Patterson, IA
Patterson wildfire risk explained
USFS scores Patterson at the 63rd national percentile for wildfire risk to structures (well above the national norm for wildfire risk), a figure built from 137 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Patterson at the 64th national percentile — 1 points above its risk-to-structures score, a gap driven by how much is actually built there.
Where Patterson's buildings actually sit
71.5% of Patterson's 137 buildings fall in USFS's Indirect exposure zone — ember cast rather than direct flame — against 28.5% Direct and 0% Minimal. Vent screens and roofing material matter more here than lot clearing alone.
How Patterson compares
Compare Patterson's two percentiles: 87th within Iowa, only 63rd nationally — a gap of 23 points that marks it as unusually exposed for its own state. Among the 31,521 US communities USFS scores, Patterson ranks 11,564 for wildfire risk (1 is highest) and 27,397 by building count (1 is largest). Within Iowa alone, it ranks 137 of 1,017 places by risk. See the full county-by-county picture for Iowa on its state page.
Shopping for coverage in Patterson
At the 63rd percentile nationally, Patterson carries the high rating that has pushed some carriers to limit new business in similarly-scored places elsewhere in the country. Worth comparing quotes rather than assuming last year's renewal terms still apply.
Hardening a home in Patterson
Patterson's 71.5% Indirect-exposure share points at embers, not flame contact, as the main pathway — ember-resistant vents and non-combustible roofing rank ahead of defensible space here. Detail in the home-hardening guide.
Where Patterson's figures come from
Patterson's 63rd-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 Patterson's dominant indirect exposure actually means, with real examples from across the dataset.