Information Sharing During Emergency Response and Recovery A Framework for Road Organizations André Dantas, Erica Seville, and Dharmista Gohil in recent years (3–7). Nevertheless, after studying various implementations of GIS in emergencies, Zerger and Smith (8) concluded that most case studies do not have a real-time capability and require events to be premodeled. According to the National Research Council, “experience has shown that it is critical, in applying IT to disaster management, to start with real problems faced by real end users, to find solutions, and then to work back from there to overarching themes. Starting with overarching themes will lead to dead-ends, and unimplemented and un-implementable technology” (9). This paper takes an end user–centric approach rather than a platform-centric approach in the design of an information-sharing framework for New Zealand road organizations. In the light of information management concepts and principles, the framework is the result of conducting comprehensive analyses of the nature and background of involved organizations, the characteristics of their involvement, their data and information needs, their data- and information-sharing needs, and how organizations could and should share data and information.
Road organizations are involved in a wide range of emergency response and recovery activities. Information sharing is a critical element in deploying road organization resources during such activities. This paper presents an information-sharing framework for road organizations. On the basis of a study of response and recovery activities, information needs were identified and a geographic information system–based information-sharing framework was created. The framework is applied to a desktop case study in the South Island of New Zealand to establish the magnitude of potential benefits. Results indicate that a reduction in time and cost of emergency response activities could be achieved if the conceptual framework was implemented through reduced response times, faster access to relevant information, and therefore enhanced decision making.
Road organizations are involved in a wide range of emergency response and recovery activities. Damaging events of various magnitudes such as car accidents, snowstorms, floods, earthquakes, and volcanic eruptions may affect road assets and disrupt the road network throughout the country. Local, regional, and national road organizations conduct response and recovery activities, which involve the deployment of resources to minimize disruptions due to road closures. Information sharing is a critical element in deploying road organization resources during emergency response and recovery activities. Without collecting, collating, and communicating data and information among multiple organizations, damage may not be properly assessed and resources adequately deployed, which may cause inefficient coordination and decision making (1, 2). Even a small event such as a car crash may result in a short or a long road closure. In contrast, an earthquake event, for example, requires intensive exchange of damage and resource deployment information that may save lives and reduce disruption. These complexities emphasize the need to develop robust yet simple frameworks for sharing information and communicating decisions within and between organizations involved in response and recovery activities. Although the importance of information sharing during emergency events is widely acknowledged, current techniques are limited in fulfilling the needs of emergency management practitioners. Technological advances in information management of spatial–temporal data such as geographic information systems (GIS) have been made
EMERGENCY MANAGEMENT IN NEW ZEALAND In New Zealand, the Ministry of Civil Defense and Emergency Management (MCDEM) is a semiautonomous body within the Department of Internal Affairs. MCDEM has overarching responsibility for developing and maintaining the preparedness of the New Zealand community for any natural and technological hazards or disasters (10). Created in 1999 from the former Ministry of Civil Defense, MCDEM also provides policy advice to the government (11). In 2002, the Civil Defense Emergency Management (CDEM) Act established a national and regional framework in which an emergency management strategy and plan were adopted. One of the features of the act is the establishment of CDEM groups based on regional council boundaries and the requirement that a risk management–based approach be adopted. CDEM groups are consortia of local authorities, emergency services, and health boards in each region. The CDEM Act requires every local authority to plan and provide for CDEM within its district and to ensure that it is able to function to the fullest possible extent, even though this may be at a reduced level, during and after an emergency. The requirement also applies to lifeline utilities and central government departments. MCDEM works in coordination with local and regional governments, utilities, and the emergency services involved in CDEM. MCDEM’s director acts as chief executive of the ministry in its day-to-day operations. In cases of national emergencies, the director has special powers defined in the legislation.
