Queens Gate, PA
Queens Gate, PA's wildfire risk, in USFS's own numbers
USFS scores Queens Gate at the 5th national percentile for wildfire risk to structures (among the lower wildfire-risk places nationally), a figure built from 291 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Queens Gate at the 5th percentile, close to its 5th-percentile risk score.
Queens Gate's building exposure, zone by zone
Most of Queens Gate's buildings (68.4% of 291) fall outside USFS's Direct and Indirect zones entirely — that doesn't zero out the score above, it means the risk is regional, not structure-by-structure.
Queens Gate against the rest of the country
Queens Gate's risk sits at a similar level relative to Pennsylvania (2nd percentile statewide) as it does nationally (5th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Queens Gate ranks 30,055 for wildfire risk (1 is highest) and 21,895 by building count (1 is largest). Within Pennsylvania alone, it ranks 1,950 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
Queens Gate's low wildfire rating (5th 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 Queens Gate
With 68.4% of buildings rated Minimal exposure, Queens Gate gets less benefit from structure hardening than a Direct- or Indirect-dominant place would — the home-hardening guide explains why the zone matters.
Where Queens Gate's figures come from
Queens Gate's 5th-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 Queens Gate's dominant minimal exposure actually means, with real examples from across the dataset.