Longfellow, PA
Longfellow wildfire risk explained
Longfellow sits at the 52nd 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 160 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Longfellow's burn probability — fire likelihood with no building count factored in — sits at the 50th percentile nationally.
What "at risk" means for the buildings here
160 buildings are counted in Longfellow, and 91.9% of them sit in USFS's Direct exposure zone — flame contact, not just ember cast, is the live possibility for most of them, against 0% rated Minimal.
Longfellow against the rest of the country
Longfellow's 86th-percentile standing inside Pennsylvania outpaces its 52nd national percentile — this is a hotter spot than most of its own state, even though the state as a whole runs cooler nationally. Among the 31,521 US communities USFS scores, Longfellow ranks 15,205 for wildfire risk (1 is highest) and 26,451 by building count (1 is largest). Within Pennsylvania alone, it ranks 290 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
At the 52nd national percentile, Longfellow rates elevated for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
What would actually reduce this score
Because Direct exposure dominates in Longfellow (91.9%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.
Where Longfellow's figures come from
Every one of the two percentiles behind Longfellow's 15,205-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Longfellow's dominant direct exposure actually means, with real examples from across the dataset.