Resilient Organizations Research Programme, Department of Civil Engineering, University of Canterbury, Private Bag 4800, Christchurch 8140, New Zealand. Corresponding author: A. Dantas,
[email protected]. Transportation Research Record: Journal of the Transportation Research Board, No. 2022, Transportation Research Board of the National Academies, Washington, D.C., 2007, pp. 21–28. DOI: 10.3141/2022-03
21
22
In the event of a civil defense emergency declaration, the CDEM group (or local) civil defense controller coordinates the response and makes decisions about response priorities after communication and consultation with the emergency services, health agencies, and key lifeline organizations. The regional and national CDEM emergency operations centers interact with these organizations to facilitate and support decisions on prioritization of response activities. Relevant information from all the above organizations is expected to be shared with CDEM agencies to facilitate decision making.
ROAD ORGANIZATIONS AND EMERGENCY RESPONSE IN NEW ZEALAND New Zealand has about 10,000 km of state highway network. These roads are a national asset worth approximately NZ$12 billion, and Transit New Zealand (NZ) is responsible for maintaining and enhancing them. Fifty-six percent of the annual budget is allocated to the maintenance and rehabilitation of existing roads (12). Typically, Transit NZ appoints consultants to undertake technical services to determine work requirements according to directives of Transit NZ regional offices and contractors to carry out the physical work (13). The state highway network is divided into seven regions, each with its own consultant and contractor arrangements. This structure provides the state highway network with some resilience during emergencies in that many of the consultants and contractors are national or even international organizations. Thus, resources can be brought in from other areas to boost those available to an affected region during a crisis. However, this structure adds complexity that needs to be recognized and managed. As the number of organizations involved in response and recovery increases, particularly if an emergency spans more than one region, communication and sharing of information within and between organizations become more complex to manage. The Transit NZ emergency response process can be divided into six core elements: event warning, event observation, event assessment, organization action, organization reporting, and organization reevaluation. During reevaluation, the outcomes are used to decide whether the response is considered over or should be continued from event assessment. The dynamic nature of emergency response is such that many elements of the response process are conducted simultaneously, and the appropriateness of different response strategies must be constantly reevaluated as the event develops. Different organizations are involved in each stage of the response process. In the event warning phase, external organizations such as research institutes, meteorological services, and regional and local councils provide initial warnings and updates of potential events. During or after the event (event observation phase), the contractor, external organizations, and the public verify initial damage caused to the transportation system (pavement and bridge collapses, obstruction of lanes, etc.). Depending on the extent of damage, these conditions are reported to the consultant, Transit NZ, local road controlling authorities, emergency services and other lifeline organizations, and if a civil defense emergency has been declared, the regional or national CDEM emergency operations center. In the subsequent phase (event assessment), again depending on the type of the emergency, all the above organizations except external organizations and the public are involved. Organization action involves the same organizations deploying their physical and personnel resources according to their responsibilities. Most of the field operation is conducted by the contractors in small and medium events.
Transportation Research Record 2022
In large events the CDEM controller, lifeline organizations, and local and regional authorities are also involved. These actions are supervised by the consultant and Transit NZ. As part of organization reporting, the contractor, CDEM, local and regional authorities, and lifeline organizations describe current road conditions after the initial round of measures and any further development of the original event (better information about damage, more events, etc.). These reports are taken into consideration during organization reevaluation, in which the organization evaluates the measures taken and their efficiency. Finally, decisions are made as to whether to continue or stop response activities depending on the efficiency assessment. If a decision is made to continue, the process restarts from event assessment. Emergency situations are classified by Transit NZ into three levels according to the time required for road reopening: small (a specific part or segment of the state highway network is affected for less than approximately 6 h), medium (multiple parts or segments of the network are affected for up to 1 day), and large events (severe damage to the network or other lifeline infrastructure systems and lifethreatening situations are observed, prompting MCDEM to dictate response and recovery priorities) (13). Organizations involved in response and recovery activities need a large variety of information. To act in a coordinated and effective way, organizations require access to data and information characterizing the disaster’s intensity and location and related damage, as well as the availability of human and physical resources. Organizations will have their own particular information needs, which may be different for each level in the organization. For example, Transit NZ headquarters personnel in Wellington will need general road closure information such as summary of damage, expected opening, and forecast recovery cost. In contrast, the Transit NZ network engineer will need access to much more specific information about damage, work progress, costs, and resource availability. The two sections will make their decisions concerning allocating resources over time and space on the basis of the available information.
