Coulter, IA
How exposed is Coulter to wildfire?
Coulter sits at the 3rd percentile nationally for wildfire risk to structures — among the lower wildfire-risk places nationally — per USFS's Wildfire Risk to Communities model, built from its 179 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Coulter at the 2nd national percentile — 0 points below its risk-to-structures score, a gap driven by how much is actually built there.
Coulter's building exposure, zone by zone
84.9% of Coulter's 179 buildings sit in USFS's Minimal exposure zone, with only 15.1% rated Direct — risk here comes from regional burn probability more than proximity to burnable vegetation at the structure itself.
Where Coulter ranks
There's little gap between Coulter's 3rd national percentile and its 5th percentile inside Iowa, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Coulter ranks 30,666 for wildfire risk (1 is highest) and 25,670 by building count (1 is largest). Within Iowa alone, it ranks 969 of 1,017 places by risk. See the full county-by-county picture for Iowa on its state page.
Shopping for coverage in Coulter
Coulter's low rating (3rd percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.
Hardening a home in Coulter
Even with 84.9% of Coulter 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 Coulter's figures come from
Every one of the two percentiles behind Coulter's 30,666-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Coulter's dominant minimal exposure actually means, with real examples from across the dataset.