Utica, OK
How exposed is Utica to wildfire?
USFS scores Utica at the 77th national percentile for wildfire risk to structures (well above the national norm for wildfire risk), a figure built from 52 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Utica at the 78th percentile, close to its 77th-percentile risk score.
What "at risk" means for the buildings here
USFS classifies 100% of Utica's buildings as Direct exposure, higher than its 0% Indirect share and far above its 0% Minimal share — a profile where 52 structures sit close enough to vegetation that lot clearing matters most.
How Utica compares
Utica's 77th national percentile looks worse in isolation than its 16th ranking inside Oklahoma does — this place is on the milder end for its own state, by 61 points. Among the 31,521 US communities USFS scores, Utica ranks 7,413 for wildfire risk (1 is highest) and 30,885 by building count (1 is largest). Within Oklahoma alone, it ranks 704 of 834 places by risk. See the full county-by-county picture for Oklahoma on its state page.
Utica and the insurance market
Utica's 77th-percentile, high rating is the kind of score behind a broader national pattern: insurers pulling back from the highest wildfire-risk markets, non-renewing or declining new policies outright, most visibly in California. Shopping around, not assuming automatic renewal, tends to matter here.
What would actually reduce this score
Utica's 100% Direct-exposure share means lot clearing around the structure typically outweighs any single material upgrade here. The home-hardening guide ranks the options for a place shaped like this.
Where Utica's figures come from
The methodology guide shows exactly how USFS turned 52 counted buildings into the percentiles shown above for Utica. The exposure-zones guide covers what Utica's dominant direct exposure actually means, with real examples from across the dataset.