EMERGENCY RESPONSE INFORMATIONSHARING FRAMEWORK FOR NEW ZEALAND ROAD ORGANIZATIONS The information-sharing framework was developed by applying the concepts of knowledge and information management (14). The first step in the process was to identify the information needs of the organizations involved in response. That was done by examining Transit NZ’s emergency procedures and reports and translating them with the Integrated Definition modeling language (semantics and syntax) (15) into a summary of information needs and sources during each phase of the response and recovery effort (Table 1). These information needs were then considered in the conception of the data- and information-sharing framework presented in Figure 1. The framework uses Transit NZ’s current inventory database to generate a dynamic geographic information system (DGIS) for emergency response. Transit NZ’s inventory database (RAMM) comprises historic data on road assets and their condition over time. In an emergency response event, the framework proposes that data from RAMM be dynamically retrieved, organized, and distributed among consultants, contractors, and Transit NZ by using the DGIS. The framework establishes the linkages, templates, and sharing standards to enable the conversion of road maintenance data (RAMM) into information required during emergency response activities (DGIS).
Event reassessment
Event reporting
Resources deployment
Event assessment
Comparison before and after/damaged asset (location; original condition; characteristics; treatment options; costs; priority; repair availability) Contractors’ available resources Stop response/initiate recovery mode/continue response?
Damaged area/region Type of event Damaged asset type Partial or complete road closure Alternative roads Traffic flow composition Contractors’ resources Civil defense emergency declaration? Comparison of damaged asset before and after event Location Original condition Characteristics Treatment options Costs Priority Repair availability Contractors’ available resources Location of contractors’ equipment and personnel Deployment times Allocation plan of resources and personnel per damaged asset (location; original condition; characteristics; treatment; priority; effectiveness) Traffic management plan MCDEM emergency declaration? Damaged area/region Attributes of damaged assets (location; original/current conditions; characteristics; treatment; costs; priorities; repair availability)
Regional Consultant Information Needs
Damaged asset type Attributes of damaged assets (location; original/current conditions; characteristics; treatment; costs; priorities; repair availability) Partial or complete road closure Alternative roads Traffic flow composition Contractors’ available resources
Allocation plan of resources and personnel per damaged asset (location; original condition; characteristics; treatment; priority; effectiveness) Deployment times Traffic management plan MCDEM emergency declaration?
Potential damaged area/region Type of event Intensity and expected duration Available resources Damaged area/region Type of event Attributes of potentially damaged assets (location; original condition; characteristics; costs; priority; repair availability)
Regional Contractor Information Needs
Transit NZ’s and Response Partners’ Information Needs in Response Activities
Event observation
Event warning
TABLE 1
Report on before and after/damaged asset Summary of damaged assets per type, treatment options, costs, and priorities Repair availability Consultants’ and contractors’ available resources Initial road closure time cost estimation Stop response/initiate recovery mode/continue response? MCDEM emergency declaration?
Damaged asset type Partial or complete road closure Alternative roads Traffic flow composition Contractors’ and consultants’ available resources Road closure time/costs estimation MCDEM emergency declaration?
Damaged area/region and event type Damaged asset type Partial or complete road closure Alternative roads Traffic flow composition Contractors’ and consultants’ available resources Initial road closure time/costs estimation MCDEM emergency declaration? Report on before and after/damaged asset Summary of damaged assets per type Summary of treatment options Summary of costs/priorities Repair availability Consultants’ and contractors’ available resources Initial road closure time estimation Initial cost estimation MCDEM emergency declaration?
