Strong, PA
Strong wildfire risk explained
Strong sits at the 56th 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 52 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Strong's burn probability — fire likelihood with no building count factored in — sits at the 54th percentile nationally.
Strong's building exposure, zone by zone
Most of Strong's buildings (90.4%) sit in the Indirect zone, where wind-blown embers rather than flame front are the mechanism USFS is scoring — ember-resistant vents and non-combustible roofing are the interventions this pattern favors, more than defensible space alone.
Where Strong ranks
Compare Strong's two percentiles: 92nd within Pennsylvania, only 56th nationally — a gap of 36 points that marks it as unusually exposed for its own state. Among the 31,521 US communities USFS scores, Strong ranks 13,879 for wildfire risk (1 is highest) and 30,886 by building count (1 is largest). Within Pennsylvania alone, it ranks 161 of 1,991 places by risk. See the full county-by-county picture for Pennsylvania on its state page.
Shopping for coverage in Strong
Strong's elevated wildfire rating (56th 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.
What would actually reduce this score
With ember exposure the dominant pattern in Strong (90.4% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.
Where Strong's figures come from
Strong's 56th-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 Strong's dominant indirect exposure actually means, with real examples from across the dataset.