IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0071708.html
   My bibliography  Save this article

Land Use Planning and Wildfire: Development Policies Influence Future Probability of Housing Loss

Author

Listed:
  • Alexandra D Syphard
  • Avi Bar Massada
  • Van Butsic
  • Jon E Keeley

Abstract

Increasing numbers of homes are being destroyed by wildfire in the wildland-urban interface. With projections of climate change and housing growth potentially exacerbating the threat of wildfire to homes and property, effective fire-risk reduction alternatives are needed as part of a comprehensive fire management plan. Land use planning represents a shift in traditional thinking from trying to eliminate wildfires, or even increasing resilience to them, toward avoiding exposure to them through the informed placement of new residential structures. For land use planning to be effective, it needs to be based on solid understanding of where and how to locate and arrange new homes. We simulated three scenarios of future residential development and projected landscape-level wildfire risk to residential structures in a rapidly urbanizing, fire-prone region in southern California. We based all future development on an econometric subdivision model, but we varied the emphasis of subdivision decision-making based on three broad and common growth types: infill, expansion, and leapfrog. Simulation results showed that decision-making based on these growth types, when applied locally for subdivision of individual parcels, produced substantial landscape-level differences in pattern, location, and extent of development. These differences in development, in turn, affected the area and proportion of structures at risk from burning in wildfires. Scenarios with lower housing density and larger numbers of small, isolated clusters of development, i.e., resulting from leapfrog development, were generally predicted to have the highest predicted fire risk to the largest proportion of structures in the study area, and infill development was predicted to have the lowest risk. These results suggest that land use planning should be considered an important component to fire risk management and that consistently applied policies based on residential pattern may provide substantial benefits for future risk reduction.

Suggested Citation

  • Alexandra D Syphard & Avi Bar Massada & Van Butsic & Jon E Keeley, 2013. "Land Use Planning and Wildfire: Development Policies Influence Future Probability of Housing Loss," PLOS ONE, Public Library of Science, vol. 8(8), pages 1-12, August.
  • Handle: RePEc:plo:pone00:0071708
    DOI: 10.1371/journal.pone.0071708
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0071708
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0071708&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0071708?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
    ---><---

    References listed on IDEAS

    as
    1. Freeman, Elizabeth A. & Moisen, Gretchen G., 2008. "A comparison of the performance of threshold criteria for binary classification in terms of predicted prevalence and kappa," Ecological Modelling, Elsevier, vol. 217(1), pages 48-58.
    2. Karen A. Danielsen & Robert E. Lang & William Fulton, 1999. "Retracting suburbia: Smart growth and the future of housing," Housing Policy Debate, Taylor & Francis Journals, vol. 10(3), pages 513-540, January.
    3. Carmen Carrión-Flores & Elena G. Irwin, 2004. "Determinants of Residential Land-Use Conversion and Sprawl at the Rural-Urban Fringe," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(4), pages 889-904.
    4. Uddhab Bhandary & Brian Muller, 2009. "Land use planning and wildfire risk mitigation: an analysis of wildfire-burned subdivisions using high-resolution remote sensing imagery and GIS data," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 52(7), pages 939-955.
    5. Van Butsic & David J. Lewis & Lindsay Ludwig, 2011. "An Econometric Analysis of Land Development with Endogenous Zoning," Land Economics, University of Wisconsin Press, vol. 87(3), pages 412-432.
    6. Elena G. Irwin, 2010. "New Directions For Urban Economic Models Of Land Use Change: Incorporating Spatial Dynamics And Heterogeneity," Journal of Regional Science, Wiley Blackwell, vol. 50(1), pages 65-91, February.
    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. Depietri, Yaella & Orenstein, Daniel E., 2020. "Managing fire risk at the wildland-urban interface requires reconciliation of tradeoffs between regulating and cultural ecosystem services," Ecosystem Services, Elsevier, vol. 44(C).
    2. Laura Serra & Claudio Detotto & Marco Vannini, 2022. "Public lands as a mitigator of wildfire burned area using a spatio-temporal model applied in Sardinia," Letters in Spatial and Resource Sciences, Springer, vol. 15(3), pages 621-635, December.
    3. Stephen M. Strader, 2018. "Spatiotemporal changes in conterminous US wildfire exposure from 1940 to 2010," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 92(1), pages 543-565, May.
    4. Sonia Akter & R. Quentin Grafton, 2021. "Do fires discriminate? Socio-economic disadvantage, wildfire hazard exposure and the Australian 2019–20 ‘Black Summer’ fires," Climatic Change, Springer, vol. 165(3), pages 1-21, April.
    5. Paveglio, Travis B. & Stasiewicz, Amanda M. & Edgeley, Catrin M., 2021. "Understanding support for regulatory approaches to wildfire management and performance of property mitigations on private lands," Land Use Policy, Elsevier, vol. 100(C).
    6. Susan D. Kocher & Van Butsic, 2017. "Governance of Land Use Planning to Reduce Fire Risk to Homes Mediterranean France and California," Land, MDPI, vol. 6(2), pages 1-18, March.
    7. Galiana-Martín Luis, 2017. "Spatial Planning Experiences for Vulnerability Reduction in the Wildland-Urban Interface in Mediterranean European Countries," European Countryside, Sciendo, vol. 9(3), pages 577-593, September.
    8. Van Butsic & Maggi Kelly & Max A. Moritz, 2015. "Land Use and Wildfire: A Review of Local Interactions and Teleconnections," Land, MDPI, vol. 4(1), pages 1-17, February.
    9. Edgeley, Catrin M. & Paveglio, Travis B. & Williams, Daniel R., 2020. "Support for regulatory and voluntary approaches to wildfire adaptation among unincorporated wildland-urban interface communities," Land Use Policy, Elsevier, vol. 91(C).

