Chevy Chase (CDP), MD
How exposed is Chevy Chase (CDP) to wildfire?
Chevy Chase (CDP)'s 1,122 buildings earn a 11th-percentile wildfire-risk score nationally under USFS's model — among the lower wildfire-risk places nationally. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Chevy Chase (CDP) at the 11th national percentile — 0 points above its risk-to-structures score, a gap driven by how much is actually built there.
Chevy Chase (CDP)'s building exposure, zone by zone
Chevy Chase (CDP) rates 59.9% Minimal exposure against just 40.1% Direct and 0% Indirect — of 1,122 buildings counted, few sit close enough to burnable vegetation for USFS to flag them individually.
Chevy Chase (CDP) against the rest of the country
There's little gap between Chevy Chase (CDP)'s 11th national percentile and its 5th percentile inside Maryland, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Chevy Chase (CDP) ranks 28,206 for wildfire risk (1 is highest) and 11,141 by building count (1 is largest). Within Maryland alone, it ranks 499 of 527 places by risk. See the full county-by-county picture for Maryland on its state page.
Chevy Chase (CDP) and the insurance market
Chevy Chase (CDP)'s low wildfire rating (11th 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.
Lowering exposure, not just insuring around it
Chevy Chase (CDP)'s 59.9% 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 Chevy Chase (CDP)'s figures come from
The methodology guide shows exactly how USFS turned 1,122 counted buildings into the percentiles shown above for Chevy Chase (CDP). The exposure-zones guide covers what Chevy Chase (CDP)'s dominant minimal exposure actually means, with real examples from across the dataset.