Goldston, NC
Goldston wildfire risk explained
Goldston sits at the 52nd percentile nationally for wildfire risk to structures — modestly above the national average for wildfire risk — per USFS's Wildfire Risk to Communities model, built from its 279 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 Goldston at the 54th percentile, close to its 52nd-percentile risk score.
Where Goldston's buildings actually sit
86.4% of Goldston's 279 buildings sit in USFS's Direct exposure zone, roughly 241 structures close enough to burnable vegetation for flame contact, not just embers — 13.6% fall in the Indirect, ember-only zone and 0% are Minimal.
Where Goldston ranks
Goldston scores 52nd nationally and 44th within North Carolina — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, Goldston ranks 15,136 for wildfire risk (1 is highest) and 22,229 by building count (1 is largest). Within North Carolina alone, it ranks 434 of 772 places by risk. See the full county-by-county picture for North Carolina on its state page.
Shopping for coverage in Goldston
Goldston's elevated wildfire rating (52nd 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.
Hardening a home in Goldston
Goldston's 86.4% 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 Goldston's figures come from
Every one of the two percentiles behind Goldston's 15,136-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Goldston's dominant direct exposure actually means, with real examples from across the dataset.