WildfireRiskFinder

Dunkirk, MD

Dunkirk, MD's wildfire risk, in USFS's own numbers

Elevated
47thpercentile nationally

USFS's Wildfire Risk to Communities model puts Dunkirk at the 47th national percentile for risk to structures, modestly above the national average for wildfire risk — a score built from 1,216 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)

Fire likelihood alone (USFS's burn-probability figure) ranks Dunkirk at the 47th national percentile — 0 points below its risk-to-structures score, a gap driven by how much is actually built there.

Dunkirk's building exposure, zone by zone

1,216Total buildings
93.1%Direct exposure
6.9%Indirect exposure
0%Minimal exposure

Direct exposure dominates in Dunkirk: 93.1% of its 1,216 buildings, versus 6.9% Indirect and 0% Minimal. Clearing space around a structure changes the outcome here more than any single building-material swap.

Where Dunkirk ranks

Compare Dunkirk's two percentiles: 67th within Maryland, only 47th nationally — a gap of 19 points that marks it as unusually exposed for its own state. Among the 31,521 US communities USFS scores, Dunkirk ranks 16,576 for wildfire risk (1 is highest) and 10,553 by building count (1 is largest). Within Maryland alone, it ranks 176 of 527 places by risk. See the full county-by-county picture for Maryland on its state page.

What this risk score means for insurance

Dunkirk's elevated rating (47th 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

Because Direct exposure dominates in Dunkirk (93.1%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.

Where Dunkirk's figures come from

The methodology guide shows exactly how USFS turned 1,216 counted buildings into the percentiles shown above for Dunkirk. The exposure-zones guide covers what Dunkirk's dominant direct exposure actually means, with real examples from across the dataset.