South Williamsport, PA
How exposed is South Williamsport to wildfire?
South Williamsport's 2,947 buildings earn a 49th-percentile wildfire-risk score nationally under USFS's model — modestly above the national average for wildfire risk. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, South Williamsport's burn probability — fire likelihood with no building count factored in — sits at the 47th percentile nationally.
What "at risk" means for the buildings here
Indirect exposure is dominant in South Williamsport (89.8% of 2,947 buildings): far enough from burnable vegetation to avoid flame contact, close enough for wind-blown embers. Only 10.3% sit in the Direct zone.
How South Williamsport compares
Compare South Williamsport's two percentiles: 80th within Pennsylvania, only 49th nationally — a gap of 31 points that marks it as unusually exposed for its own state. Among the 31,521 US communities USFS scores, South Williamsport ranks 16,088 for wildfire risk (1 is highest) and 5,518 by building count (1 is largest). Within Pennsylvania alone, it ranks 401 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
South Williamsport's elevated rating (49th percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.
What would actually reduce this score
South Williamsport's 89.8% Indirect-exposure share points at embers, not flame contact, as the main pathway — ember-resistant vents and non-combustible roofing rank ahead of defensible space here. Detail in the home-hardening guide.
Where South Williamsport's figures come from
Every one of the two percentiles behind South Williamsport's 16,088-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what South Williamsport's dominant indirect exposure actually means, with real examples from across the dataset.