Transit NZ Regional Office Information Needs
Report on road closures (location; partial/complete; expected road opening) Consultants’ and contractors’ available resources Initial cost estimation
Report on road closures (location; partial/complete; expected road opening) Consultants’ and contractors’ available resources Initial cost estimation
CDEM Group Information Needs
24
Transportation Research Record 2022
Nonwarning event
Highway maintenance and operation
Event warning (B)
(A)
RAMM Data extraction from RAMM Road closure
ID X (C )
Emergency resources preparation
Y
Z
i
Xi Yi
Zi
j
Xj Yj
Zj
(D)
… … … … … … …
T
V
$ $$
Ti Vi $i $$i Tj Vj $j $$j
(E)
(Aa)
DGIS MAP -potentially affected region-assets
-MCDEM -Local/regional authorities
DATA-Potentially affected region-assets
ID X
V
$
i
Xi Yi
Y
Zi Ti Vi
Z
T
$i
j
Xj Yj
Zj Tj Vj
$j
(S)
Sharing - Lifeline organizations - Transit NZ HQ
MAP - damaged assets
MAP – resource allocation
(N)
(K )
(G)
(P1)
(L1)
(Aa)
Initial assessment
Treatment decision (J )
Reporting
(H )
(L2)
(M)
(P2 )
Results reporting
(Q)
Efficiency assessment
Resource deployment (R)
Key: (4b)
FIGURE 1
Event Data/info flow
Aa
Preresponse data/info flow
Consultant’s action
Contractor’s action
S
Internal-external data/info flow Database
External data sharing
Data and information framework for road organizations.
For example, during an emergency event with warning (e.g., flooding), the framework (see Figure 1) is applied by following the steps below: • Preliminary information (Arrows A and B) on the potentially damaged region and assets is used by Transit NZ, consultants, and contractors in generating data and information related to the potential emergency by using RAMM (C), and emergency response resources are placed on alert (D). • The relevant information is then extracted from RAMM by the consultant (E) and linked to maps by using the DGIS.
• During and after the hazard event, contractors receive information from the police and the public about road closures and damage. • On the basis of data from DGIS (G), the contractors perform an in situ initial assessment by comparing observed conditions with road characteristics before the event (e.g., bridge abutment collapsed, signpost missing). • The observed conditions (H) are summarized and reported back to the consultant via the DGIS database (J). • The consultant retrieves data on the damaged assets (K), and in view of the available resources, a treatment decision is made (L1) and shared with the contractor (L2).
Dantas, Seville, and Gohil
25
• The contractor deploys resources to implement the treatment; actual resource deployment is recorded (M) in the DGIS database. • After the completion of the work, the contractor compares conditions before and after the event (N) and conducts a results reporting, which is subsequently recorded (P1) in DGIS. • The consultant retrieves data (P2) and conducts an efficiency assessment in which the response is either finalized [road opening (Q)] or continued (R). • If the response is continued, the consultant restarts the process from the treatment decision phase. During all the response phases, data are simultaneously shared with all other involved organizations (S). These organizations also input new information, which is shared among Transit NZ’s consultants and contractors. Transit NZ regional engineers can either act as observers for small events or become involved with the decision-making process. For events without warning (e.g., car accidents, earthquakes), the same phases are followed except for the initial preparation (emergency tables preparation and emergency resources preparation).
Study Area and Data Sources The case study consists of road closures in the South Island of New Zealand. South Island occupies 151,215 km2 and has approximately 5,000 km of state highway network. The organization responsible for the maintenance of the state highway network is Transit NZ, which has divided South Island into six regions: North Canterbury, South Canterbury, West Coast, Coastal Otago, Central Otago, and Southland. Each region has a contractor and a consultant for the construction and maintenance of the state highways on contractual bases. During the case study, Opus International, Limited, had the contract for consultation with Transit NZ for all the regions except Coastal Otago. The road closure data used for applying the data and information framework were obtained from Opus International’s office in Greymouth. The database comprises information such as closure date, closure time, open date, open time, route station, route position, location, closure type, closure reason, comments, and region. The number of road closures recorded during the 1-year period (April 2004 to March 2005) is 113. Figure 2 shows a GIS map with the road closures categorized by road closure type.
