Cobb Island, MD
How exposed is Cobb Island to wildfire?
USFS scores Cobb Island at the 40th national percentile for wildfire risk to structures (close to the middle of USFS's national wildfire-risk range), a figure built from 672 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Cobb Island's burn probability — fire likelihood with no building count factored in — sits at the 35th percentile nationally.
Cobb Island's building exposure, zone by zone
Cobb Island rates 50.6% Minimal exposure against just 31% Direct and 18.5% Indirect — of 672 buildings counted, few sit close enough to burnable vegetation for USFS to flag them individually.
How Cobb Island compares
Cobb Island's 58th-percentile standing inside Maryland outpaces its 40th 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, Cobb Island ranks 19,062 for wildfire risk (1 is highest) and 14,951 by building count (1 is largest). Within Maryland alone, it ranks 223 of 527 places by risk. See the full county-by-county picture for Maryland on its state page.
Cobb Island and the insurance market
Cobb Island's moderate wildfire rating (40th 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 50.6% of buildings rated Minimal exposure, Cobb Island gets less benefit from structure hardening than a Direct- or Indirect-dominant place would — the home-hardening guide explains why the zone matters.
Where Cobb Island's figures come from
Every one of the two percentiles behind Cobb Island's 19,062-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Cobb Island's dominant minimal exposure actually means, with real examples from across the dataset.