Linthicum, MD
Linthicum wildfire risk explained
USFS scores Linthicum at the 22nd national percentile for wildfire risk to structures (close to the middle of USFS's national wildfire-risk range), a figure built from 4,659 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Linthicum at the 22nd national percentile — 0 points above its risk-to-structures score, a gap driven by how much is actually built there.
What "at risk" means for the buildings here
Linthicum rates 85.1% Minimal exposure against just 14.9% Direct and 0% Indirect — of 4,659 buildings counted, few sit close enough to burnable vegetation for USFS to flag them individually.
Linthicum against the rest of the country
There's little gap between Linthicum's 22nd national percentile and its 30th percentile inside Maryland, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Linthicum ranks 24,678 for wildfire risk (1 is highest) and 3,651 by building count (1 is largest). Within Maryland alone, it ranks 370 of 527 places by risk. See the full county-by-county picture for Maryland on its state page.
Linthicum and the insurance market
Linthicum's moderate wildfire rating (22nd 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 85.1% of buildings rated Minimal exposure, Linthicum gets less benefit from structure hardening than a Direct- or Indirect-dominant place would — the home-hardening guide explains why the zone matters.
Where Linthicum's figures come from
Every one of the two percentiles behind Linthicum's 24,678-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Linthicum's dominant minimal exposure actually means, with real examples from across the dataset.