IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v258y2017i3p1095-1105.html
   My bibliography  Save this article

A maximal covering location-based model for analyzing the vulnerability of landscapes to wildfires: Assessing the worst-case scenario

Author

Listed:
  • Rashidi, Eghbal
  • Medal, Hugh
  • Gordon, Jason
  • Grala, Robert
  • Varner, Morgan

Abstract

In this research, we study the vulnerability of landscapes to wildfires based on the impact of the worst-case scenario ignition locations. Using this scenario, we model wildfires that cause the largest damage to a landscape over a given time horizon. The landscape is modeled as a grid network, and the spread of wildfire is modeled using the minimum travel time model. To assess the impact of a wildfire in the worst-case scenario, we develop a mathematical programming model to optimally locate the ignition points so that the resulting wildfire results in the maximum damage. We compare the impacts of the worst-case wildfires (with optimally located ignition points) with the impacts of wildfires with randomly located ignition points on three landscape test cases clipped out from three national forests located in the western U.S. Our results indicate that the worst-case wildfires, on average, have more than twice the impact on landscapes than wildfires with randomly located ignition points.

Suggested Citation

  • Rashidi, Eghbal & Medal, Hugh & Gordon, Jason & Grala, Robert & Varner, Morgan, 2017. "A maximal covering location-based model for analyzing the vulnerability of landscapes to wildfires: Assessing the worst-case scenario," European Journal of Operational Research, Elsevier, vol. 258(3), pages 1095-1105.
    • Handle: RePEc:eee:ejores:v:258:y:2017:i:3:p:1095-1105
    DOI: 10.1016/j.ejor.2016.08.074
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221716307135
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ejor.2016.08.074?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kim, Young-Hwan & Bettinger, Pete & Finney, Mark, 2009. "Spatial optimization of the pattern of fuel management activities and subsequent effects on simulated wildfires," European Journal of Operational Research, Elsevier, vol. 197(1), pages 253-265, August.
    2. Minas, James P. & Hearne, John W. & Martell, David L., 2014. "A spatial optimisation model for multi-period landscape level fuel management to mitigate wildfire impacts," European Journal of Operational Research, Elsevier, vol. 232(2), pages 412-422.
    3. Dimopoulou, Maria & Giannikos, Ioannis, 2004. "Towards an integrated framework for forest fire control," European Journal of Operational Research, Elsevier, vol. 152(2), pages 476-486, January.
    4. Bettinger, Pete & Boston, Kevin & Kim, Young-Hwan & Zhu, Jianping, 2007. "Landscape-level optimization using tabu search and stand density-related forest management prescriptions," European Journal of Operational Research, Elsevier, vol. 176(2), pages 1265-1282, January.
    5. Masashi Konoshima & Claire A. Montgomery & Heidi J. Albers & Jeffrey L. Arthur, 2008. "Spatial-Endogenous Fire Risk and Efficient Fuel Management and Timber Harvest," Land Economics, University of Wisconsin Press, vol. 84(3), pages 449-468.
    6. David L. Martell, 2007. "Forest Fire Management," International Series in Operations Research & Management Science, in: Andres Weintraub & Carlos Romero & Trond Bjørndal & Rafael Epstein & Jaime Miranda (ed.), Handbook Of Operations Research In Natural Resources, chapter 0, pages 489-509, Springer.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Qin Liu & Tiange Shi, 2019. "Spatiotemporal Differentiation and the Factors of Ecological Vulnerability in the Toutun River Basin Based on Remote Sensing Data," Sustainability, MDPI, vol. 11(15), pages 1-19, August.
    2. Eghbal Rashidi & Hugh Medal & Aaron Hoskins, 2018. "An attacker‐defender model for analyzing the vulnerability of initial attack in wildfire suppression," Naval Research Logistics (NRL), John Wiley & Sons, vol. 65(2), pages 120-134, March.
    3. Bhuiyan, Tanveer Hossain & Moseley, Maxwell C. & Medal, Hugh R. & Rashidi, Eghbal & Grala, Robert K., 2019. "A stochastic programming model with endogenous uncertainty for incentivizing fuel reduction treatment under uncertain landowner behavior," European Journal of Operational Research, Elsevier, vol. 277(2), pages 699-718.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. James Minas & John Hearne & David Martell, 2015. "An integrated optimization model for fuel management and fire suppression preparedness planning," Annals of Operations Research, Springer, vol. 232(1), pages 201-215, September.