    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. Kane, Kevin & York, Abigail M., 2017. "Prices, policies, and place: What drives greenfield development?," Land Use Policy, Elsevier, vol. 68(C), pages 415-428.
    2. Carmen Carrión-Flores & Elena G. Irwin, 2017. "A fixed effects logit model of rural land conversion and zoning," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 58(1), pages 181-208, January.
    3. Van Butsic & David J. Lewis & Lindsay Ludwig, 2011. "An Econometric Analysis of Land Development with Endogenous Zoning," Land Economics, University of Wisconsin Press, vol. 87(3), pages 412-432.
    4. Kaza, Nikhil & Towe, Charles & Ye, Xin, 2011. "A Hybrid Land Conversion Model Incorporating Multiple End Uses," Agricultural and Resource Economics Review, Cambridge University Press, vol. 40(3), pages 341-359, December.
    5. Sandler, Austin M. & Rashford, Benjamin S., 2018. "Misclassification error in satellite imagery data: Implications for empirical land-use models," Land Use Policy, Elsevier, vol. 75(C), pages 530-537.
    6. Kathleen Segerson & Catherine L. Kling & Nancy E. Bockstael, 2022. "Contributions of women at the intersection of agricultural economics and environmental and natural resource economics," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 44(1), pages 38-53, March.
    7. Wrenn, Douglas H. & Sam, Abdoul G., 2014. "Geographically and temporally weighted likelihood regression: Exploring the spatiotemporal determinants of land use change," Regional Science and Urban Economics, Elsevier, vol. 44(C), pages 60-74.
    8. Cho, Seong-Hoon & Kim, Heeho & Roberts, Roland K. & Kim, Taeyoung & Lee, Daegoon, 2014. "Effects of changes in forestland ownership on deforestation and urbanization and the resulting effects on greenhouse gas emissions," Journal of Forest Economics, Elsevier, vol. 20(1), pages 93-109.
    9. Lin, Huiyan & Lu, Kang Shou & Espey, Molly & Allen, Jeffery, 2005. "Modeling Urban Sprawl and Land Use Change in a Coastal Area-- A Neural Network Approach," 2005 Annual meeting, July 24-27, Providence, RI 19364, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    10. Václavík, Tomáš & Meentemeyer, Ross K., 2009. "Invasive species distribution modeling (iSDM): Are absence data and dispersal constraints needed to predict actual distributions?," Ecological Modelling, Elsevier, vol. 220(23), pages 3248-3258.
    11. Changchun Feng & Hao Zhang & Liang Xiao & Yongpei Guo, 2022. "Land Use Change and Its Driving Factors in the Rural–Urban Fringe of Beijing: A Production–Living–Ecological Perspective," Land, MDPI, vol. 11(2), pages 1-18, February.
    12. Chunhong Zhao & Jennifer L.R. Jensen & Russell Weaver, 2020. "Global and Local Modeling of Land Use Change in the Border Cities of Laredo, Texas, USA and Nuevo Laredo, Tamaulipas, Mexico: A Comparative Analysis," Land, MDPI, vol. 9(10), pages 1-18, September.
    13. Carrión-Flores, Carmen E. & Flores-Lagunes, Alfonso & Guci, Ledia, 2018. "An estimator for discrete-choice models with spatial lag dependence using large samples, with an application to land-use conversions," Regional Science and Urban Economics, Elsevier, vol. 69(C), pages 77-93.
    14. Dominique Prunetti & Alexandre Muzy & Eric Innocenti & Xavier Pieri, 2014. "Utility-based Multi-agent System with Spatial Interactions: The Case of Virtual Estate Development," Computational Economics, Springer;Society for Computational Economics, vol. 43(3), pages 271-299, March.
    15. Qingxu Huang & Dawn C Parker & Tatiana Filatova & Shipeng Sun, 2014. "A Review of Urban Residential Choice Models Using Agent-Based Modeling," Environment and Planning B, , vol. 41(4), pages 661-689, August.
    16. Barry Kew & Brian D. Lee, 2013. "Measuring Sprawl across the Urban Rural Continuum Using an Amalgamated Sprawl Index," Sustainability, MDPI, vol. 5(5), pages 1-23, April.
    17. Thériault, Marius & Le Berre, Iwan & Dubé, Jean & Maulpoix, Adeline & Vandersmissen, Marie-Hélène, 2020. "The effects of land use planning on housing spread: A case study in the region of Brest, France," Land Use Policy, Elsevier, vol. 92(C).
    18. Thomas de Graaff & Frank G. van Oort & Raymond J.G.M. Florax, 2012. "Regional Population–Employment Dynamics Across Different Sectors Of The Economy," Journal of Regional Science, Wiley Blackwell, vol. 52(1), pages 60-84, February.
    19. Suzanne Vallance, 2014. "Living on the Edge: Lessons from the Peri-urban Village," International Journal of Urban and Regional Research, Wiley Blackwell, vol. 38(6), pages 1954-1969, November.
    20. Andrew McMillan & Sugie Lee, 2017. "Smart growth characteristics and the spatial pattern of multifamily housing in US metropolitan areas," Urban Studies, Urban Studies Journal Limited, vol. 54(15), pages 3500-3523, November.

    More about this item

    Statistics

    Access and download statistics

    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:plo:pone00:0071708. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.