CASE STUDY This proposed information-sharing framework was applied in a desktop case study in the South Island of New Zealand to establish the magnitude of potential benefits. This section describes the implementation issues and a comprehensive analysis in terms of cost (in New Zealand dollars) and duration (in minutes) of response activities with and without the data and information framework.
Information-Sharing Framework Applied to Road Closure Example The information-sharing framework is applied to a road closure that occurred on Saturday, January 8, 2005, at 5:00 a.m. The road between Tapanui and Gore (Pomehaka Bridge) was closed by the contractor because of flooding. The road was reopened after 37 h 40 min on
Black Ice Fire Floods Rain Snow Bridge Washout State Highways Contractor’s Office C Consultant’s Office New Zealand coast
C
C
C
C 0
40
80
FIGURE 2
120
160
200 km
Road closures by closure type.
C
26
Transportation Research Record 2022
January 9, 2005, at 18:40:00. Each of the response phases using the data and information framework is explained below.
8
ARTe [EL; Y ] = ∑ AT p [EL; Y ]
(3)
p =1
• On the basis of a warning from MetService, RAMM database and DGIS maps are selected for the potentially damaged areas. • The consultants retrieve the data from RAMM and export the data to DGIS. The map showing the roads likely to be damaged and other features (signs, bridges, etc.) with their exact location is displayed along with their attributes (signpost ID, type of signpost, foundation, bridge name, length, etc.). • When the disaster occurs, the contractors go on site while the consultants fill in the details in an emergency response form. These data are then shared with the other road organizations and civil defense. The contractor accesses this information by using a personal digital assistant or cell phone with mapping facilities. In addition, information from the police and other first responders is added to DGIS. • Once the contractor reaches the road closure site, the actual damage at the site is examined and then updated in the DGIS and shared with the consultants and other road organizations. • The consultants then assess the damaged condition on the basis of the data and information provided by the contractor in DGIS and make decisions about the treatment to be given and prioritization of the work. The decision is made and shared in DGIS by the consultants. The contractors make the repair in accordance with the instructions given by the consultants or civil defense. • After the repair is made, the contractor reports back to the consultants on the condition of the road. The condition of the bridge and the reinstallation of the signpost are reported back on DGIS. • The consultants then decide whether the repair is done or the work is to be continued. After all the repair work is done, the road is reopened to traffic.
Assessment of Time and Cost Saving Using Data and Information Framework To estimate the time and cost saving attributable to use of the data and information framework, the time and cost of disaster response on the basis of current practice and on the basis of the data and information framework are calculated. Since only the total time for disaster response is available from the road closure data, it is subdivided into time periods for each phase by using a set of assumptions. In addition, road closure costs are assessed on the basis of road traffic and time of closure (morning or afternoon). A road closure event e that had a response time (RTe) is classified according to its type (Y ) and emergency level (EL). Each event is also associated with a set of response phases p, where external agency or police contact consultants (p = 1), consultants contact contractors ( p = 2), contractors reach the disaster-affected site (p = 3), contractors inform consultants of actual site condition (p = 4), a decision is made on the treatment by contractors and consultants ( p = 5), contractors wait until condition is suitable for repair or to get orders from MCDEM ( p = 6), repair done (p = 7), and report to consultants ( p = 8). When all the data are combined, each event (e) can be described as in Equations 1, 2, 3, and 4. p e = {Y ; EL; tEL; Y}
(1)
⎧1 if RTe < 6 h ⎪⎪ EL = ⎨ 2 if 6 ≤ RTe < 24 h ⎪ ⎪⎩3 if RTe ≥ 24 h
(2)
n
AT [EL; Y ] = p
∑t
p
[EL; Y ]
e =1
n[EL; Y ]
(4)
where Y = event type (1 = car crash, 2 = snowfall, 3 = slips, 4 = volcanic eruption, etc.), ARTe[EL; Y] = average time for road reopening for an event e of level EL and type Y, ATp[EL; Y] = average time for each phase p and emergency level EL and type Y, t p = time for each phase p for each event e, and n = number of events of same type Y and same emergency level EL. To assess the efficiency of the information-sharing framework partially, the travel delay costs to road users are estimated. The average cost of the road closure (AC) is dependent on the type of road closure, the level of emergency, and the response phase duration. The total cost of a road closure is the summation of all costs for each phase, which is given in Equation 5. CPep = t(pEL ; Y ) ×