    2. Araya-Córdova, P.J. & Vásquez, Óscar C., 2018. "The disaster emergency unit scheduling problem to control wildfires," International Journal of Production Economics, Elsevier, vol. 200(C), pages 311-317.
    3. Khakzad, Nima, 2021. "Optimal firefighting to prevent domino effects: Methodologies based on dynamic influence diagram and mathematical programming," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    4. Minas, James P. & Hearne, John W. & Martell, David L., 2014. "A spatial optimisation model for multi-period landscape level fuel management to mitigate wildfire impacts," European Journal of Operational Research, Elsevier, vol. 232(2), pages 412-422.
    5. Mikael Rönnqvist & Sophie D’Amours & Andres Weintraub & Alejandro Jofre & Eldon Gunn & Robert Haight & David Martell & Alan Murray & Carlos Romero, 2015. "Operations Research challenges in forestry: 33 open problems," Annals of Operations Research, Springer, vol. 232(1), pages 11-40, September.
    6. Calkin, David C. & Finney, Mark A. & Ager, Alan A. & Thompson, Matthew P. & Gebert, Krista M., 2011. "Progress towards and barriers to implementation of a risk framework for US federal wildland fire policy and decision making," Forest Policy and Economics, Elsevier, vol. 13(5), pages 378-389, June.
    7. Bhuiyan, Tanveer Hossain & Moseley, Maxwell C. & Medal, Hugh R. & Rashidi, Eghbal & Grala, Robert K., 2019. "A stochastic programming model with endogenous uncertainty for incentivizing fuel reduction treatment under uncertain landowner behavior," European Journal of Operational Research, Elsevier, vol. 277(2), pages 699-718.
    8. Moriguchi, Kai & Ueki, Tatsuhito & Saito, Masashi, 2020. "Establishing optimal forest harvesting regulation with continuous approximation," Operations Research Perspectives, Elsevier, vol. 7(C).
    9. Miren Bilbao & Sergio Gil-López & Javier Ser & Sancho Salcedo-Sanz & Mikel Sánchez-Ponte & Antonio Arana-Castro, 2014. "Novel hybrid heuristics for an extension of the dynamic relay deployment problem over disaster areas," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(3), pages 997-1016, October.
    10. Warziniack, Travis & Sims, Charles & Haas, Jessica, 2019. "Fire and the joint production of ecosystem services: A spatial-dynamic optimization approach," Forest Policy and Economics, Elsevier, vol. 107(C), pages 1-1.
    11. Yi Xiong & W. John Braun & X. Joan Hu, 2021. "Estimating duration distribution aided by auxiliary longitudinal measures in presence of missing time origin," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 27(3), pages 388-412, July.
    12. Kim Meyer Hall & Heidi J. Albers & Majid Alkaee Taleghan & Thomas G. Dietterich, 2018. "Optimal Spatial-Dynamic Management of Stochastic Species Invasions," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 70(2), pages 403-427, June.
    13. André Vizinho & David Avelar & Cristina Branquinho & Tiago Capela Lourenço & Silvia Carvalho & Alice Nunes & Leonor Sucena-Paiva & Hugo Oliveira & Ana Lúcia Fonseca & Filipe Duarte Santos & Maria José, 2021. "Framework for Climate Change Adaptation of Agriculture and Forestry in Mediterranean Climate Regions," Land, MDPI, vol. 10(2), pages 1-33, February.
    14. Mendes, André Bergsten & e Alvelos, Filipe Pereira, 2023. "Iterated local search for the placement of wildland fire suppression resources," European Journal of Operational Research, Elsevier, vol. 304(3), pages 887-900.
    15. Stavros Sakellariou & Stergios Tampekis & Fani Samara & Olga Christopoulou, 2015. "The added value of modern Decision Support Systems (DSS) against forest fires in a global scale," ERSA conference papers ersa15p1246, European Regional Science Association.
    16. Kıbış, Eyyüb Y. & Büyüktahtakın, İ. Esra, 2017. "Optimizing invasive species management: A mixed-integer linear programming approach," European Journal of Operational Research, Elsevier, vol. 259(1), pages 308-321.
    17. Christopher Costello & Nicolas Querou & Agnès Tomini, 2014. "Spatial concessions with limited tenure," Post-Print hal-01123392, HAL.
    18. Adán Rodríguez-Martínez & Begoña Vitoriano, 2020. "Probability-Based Wildfire Risk Measure for Decision-Making," Mathematics, MDPI, vol. 8(4), pages 1-18, April.
    19. Marion Rauner & Michaela Schaffhauser-Linzatti & Helmut Niessner, 2012. "Resource planning for ambulance services in mass casualty incidents: a DES-based policy model," Health Care Management Science, Springer, vol. 15(3), pages 254-269, September.
    20. Belavenutti, Pedro & Ager, Alan A. & Day, Michelle A. & Chung, Woodam, 2022. "Designing forest restoration projects to optimize the application of broadcast burning," Ecological Economics, Elsevier, vol. 201(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:258:y:2017:i:3:p:1095-1105. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.