Abstract
Context: Wildfires destroy thousands of buildings every year in the wildland urban interface. However, fire typically only destroys a fraction of the buildings within a given fire perimeter, suggesting more could be done to mitigate risk if we understood how to configure residential landscapes so that both people and buildings could survive fire. Objectives: Our goal was to understand the relative importance of vegetation, topography and spatial arrangement of buildings on building loss, within the fire’s landscape context. Methods: We analyzed two fires: one in San Diego, CA and another in Boulder, CO. We analyzed Google Earth historical imagery to digitize buildings exposed to the fires, a geographic information system to measure some of the explanatory variables, and FRAGSTATS to quantify landscape metrics. Using logistic regression we conducted an exhaustive model search to select the best models. Results: The type of variables that were important varied across communities. We found complex spatial effects and no single model explained building loss everywhere, but topography and the spatial arrangement of buildings explained most of the variability in building losses. Vegetation connectivity was more important than vegetation type. Conclusions: Location and spatial arrangement of buildings affect which buildings burn in a wildfire, which is important for urban planning, building siting, landscape design of future development, and to target fire prevention, fuel reduction, and homeowner education efforts in existing communities. Landscape context of buildings and communities is an important aspect of building loss, and if taken into consideration, could help communities adapt to fire.
Original language | English |
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Pages (from-to) | 415-430 |
Number of pages | 16 |
Journal | Landscape Ecology |
Volume | 31 |
Issue number | 2 |
DOIs | |
State | Published - 1 Feb 2016 |
Bibliographical note
Funding Information:This work was supported by a research joint venture agreement with the Rocky Mountain Research Station and Northern Research Station of the USDA Forest Service, and by a Fulbright Exchange program fellowship awarded to Patricia Alexandre, and by a Ph.D. fellowship provided by the Foundation for Science and Technology to Patricia Alexandre in 2014 (FCT—Portugal—reference: SFRH/BD/92960/2013, financed by POPH—QREN—Tipology 4.1—Advanced formation funded by the European Social fund and by the MEC National Fund). Fulbright and FCT had no involvement in the study design, collection, analysis, and interpretation of the results or in the decision to publish. Forest Service scientists were involved in the study design, interpretation of the results and decision to publish. LANDFIRE data were provided by the U.S. Geological Survey Earth Resources Observation Systems (EROS) Data Center. We thank J. Jenness for his help with the Topographic Position Index tool extension for ArcGis, D. Helmers and M. Beighley for their advice, J. Orestes and T. Henriques for support with glmulti R package, and C. Frederick and S. Roberts for help with data collection. Three anonymous reviewers provided valuable feedback, which greatly improved our manuscript, and we thank them for their suggestions.
Publisher Copyright:
© 2015, Springer Science+Business Media Dordrecht.
Keywords
- Best-subsets
- Building loss
- FRAGSTATS
- Logistic regression
- WUI
- Wildfires
ASJC Scopus subject areas
- Geography, Planning and Development
- Ecology
- Nature and Landscape Conservation