Dorneyville, PA
Dorneyville, PA's wildfire risk, in USFS's own numbers
USFS scores Dorneyville at the 18th national percentile for wildfire risk to structures (among the lower wildfire-risk places nationally), a figure built from 2,292 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Dorneyville at the 20th national percentile — 2 points above its risk-to-structures score, a gap driven by how much is actually built there.
Dorneyville's building exposure, zone by zone
76.4% of Dorneyville's 2,292 buildings sit in USFS's Minimal exposure zone, with only 23.6% rated Direct — risk here comes from regional burn probability more than proximity to burnable vegetation at the structure itself.
Where Dorneyville ranks
There's little gap between Dorneyville's 18th national percentile and its 19th percentile inside Pennsylvania, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Dorneyville ranks 25,886 for wildfire risk (1 is highest) and 6,717 by building count (1 is largest). Within Pennsylvania alone, it ranks 1,616 of 1,991 places by risk. See the full county-by-county picture for Pennsylvania on its state page.
Dorneyville and the insurance market
Dorneyville's low rating (18th 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 Dorneyville
Dorneyville's 76.4% Minimal-exposure share means structure-level hardening matters less here than it would elsewhere — still worth the low-cost basics, per the home-hardening guide.
Where Dorneyville's figures come from
Every one of the two percentiles behind Dorneyville's 25,886-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Dorneyville's dominant minimal exposure actually means, with real examples from across the dataset.