Farwell, PA
Farwell, PA's wildfire risk, in USFS's own numbers
Farwell sits at the 59th percentile nationally for wildfire risk to structures — modestly above the national average for wildfire risk — per USFS's Wildfire Risk to Communities model, built from its 197 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Farwell's burn probability — fire likelihood with no building count factored in — sits at the 57th percentile nationally.
Where Farwell's buildings actually sit
Direct exposure dominates in Farwell: 51.3% of its 197 buildings, versus 48.7% Indirect and 0% Minimal. Clearing space around a structure changes the outcome here more than any single building-material swap.
Where Farwell ranks
Compare Farwell's two percentiles: 96th within Pennsylvania, only 59th nationally — a gap of 36 points that marks it as unusually exposed for its own state. Among the 31,521 US communities USFS scores, Farwell ranks 12,835 for wildfire risk (1 is highest) and 24,972 by building count (1 is largest). Within Pennsylvania alone, it ranks 87 of 1,991 places by risk. See the full county-by-county picture for Pennsylvania on its state page.
Farwell and the insurance market
Farwell's elevated wildfire rating (59th 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
With 51.3% of Farwell in Direct exposure, defensible-space clearing and ember-resistant construction (vents, Class-A roofing) address the exposure this page's own numbers describe, not a generic checklist. See the home-hardening guide.
Where Farwell's figures come from
Every one of the two percentiles behind Farwell's 12,835-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Farwell's dominant direct exposure actually means, with real examples from across the dataset.