Davis, NC
Davis, NC's wildfire risk, in USFS's own numbers
Out of every US place USFS scores, Davis lands at the 97th percentile for wildfire risk to structures — in USFS's highest wildfire-risk band nationally — a figure built from its 371 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Davis's burn probability — fire likelihood with no building count factored in — sits at the 95th percentile nationally.
Where Davis's buildings actually sit
Of Davis's 371 counted buildings, 85.7% carry Direct exposure and only 4% carry Minimal — a lopsided split that puts defensible-space clearing ahead of vents or roofing as the intervention worth doing first.
Where Davis ranks
Davis's risk sits at a similar level relative to North Carolina (100th percentile statewide) as it does nationally (97th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Davis ranks 979 for wildfire risk (1 is highest) and 19,841 by building count (1 is largest). Within North Carolina alone, it ranks 3 of 772 places by risk. See the full county-by-county picture for North Carolina on its state page.
Davis and the insurance market
Davis's 97th-percentile, very 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.
Lowering exposure, not just insuring around it
Davis's 85.7% 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 Davis's figures come from
Davis's 97th-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 Davis's dominant direct exposure actually means, with real examples from across the dataset.