WildfireRiskFinder

Chelsea, OK

Chelsea, OK's wildfire risk, in USFS's own numbers

High
78thpercentile nationally

Chelsea's 1,276 buildings earn a 78th-percentile wildfire-risk score nationally under USFS's model — well above the national norm for wildfire risk. (Source: USFS's Wildfire Risk to Communities methodology.)

Separately from the risk score above, Chelsea's burn probability — fire likelihood with no building count factored in — sits at the 79th percentile nationally.

Where Chelsea's buildings actually sit

1,276Total buildings
36.1%Direct exposure
64%Indirect exposure
0%Minimal exposure

1,276 buildings are counted in Chelsea, and 64% of them are Indirect exposure — ember-driven risk rather than the 36.1% in Direct exposure or the 0% rated Minimal.

Where Chelsea ranks

Inside Oklahoma, Chelsea sits at just the 17th percentile even though it scores 78th nationally — the state's overall wildfire exposure is high enough to make this a relatively quiet corner of it. Among the 31,521 US communities USFS scores, Chelsea ranks 7,030 for wildfire risk (1 is highest) and 10,217 by building count (1 is largest). Within Oklahoma alone, it ranks 695 of 834 places by risk. See the full county-by-county picture for Oklahoma on its state page.

What this risk score means for insurance

At the 78th percentile nationally, Chelsea carries the high rating that has pushed some carriers to limit new business in similarly-scored places elsewhere in the country. Worth comparing quotes rather than assuming last year's renewal terms still apply.

Lowering exposure, not just insuring around it

With ember exposure the dominant pattern in Chelsea (64% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.

Where Chelsea's figures come from

Chelsea's 78th-percentile score and its burn-probability figure both come from the same USFS workbook, documented in the methodology guide. The exposure-zones guide covers what Chelsea's dominant indirect exposure actually means, with real examples from across the dataset.