Orangeville, PA
Orangeville wildfire risk explained
Out of every US place USFS scores, Orangeville lands at the 45th percentile for wildfire risk to structures — modestly above the national average for wildfire risk — a figure built from its 224 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Orangeville at the 45th percentile, close to its 45th-percentile risk score.
Where Orangeville's buildings actually sit
224 buildings are counted in Orangeville, and 63.8% of them are Indirect exposure — ember-driven risk rather than the 36.2% in Direct exposure or the 0% rated Minimal.
Orangeville against the rest of the country
Within Pennsylvania, Orangeville ranks higher (72nd percentile) than it does nationally (45th) — one of the more fire-exposed places in a state that, overall, scores lower than that. Among the 31,521 US communities USFS scores, Orangeville ranks 17,378 for wildfire risk (1 is highest) and 23,996 by building count (1 is largest). Within Pennsylvania alone, it ranks 554 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
Orangeville's elevated wildfire rating (45th 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
Because 63.8% of Orangeville's buildings sit in the Indirect zone, sealing the ember pathway (vents, roofing, gutters) is the intervention this page's data actually supports — see the home-hardening guide.
Where Orangeville's figures come from
Orangeville's 45th-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 Orangeville's dominant indirect exposure actually means, with real examples from across the dataset.