Lakota, IA
Lakota, IA's wildfire risk, in USFS's own numbers
Out of every US place USFS scores, Lakota lands at the 3rd percentile for wildfire risk to structures — among the lower wildfire-risk places nationally — a figure built from its 252 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Lakota at the 3rd percentile, close to its 3rd-percentile risk score.
Where Lakota's buildings actually sit
Only 16.7% of Lakota's 252 buildings carry Direct exposure and 0% carry Indirect; the remaining 83.3% are Minimal, which shifts the risk driving this page's score toward the surrounding landscape rather than any one structure.
Lakota against the rest of the country
Lakota's risk sits at a similar level relative to Iowa (6th percentile statewide) as it does nationally (3rd) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Lakota ranks 30,486 for wildfire risk (1 is highest) and 23,073 by building count (1 is largest). Within Iowa alone, it ranks 956 of 1,017 places by risk. See the full county-by-county picture for Iowa on its state page.
Shopping for coverage in Lakota
Lakota's low wildfire rating (3rd percentile) isn't the kind of score driving the carrier pullback making news in the highest-risk Western markets — but a standard homeowners quote is still worth comparing on its own terms.
Lowering exposure, not just insuring around it
Even with 83.3% of Lakota 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 Lakota's figures come from
Every one of the two percentiles behind Lakota's 30,486-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Lakota's dominant minimal exposure actually means, with real examples from across the dataset.