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equirements and a past lack of enforcement of state statutes has led to a lack of fire
occurrence data for both prescribed burns and wildfires being available. Changes in
enforcement of wildfire reporting requirements at the state level, as well as prescribed fire
reporting requirements that are part of the EPA-mandated Kansas Flint Hills Smoke
Management Plan (approved in 2011), will give the Kansas Forest Service a much greater
opportunity to begin using real-time fire occurrence data to assist in making the best fire
management decisions.
In light of the data limitations associated with available statistics, and with the publication of the
2011 Kansas Forest Action Plan, the planning committee determined that the best available
data for the vulnerability analysis for the Wildfire Hazard is the ‘Weighted Sum’ analysis that
was completed and utilized to develop a ‘Wildfire Risk’ composite layer as part of the Forest
Action Plan.
The ‘Wildfire Risk’ composite layer was developed using a ‘Weighted Sum’ analysis to combine
six data layers produced from a combination of eight separate datasets. In close consultation
with the Kansas Forest Service’s Fire Management Coordinator and other Fire Management
staff six data inputs were developed to represent Wildfire Risk in Kansas. These data inputs
and their corresponding analysis weight are listed below:
1) Wildland Urban Interface—from 3 data sets (.85)
2) ISO Fire Station Coverage Gaps (.75);
3) Conservation Reserve Program Lands (.60);
4) Eastern Redcedar in Grasslands (.75);
5) ‘Moderate’ Fire Potential risk and (.53);
6) ‘High’ Fire Potential risk (.80).
For more detailed descriptions of these six data layers, see pages 27-28 of the Kansas Forest
Action Plan, http://www.kansasforests.org/assessment.shtml. The six data layer inputs were
combined using the ‘Weighted sum’ analysis. The resulting raster contains values ranging from
0 to 3.48. The higher the numbers (darker shading) indicate higher wildfire risk. Figure 3.80 is
the resulting composite map. Figure 3.81 that follows provides a map indicating the mean score
for each county. Then Table 3.168 provides a table of the mean score for each county.
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