Linganore, MD
Linganore wildfire risk explained
Out of every US place USFS scores, Linganore lands at the 14th percentile for wildfire risk to structures — among the lower wildfire-risk places nationally — a figure built from its 3,488 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Linganore at the 13th percentile, close to its 14th-percentile risk score.
Linganore's building exposure, zone by zone
3,488 buildings are counted in Linganore, and 58.6% of them sit in USFS's Direct exposure zone — flame contact, not just ember cast, is the live possibility for most of them, against 0.7% rated Minimal.
Linganore against the rest of the country
There's little gap between Linganore's 14th national percentile and its 12th percentile inside Maryland, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Linganore ranks 27,042 for wildfire risk (1 is highest) and 4,785 by building count (1 is largest). Within Maryland alone, it ranks 462 of 527 places by risk. See the full county-by-county picture for Maryland on its state page.
Linganore and the insurance market
Linganore's low wildfire rating (14th 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
Because Direct exposure dominates in Linganore (58.6%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.
Where Linganore's figures come from
Every one of the two percentiles behind Linganore's 27,042-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Linganore's dominant direct exposure actually means, with real examples from across the dataset.