ACe ARTe
(5)
where ACe = average cost of road closure for total time of road closure to the user, ARTe = average road reopening time for a road closure event e for emergency level EL and type Y, CPep = cost per phase p for an event e, and t p(EL; Y ) = time for phase p for an emergency level EL and type Y. The implementation and operation of the data and information framework are expected to reduce the response duration for some of the phases. There may not be any change in time for some phases; however, the overall time is likely to be reduced. Since Phases 1 and 2 are solely related to communications, it is assumed that DGIS will not have a major impact in reducing response times. For all the other phases, a reduction can be achieved by adopting the following measures: • Phase 3 (time taken for contractor to reach the site): This time can be reduced if the contractor has a GIS map showing the exact location of the road closure site. The amount by which this time is reduced may be assumed to be between 1% and 5% of the original time. • Phase 4 (contractor informs the consultant of the site condition): This time can also be reduced by using the information framework by between 1% and 5% because the contractor has the details of the road site in DGIS. • Phase 5 (decision-making stage on the treatment to be given): The time can be reduced by 10% to 15%, since all the data and information are available for the decision to be made quickly. • Phase 6 (waiting time for orders from civil defense in case of large events): The time for this phase can be assumed to be reduced by 10% to 15%, because civil defense will have the GIS maps and the required information based on which the decision may be made faster than under current practice.
Dantas, Seville, and Gohil
27
• Phase 7 (the time taken to do the repair work): The time may be reduced by 1% to 5% if the contractor has the map of the existing road features and so forth before the road closures. • Phase 8 (consultants can report back to civil defense and the contractors concerning the condition after the repair): The time can be reduced by 1% to 5% with the use of the framework. On the basis of these assumptions, three scenarios are created as summarized in Table 2. For Scenario 1, the durations of Phases 1 and 2 are not reduced, but those of Phases 3, 4, 7, and 8 are reduced by 2.5%, and those of Phases 5 and 6 are reduced by 12.5%. For Scenario 2 (best-case scenario), the durations of Phases 1 and 2 are not reduced, but those of Phases 3, 4, 7, and 8 are reduced by 5%, and the durations of Phases 5 and 6 are reduced by 15%. Finally, for Scenario 3 (worst-case scenario), the durations of Phases 1 and 2 are not reduced. The durations of Phases 3, 4, 7, and 8 are reduced by 1%, and the durations of Phases 5 and 6 are reduced by 10%. The percentage reduction in time is applied to all the phases for the three scenarios to calculate the reduction in time. The cost for the three scenarios is found by calculating the proportional cost for the reduced time as compared with the original time. The results of the average time and cost for all scenarios are given in Table 2. The total cost of road closures per year is estimated to be approximately NZ$3 million. The best-case scenario (Scenario 2) would generate a 5.53% reduction, while the worst-case scenario (Scenario 3) would generate a reduction of 1.70% (NZ$49,952). The analysis of road closures reveals that slip events cause the highest costs (NZ$181,849) for the current practice (business as usual). With the use of the data and information framework, the cost reduction could range between 5.89% and 2%. The annual cost of road closure due to flooding, snow, and accidents is also high, and a considerable reduction in the cost of these road closures may be achieved in Scenario 2. For small emergencies, the maximum cost of road closures is due to accidents. On the one hand, this may be because from the 113 road closures recorded for 1 year (from April 2004 to March 2005), 29 road closures are due to small accidents. On the other hand, it could be because all the road closures due to accidents do not have an initial warning, which means that the consultants and contractors may not be well prepared for the response, and the accidents mostly occur on roads with high traffic flow and thus cause delay to more users.
