Coatesville, IN
Coatesville wildfire risk explained
USFS scores Coatesville at the 6th national percentile for wildfire risk to structures (among the lower wildfire-risk places nationally), a figure built from 368 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Coatesville's burn probability — fire likelihood with no building count factored in — sits at the 6th percentile nationally.
What "at risk" means for the buildings here
USFS classifies 71.5% of Coatesville's buildings as Minimal exposure, the largest of the three zones here by a wide margin over 28.5% Direct and 0% Indirect — a landscape-level risk rather than a building-by-building one.
Where Coatesville ranks
Within Indiana, Coatesville ranks higher (40th percentile) than it does nationally (6th) — one of the more fire-exposed places in a state that, overall, scores lower than that. Among the 31,521 US communities USFS scores, Coatesville ranks 29,714 for wildfire risk (1 is highest) and 19,901 by building count (1 is largest). Within Indiana alone, it ranks 581 of 967 places by risk. See the full county-by-county picture for Indiana on its state page.
What this risk score means for insurance
Coatesville's low rating (6th percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.
What would actually reduce this score
Even with 71.5% of Coatesville 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 Coatesville's figures come from
Every one of the two percentiles behind Coatesville's 29,714-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Coatesville's dominant minimal exposure actually means, with real examples from across the dataset.