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

Overview of attention for article published in PLOS ONE, August 2013
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

Mentioned by

news
16 news outlets
blogs
1 blog
policy
1 policy source
twitter
10 tweeters
facebook
1 Facebook page

Citations

dimensions_citation
76 Dimensions

Readers on

mendeley
174 Mendeley
citeulike
1 CiteULike
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Title
Land Use Planning and Wildfire: Development Policies Influence Future Probability of Housing Loss
Published in
PLOS ONE, August 2013
DOI 10.1371/journal.pone.0071708
Pubmed ID
Authors

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.

Twitter Demographics

The data shown below were collected from the profiles of 10 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 174 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 1%
Indonesia 1 <1%
Malaysia 1 <1%
South Africa 1 <1%
Australia 1 <1%
Unknown 168 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 34 20%
Researcher 34 20%
Student > Master 25 14%
Student > Bachelor 15 9%
Student > Doctoral Student 9 5%
Other 29 17%
Unknown 28 16%
Readers by discipline Count As %
Environmental Science 47 27%
Social Sciences 24 14%
Agricultural and Biological Sciences 14 8%
Engineering 12 7%
Earth and Planetary Sciences 9 5%
Other 31 18%
Unknown 37 21%

Attention Score in Context

This research output has an Altmetric Attention Score of 153. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 04 January 2020.
All research outputs
#196,212
of 21,347,688 outputs
Outputs from PLOS ONE
#3,039
of 182,534 outputs
Outputs of similar age
#1,438
of 175,997 outputs
Outputs of similar age from PLOS ONE
#75
of 3,843 outputs
Altmetric has tracked 21,347,688 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 182,534 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.5. This one has done particularly well, scoring higher than 98% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 175,997 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 3,843 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 98% of its contemporaries.