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JDR Vol.7 No.6 pp. 793-802
(2012)
doi: 10.20965/jdr.2012.p0793

Paper:

Emergency Management: Building an O-D Ranking Model Using GIS Network Analysis

Carine J. Yi*, Roy S. Park**, Osamu Murao***,
and Eiji Okamoto***

*Graduate School of Systems and Information Engineering, University of Tsukuba, 1-1-1 Tennodai, Tsukuba City, Ibaraki 305-8573, Japan

**R. Park and Associates Inc., 46 Woodward Ave. Markham, Ontario L3T 1E5, Canada

***Faculty of Engineering, Systems and Information, University of Tsukuba, 1-1-1 Tennodai, Tsukuba City, Ibaraki 305-8573, Japan

Received:
May 28, 2012
Accepted:
September 20, 2012
Published:
December 1, 2012
Keywords:
emergency management, optimal evacuation route finding, wildfire, O-D ranking model
Abstract
Enormous natural disasters due to climate change are frequently observed all around the world. Unexpected catastrophes become a huge threat for community residents. Activating an evacuation order in a large-scale incident such as a wildfire depends on how information can be acquired in real time. Geographic Information Systems (GIS) provide highly analyzed map products to decision makers. Under real wildfire circumstances, GIS map products are very effective materials that include collected and analyzed information and results visualized to enable interpretation of the situation in real time. The challenge of this study is the construction of an optimal route selection method using a GIS network for issuing evacuation-order decisions. The most effective evacuation routes were defined by networking analysis using 2007 San Diego wildfire datasets. The shortest evacuation routes were calculated between affected points and shelters and chosen automatically by an O-D (Origin - Destination) ranking model. Considerable roads and land features and other environmental factors when the closest facilities and routes are selected, selection criteria and approach methods can be suggested for future events. Using this model, accessible routes can be chosen any time and any place, even during an ongoing evacuation. Decision makers should therefore provide proper evacuation orders to rescue crews using this O-D ranking model.
Cite this article as:
C. Yi, R. Park, O. Murao, and E. Okamoto, “Emergency Management: Building an O-D Ranking Model Using GIS Network Analysis,” J. Disaster Res., Vol.7 No.6, pp. 793-802, 2012.
Data files:
References
  1. [1] Union of Concerned Scientist U.S.A. (UCSUSA), “Global Warming and California Wildfires” (A fact sheet of the Union of Concerned Scientists) www.ucsusa.org/clean_california [accessed Jan. 30, 2012].
  2. [2] A. L. Westerling, H. G. Hidalgo, D. R. Cayan, and T. W. Swetnam, “Warming and Earlier Spring Increase Western U.S. ForestWildfire Activity,” Science, Vol.313, pp. 940-943, 2006, DOI: 10.1126/science. 1128834.
  3. [3] Mathew Bettenhausen, “State of California Emergency Plan,” California Emergency Management Agency (CalEMA), 2009.
  4. [4] W. F. Ekard, H. Tuck, and R. Lane, “San Diego County Firestorms 2007 After Action Report,” Prepared by EG&G Technical Services, Inc., 2007.
  5. [5] M. K. Lindell, “EMBLEM2: An empirically based large scale evacuation time estimate model,” Transportation Research Part A: Policy and Practice, Vol.42, Issue 1, pp. 140-154, 2008.
  6. [6] Y. Sheffi, H. Mahmassani, and W. B. Powell, “A transportation network evacuation model,” Transportation Research Part A: General, Vol.16, Issue 3, pp. 209-218, 1982.
  7. [7] A. Stepanov and J. MacGregor Smith, “Multi-objective evacuation routing in transportation networks,” European Journal of Operational Research, Vol.198, pp. 435-446, 2009.
  8. [8] T. J. Cova, P. E. Dennison, T. H. Kim, and M. A. Moritz, “Setting Wildfire Evacuation Trigger Points Using Fire Spread Modeling and GIS,” Transactions in GIS, Vol.9, No.4, pp. 603.617, 2005.
  9. [9] P. E. Dennison, T. J. Cova, and M. A. Mortiz, “WUIVAC: a wildland-urban interface evacuation trigger model applied in strategic wildfire scenarios,” Natural Hazards, Vol.41, pp. 181-199, DOI 10.1007/s11069-006-9032-y, 2007.
