Quakertown, PA
How exposed is Quakertown to wildfire?
Out of every US place USFS scores, Quakertown lands at the 13th percentile for wildfire risk to structures — among the lower wildfire-risk places nationally — a figure built from its 2,670 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Quakertown's burn probability — fire likelihood with no building count factored in — sits at the 12th percentile nationally.
Quakertown's building exposure, zone by zone
USFS classifies 76.7% of Quakertown's buildings as Minimal exposure, the largest of the three zones here by a wide margin over 17% Direct and 6.3% Indirect — a landscape-level risk rather than a building-by-building one.
Where Quakertown ranks
Quakertown's risk sits at a similar level relative to Pennsylvania (12th percentile statewide) as it does nationally (13th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Quakertown ranks 27,466 for wildfire risk (1 is highest) and 5,982 by building count (1 is largest). Within Pennsylvania alone, it ranks 1,762 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
Quakertown's low wildfire rating (13th 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 76.7% of buildings rated Minimal exposure, Quakertown gets less benefit from structure hardening than a Direct- or Indirect-dominant place would — the home-hardening guide explains why the zone matters.
Where Quakertown's figures come from
Every one of the two percentiles behind Quakertown's 27,466-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Quakertown's dominant minimal exposure actually means, with real examples from across the dataset.