TABLE 2
End User Feedback and Pathway to Implementation The case study results were subsequently presented to end users. The research team has produced a prototype version that focuses on graphically representing how the framework would be deployed during an emergency. End user organizations (Transit NZ and its consultants and contractors) were encouraged to participate and contribute to refine and assimilate the research findings. Initially, a report oriented to end users was compiled to review and summarize the critical issues involved in implementing electronic dataand information-sharing frameworks. The report (16), which was written in a nonacademic style, highlighted challenges, barriers, and opportunities in the implementation of the information-sharing framework. Copies of the report have been distributed, and gradually feedback has been obtained from the end user organizations. Other initiatives were workshops and return visits to the Transit NZ regional offices. During these meetings, the research team presented the DGIS vision, which was expressed in a series of “cartoon” presentations that graphically showed how DGIS would be used in different emergency response scenarios. The presentations allowed the end users to visualize and comment on the research findings. The key issue in meeting this challenge was to adapt the research team’s reporting and presentation approach to reach end users and communicate in accordance with end users’ expectations and background.
CONCLUSION The challenges involved in coordinating an effective response to emergency events are compounded by the number and variety of organizations involved. The complexities emphasize the need to develop robust yet simple frameworks for sharing information and communicating decisions within and between organizations involved in response and recovery activities. Considerable opportunities lie in exploring new paradigms for emergency response with extensive telecommunications and geospatial technologies. However, greater focus is needed on defining data- and information-sharing requirements and how the characteristics of the organizations involved affect implementation. A major outcome of this research is that perceived barriers can be reduced if technology is used according to an organization’s needs
Case Study Scenarios and Their Respective Annual Costs Scenario Business as Usual
Percentage of time reduced for each phase p=1 p=2 p=3 p=4 p=5 p=6 p=7 p=8 Annual cost (NZ$) Reduction (NZ$) Reduction (%)
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2,933,331 0 0
1
2
3
0.0 0.0 2.5 2.5 12.5 12.5 2.5 2.5 2,839,672 93,659 3.19
0.0 0.0 5.0 5.0 15.0 15.0 5.0 5.0 2,770,989 162,342 5.53
0.0 0.0 1.0 1.0 10.0 10.0 1.0 1.0 2,883,379 49,952 1.7
28
rather than the other way around. This can be done by involving end users during all development stages of the electronic data- and information-sharing framework to produce a framework that complements the organizational structures and cultures and the interfaces between the organizations involved. This paper has shown the potential in adopting an informationsharing framework to improve emergency response. Because of its simplicity and conformance with current practices and procedures, it is likely that the framework could be applied to all the emergency types and emergency levels for response action by road organizations in New Zealand. Furthermore, the framework could be applied to other countries, taking into account the legal and institutional framework of their road organizations. Two main limitations can be identified in this research. First, the information-sharing framework and the DGIS software have not yet been implemented or applied. The second is the quality and availability of road closure information. This has affected the accuracy of the time and cost reductions after the implementation of the DGIS. Nevertheless, the limitations do not affect the validity of the findings, because an initial research effort has been made to demonstrate the potential of conceiving a customized tool for data and information sharing during emergency events. The main area of further research would be the development of the data and information prototype in DGIS and its implementation on a real road closure. The DGIS can be developed by using the principles of data sharing in GIS. The prototype could be implemented in an emergency situation and tested for its efficiency and applicability. In a recent study, Galarus (17) has developed and tested a proof-ofconcept system similar to DGIS in terms of integrated computing and data and information sharing.
Transportation Research Record 2022
2. 3. 4.
5.
6.
7.
8. 9.
10. 11. 12.
ACKNOWLEDGMENTS The Resilient Organizations Research Programme is funded by the Foundation for Research Science and Technology of New Zealand. The authors thank Peter Connors, Maurice Mildenhall, Daya Govender, and Brian Grey of Transit NZ, Mike Skelton of MWH Global, John Reynolds and John Tailby of Opus International, Dave Brunsdon and Gavin Treadgold of Kestrel Group, John Fisher of ECAN-Civil Defense, and all others who shared their knowledge of and experience with emergency procedures and events.