  10. [10] M. Potůčková, S. Gril, and J. Lysák, “Evacuation GIS for the TANGO Project,” GIS meets Remote Sensing and Photogrammetry towards Digital World: Symposium GIS Ostrava 2010, 24-27 January, Ostrava, Czech Republic, 2010.
  11. [11] E. J. Baker, “Hurricane Evacuation Behavior,” International Journal of Mass Emergencies and Disasters, Vol.9, No.2, pp. 287-310, 1991.
  12. [12] Turan Erden and Mehmet Zeki Coskun (TR), “Interfacing Emergency Management with GIS-Aided Spatial Decision Support System,” 17th Interfacing Emergency Management with GIS-aided Spatial Decision Support Systems, International Symposium on Modern Technologies, Education and Professional Practice in Geodesy and Related Fields, 09-09 November, Sofia, Bulgaria, 2007.
  13. [13] D. W. Borchardt and D. D. Puckett, “Real-Time Data for Hurricane Evacuation in Texas,” Southwest Region University Transportation Center, Texas Transportation Institute, Report No. SWUTC/08/167764-1, Project 167764, Project Title: Data for Evacuation Transportation Information System in HURREVAC, 2008.
  14. [14] J. F. Goss, E. B. Ngo, and L. M. Simpson, “Getting ready to get out: how EMS providers & hospital staff can work together to successfully relocate patients,” Journal of Emergency Medical Sercices (JEMS), Vol.33, No.5, pp. 72-81, May, 2008.
  15. [15] R. Zane, P. Biddinger, A. Hassol, T. Rich, J. Gerber, and J. DeAngelis, “Hospital Evacuation Decision Guide,” Agency for Healthcare Research and Quality of U.S. Department of Health and Human Services, AHRQ Publication No.10-0009, 2010.
  16. [16] A. H. Kaji and R. J. Lewis, “Hospital Disaster Preparedness in Los Angeles County,” Academic Emergency Medicine, Vol.13, Issue 11, pp. 1198-1203, 2008.
  17. [17] K. S. Hoyt and A. E. Gerhart, “The San Diego County Wildfires: Perspectives of Healthcare,” Disaster Management & Response, Vol.2, 2004.
  18. [18] C. I. Schranz, E. M. Castillo, and G. M. Vilke, “The 2007 San DiegoWildfire impact on the Emergency Department of the University of California,” San Diego Hospital System, Prehospital Disaster Medicine, 2010 Sep-Oct, Vol.25, No.5, pp. 472-476, 2010.
  19. [19] A. Kay Childers and K. M. Taaffe, “Healthcare Facility Evacuations: Lessons Learned, Research Activity, and the Need for Engineering Contributions,” Journal of Healthcare Engineering, Vol.1, No.1, March 2010.
  20. [20] C. W. Johnson, “Using Computer Simulations to Support A Risk-Based Approach For Hospital Evacuation,” Glasgow Accident Analysis Group, University of Glasgow, 2006.
  21. [21] D. Golmohammadi and D. Shimshak, “Estimation of the evacuation time in an emergency situation in hospitals,” Computers & Industrial Engineering, Vol.61, Issue 4, pp. 1256-1267, 2011.
  22. [22] J. Augustine and J. T. Schoettmer, “Evacuation of a Rural Community Hospital: Lessons Learned From an Unplanned Event, Disaster Management & Response,” Vol.3, Issue 3, pp. 68-72, July-September 2005.
  23. [23] N. Squillace, “Hospital Evacuations: Historical Precedence and Modern Preparedness,” Master of Public Health Program, Wright State University Boonshoft School of Medicine, 2010.
  24. [24] M. M. Arms and J. D. Van Zante, “Wildfire Evacuation: Outrunning the Witch’s Curse-One Animal Center’s Experience,” ILAR Journal, Disaster Planning and Management, Vol.51 No.2, pp. 158-163, 2010.
  25. [25] W. J. Wooten, 2007 San Diego Wildfires: Lessons Learned, County of San Diego, Health and Human Services Agency, (Air Resources Board presentation material)
    http://www.arb.ca.gov/carpa/meetings/summit08/presentations/firestorm07_wwooten.pdf [accessed Aug. 2012]
  26. [26] Health Facilities Management (on-line magazine),
    http://www.hfmmagazine.com/hfmmagazine/jsp/articledisplay.jsp?dcrpath=HFMMAGAZINE/Article/data/12DEC2007/0712HFM_Upfront_Disaster&domain=HFMMAGAZINE [accessed Aug. 13, 2012]
  27. [27] D. E. Hogan and J. L. Burstein, “Disaster Medicine,” Second Edition, Lippincott Williams & Wilkins, pp. 209, ISBN- 13: 978-0-7817-6262-5, 2007.
  28. [28] County of San Diego-Department of Public Works, “Public Road Standards,” 2012.

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