Minneapolis, KS
Minneapolis wildfire risk explained
USFS's Wildfire Risk to Communities model puts Minneapolis at the 22nd national percentile for risk to structures, close to the middle of USFS's national wildfire-risk range — a score built from 1,300 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Minneapolis's burn probability — fire likelihood with no building count factored in — sits at the 19th percentile nationally.
Where Minneapolis's buildings actually sit
USFS classifies 94% of Minneapolis's buildings as Minimal exposure, the largest of the three zones here by a wide margin over 6% Direct and 0% Indirect — a landscape-level risk rather than a building-by-building one.
Minneapolis against the rest of the country
Inside Kansas, Minneapolis sits at just the 4th percentile even though it scores 22nd nationally — the state's overall wildfire exposure is high enough to make this a relatively quiet corner of it. Among the 31,521 US communities USFS scores, Minneapolis ranks 24,516 for wildfire risk (1 is highest) and 10,076 by building count (1 is largest). Within Kansas alone, it ranks 693 of 721 places by risk. See the full county-by-county picture for Kansas on its state page.
What this risk score means for insurance
At the 22nd national percentile, Minneapolis rates moderate for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
What would actually reduce this score
Even with 94% of Minneapolis outside USFS's Direct and Indirect zones, basic hardening — gutter maintenance, ember-resistant vents — is inexpensive relative to the regional burn-probability risk noted above. Details in the home-hardening guide.
Where Minneapolis's figures come from
Minneapolis's 22nd-percentile score and its burn-probability figure both come from the same USFS workbook, documented in the methodology guide. The exposure-zones guide covers what Minneapolis's dominant minimal exposure actually means, with real examples from across the dataset.