Technical Architecture of Prototype Web-Based System 13

14 CONCLUSION This paper aimed to address the role of SDI as a framework for facilitating disaster management. In this respect, an SDI conceptual model and a web-based system that works based on SDI was developed. The developed system was tested in the context of a pilot project with the cooperation of 12 organizations from local and national levels to respond to an assumed earthquake in Tehran. The results of the pilot project showed how useful a web-based system that works based on SDI can be for effective and efficient disaster response management. The effectiveness and efficiency of the system can be interpreted by different elements, however, in this research reducing the response time and removing chaos by better management and coordination were considered as two evaluating factors. It was estimated that for each of the involved organizations, such a system can help in reducing the response lasting time, at least to 1/3 of current situation, by having all information available and accessible, and conducting appropriate planning prior to operational responding. Definitely, better results in terms of time saving will result if other factors such as coordinated response between involved parties are applied to this estimation. Time saving is an important outcome for disaster response in an emergency situation with its time-sensitive nature. Also, the pilot project showed that using a system that works based on SDI, and having all information about the current situation of emergency response in EOC database, how easily the EOC can contribute to overall planning for response, controlling the situation, and managing the emergency to remove chaos in disaster response by better inter-organizational coordination. In addition each of the involved organizations could improve their internal coordination, having all of the information describing the latest situation of an emergency available, accessible and interoperable for use. In fact, such results were expected to be achieved because the essence of spatial data in disaster response has long been well-known among disaster management communities in such a way that different GIS and modeling systems that work based on spatial data have been developed by them. But the main problems that the research can aid are relevant to availability, accessibility and interoperability of spatial data. It should be noted that due to the dynamic nature of SDI and also the dynamic nature of disaster management capacity (from social, technical and technological, political and financial perspectives), the SDI conceptual model and web-based system need regular refinement. Not only can such a system considerably improve the disaster response process, but it can also improve any other disaster management operations, by providing required spatial datasets for involved organizations. Improvement of disaster management has considerable effect on sustainable development of countries as it has direct effect on economical, social and environmental factors as three main components of sustainable development (Figure 3). For example appropriate mitigation efforts using up-to-date spatial data, reduces the economic loss from disasters and affects the economical aspect of sustainable development. Mitigation together with appropriate disaster response and recovery efforts will improve bringing back the quality of life to society in the context of social aspects of sustainable development. Also appropriate mitigation and response efforts have considerable affect on the environment, by protecting the environment from a disaster or reducing the impacts of disasters on the environment. Mitigating wild fires or rapid response to wild fires in order to limit their negative impacts are samples of effects of appropriate disaster management on sustainable development with respect to environmental aspect. ACKNOWLEDGEMENT The Authors would like to acknowledge the support of National Disaster Task Force of Iran, Tehran Emergency Management Center, K.N.Toosi University of Technology and University of Melbourne as well as the member of the Center of Spatial Data Infrastructures and Land Administration at the 14

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