Ansonville, NC
Ansonville wildfire risk explained
USFS scores Ansonville at the 53rd national percentile for wildfire risk to structures (modestly above the national average for wildfire risk), a figure built from 372 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 Ansonville at the 56th percentile, close to its 53rd-percentile risk score.
What "at risk" means for the buildings here
89.5% of Ansonville's 372 buildings sit in USFS's Direct exposure zone, roughly 333 structures close enough to burnable vegetation for flame contact, not just embers — 10.5% fall in the Indirect, ember-only zone and 0% are Minimal.
Where Ansonville ranks
There's little gap between Ansonville's 53rd national percentile and its 47th percentile inside North Carolina, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Ansonville ranks 14,723 for wildfire risk (1 is highest) and 19,825 by building count (1 is largest). Within North Carolina alone, it ranks 407 of 772 places by risk. See the full county-by-county picture for North Carolina on its state page.
Ansonville and the insurance market
Ansonville's elevated wildfire rating (53rd 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.
What would actually reduce this score
Ansonville's 89.5% 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 Ansonville's figures come from
The methodology guide shows exactly how USFS turned 372 counted buildings into the percentiles shown above for Ansonville. The exposure-zones guide covers what Ansonville's dominant direct exposure actually means, with real examples from across the dataset.