Fullerton, PA
How exposed is Fullerton to wildfire?
Fullerton sits at the 12th 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 4,073 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Fullerton at the 12th national percentile — 0 points above its risk-to-structures score, a gap driven by how much is actually built there.
What "at risk" means for the buildings here
95% of Fullerton's 4,073 buildings sit in USFS's Minimal exposure zone, with only 5% rated Direct — risk here comes from regional burn probability more than proximity to burnable vegetation at the structure itself.
Fullerton against the rest of the country
Fullerton scores 12th nationally and 10th within Pennsylvania — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, Fullerton ranks 27,873 for wildfire risk (1 is highest) and 4,166 by building count (1 is largest). Within Pennsylvania alone, it ranks 1,790 of 1,991 places by risk. See the full county-by-county picture for Pennsylvania on its state page.
What this risk score means for insurance
Fullerton's low wildfire rating (12th 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.
Hardening a home in Fullerton
With 95% of buildings rated Minimal exposure, Fullerton gets less benefit from structure hardening than a Direct- or Indirect-dominant place would — the home-hardening guide explains why the zone matters.
Where Fullerton's figures come from
The methodology guide shows exactly how USFS turned 4,073 counted buildings into the percentiles shown above for Fullerton. The exposure-zones guide covers what Fullerton's dominant minimal exposure actually means, with real examples from across the dataset.