Keyport, WA
Keyport wildfire risk explained
Keyport sits at the 19th percentile nationally for wildfire risk to structures — among the lower wildfire-risk places nationally — per USFS's Wildfire Risk to Communities model, built from its 345 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Keyport at the 19th percentile, close to its 19th-percentile risk score.
Where Keyport's buildings actually sit
USFS puts 87.3% of Keyport's 345 buildings in the Indirect exposure zone, versus 5.8% Direct and 7% Minimal — a place where the fire doesn't need to reach the structure directly for embers to.
Keyport against the rest of the country
Keyport's risk sits at a similar level relative to Washington (29th percentile statewide) as it does nationally (19th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Keyport ranks 25,420 for wildfire risk (1 is highest) and 20,462 by building count (1 is largest). Within Washington alone, it ranks 446 of 628 places by risk. See the full county-by-county picture for Washington on its state page.
Keyport and the insurance market
At the 19th national percentile, Keyport rates low for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
What would actually reduce this score
Keyport's 87.3% Indirect-exposure share points at embers, not flame contact, as the main pathway — ember-resistant vents and non-combustible roofing rank ahead of defensible space here. Detail in the home-hardening guide.
Where Keyport's figures come from
Every one of the two percentiles behind Keyport's 25,420-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Keyport's dominant indirect exposure actually means, with real examples from across the dataset.