Sheatown, PA
Sheatown, PA's wildfire risk, in USFS's own numbers
USFS's Wildfire Risk to Communities model puts Sheatown at the 52nd national percentile for risk to structures, modestly above the national average for wildfire risk — a score built from 342 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Sheatown's burn probability — fire likelihood with no building count factored in — sits at the 52nd percentile nationally.
Sheatown's building exposure, zone by zone
Most of Sheatown's buildings (83.3%) 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.
How Sheatown compares
Within Pennsylvania, Sheatown ranks higher (86th percentile) than it does nationally (52nd) — one of the more fire-exposed places in a state that, overall, scores lower than that. Among the 31,521 US communities USFS scores, Sheatown ranks 15,171 for wildfire risk (1 is highest) and 20,531 by building count (1 is largest). Within Pennsylvania alone, it ranks 284 of 1,991 places by risk. See the full county-by-county picture for Pennsylvania on its state page.
Sheatown and the insurance market
At the 52nd national percentile, Sheatown rates elevated for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
Hardening a home in Sheatown
Because 83.3% of Sheatown'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 Sheatown's figures come from
Every one of the two percentiles behind Sheatown's 15,171-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Sheatown's dominant indirect exposure actually means, with real examples from across the dataset.