WildfireRiskFinder

Hebron, PA

How exposed is Hebron to wildfire?

Low
11thpercentile nationally

USFS's Wildfire Risk to Communities model puts Hebron at the 11th national percentile for risk to structures, among the lower wildfire-risk places nationally — a score built from 204 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)

USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Hebron at the 12th percentile, close to its 11th-percentile risk score.

What "at risk" means for the buildings here

204Total buildings
1%Direct exposure
0%Indirect exposure
99%Minimal exposure

Only 1% of Hebron's 204 buildings carry Direct exposure and 0% carry Indirect; the remaining 99% are Minimal, which shifts the risk driving this page's score toward the surrounding landscape rather than any one structure.

Where Hebron ranks

Hebron's risk sits at a similar level relative to Pennsylvania (9th percentile statewide) as it does nationally (11th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Hebron ranks 28,122 for wildfire risk (1 is highest) and 24,706 by building count (1 is largest). Within Pennsylvania alone, it ranks 1,811 of 1,991 places by risk. See the full county-by-county picture for Pennsylvania on its state page.

Shopping for coverage in Hebron

Hebron's low rating (11th percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.

Lowering exposure, not just insuring around it

Hebron's 99% Minimal-exposure share means structure-level hardening matters less here than it would elsewhere — still worth the low-cost basics, per the home-hardening guide.

Where Hebron's figures come from

The methodology guide shows exactly how USFS turned 204 counted buildings into the percentiles shown above for Hebron. The exposure-zones guide covers what Hebron's dominant minimal exposure actually means, with real examples from across the dataset.