REFERENCES 1. Britton, N. Response Strategies Within an Integrated Disaster Risk Management Framework. Presented at 4th Annual International Institute for Applied Systems Analysis–Disaster Prevention Research Institute Meeting
13. 14. 15. 16.
17.
on Integrated Disaster Risk Management: Challenges of Implementation, Ravello, Italy, 2004. Risks and Realities: A Multidisciplinary Approach to the Vulnerability of Lifelines to Natural Hazards. Christchurch Engineering Lifelines Group, Center for Advanced Engineering, Christchurch, New Zealand, 1997. Birkin, M., G. P. Clarke, M. Clarke, and A. G. Wilson. Intelligent GIS: Location Decisions and Strategic Planning. Geoinformation International, Cambridge, United Kingdom, 1996. Kwan, M.-P., and J. Lee. Geovisualization of Human Activity Patterns Using 3D GIS: A Timegeographic Approach. In Spatially Integrated Social Science: Examples in Best Practice (M. Goodchild and D. Janelle, eds.), Oxford University Press, New York, 2003, pp. 48–66. Schwarz, B. K. Ambulance Dispatch: Topics Surrounding a Real-Time Application. Proc., GIS/LIS 1989, American Congress on Surveying and Mapping/American Society for Photogrammetry and Remote Sensing, 1989. Lanza, L., and F. Siccardi. The Role of GIS as a Tool for the Assessment of Flood Hazard at the Regional Scale. In Geographical Information Systems in Assessing Natural Hazards (A. Carrara and F. Guzzetti, eds.), Kluwer, Netherlands, 1995, pp. 199–217. Hazelton, N. W. J. Using GIS with Non-Point-Source and Distributed Models: The “Why” and “How” of an Information Opportunity. In AURISA 91, Australasian Urban and Regional Information Systems Association, Wellington, New Zealand, 1991, pp. 289–313. Zerger, A., and D. I. Smith. Impediments to Using GIS for Real Time Disaster Decision Support. Computers, Environment and Urban Systems, Vol. 27, 2003, pp. 123–141. Summary of a Workshop on Using Information Technology to Enhance Disaster Management. Committee on Using Information Technology to Enhance Disaster Management, National Research Council of the National Academies, Washington, D.C., 2005. books.nap.edu/catalog/ 11458.html. Britton, N., and G. Clark. From Response to Resilience: Emergency Management Reform in New Zealand. Natural Hazards Review, Vol. 1, No. 3, 2000, pp. 145–150. MWH Global. Lifelines Coordination and Recovery—Looking Back on the February 2004 Floods and Future Arrangements. Ministry of Civil Defense and Emergency Management, New Zealand, 2004. Transportation Asset Management in Australia, Canada, England, and New Zealand. FHWA-PL-05-019. U.S. Department of Transportation, Washington, D.C., 2005. State Highway Emergency Procedure and Contingency Plan, Region 11 and 12. Report 98/32. Transit New Zealand, 2001. Choo, C. Information Management for the Intelligent Organisation: The Art of Scanning the Environment, 3rd ed. Information Today, Medford, N.J., 2002. Integration Definition for Function Modelling. Draft Federal Information Processing Standards Publication 183. National Institute of Standards and Technology, Gaithersburg, Md., 1993. Dantas, A., E. Seville, and A. Nicholson. Information Sharing During Disaster: Can We Do Better? Report 2. Resilient Organizations Research Programme, University of Canterbury, Christchurch, New Zealand, 2006. www.resorgs.nz. Galarus, D. Redding Responder Project: Computing and Communication in the Middle of Nowhere. Presented at 86th Annual Meeting of the Transportation Research Board, Washington, D.C., 2007.
The Critical Transportation Infrastructure Protection Committee sponsored publication of this paper.
