Gatesville, NC
Gatesville wildfire risk explained
USFS scores Gatesville at the 47th national percentile for wildfire risk to structures (modestly above the national average for wildfire risk), a figure built from 278 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 Gatesville at the 48th percentile, close to its 47th-percentile risk score.
Where Gatesville's buildings actually sit
Direct exposure dominates in Gatesville: 66.9% of its 278 buildings, versus 33.1% Indirect and 0% Minimal. Clearing space around a structure changes the outcome here more than any single building-material swap.
Where Gatesville ranks
Gatesville's 47th national percentile looks worse in isolation than its 31st ranking inside North Carolina does — this place is on the milder end for its own state, by 16 points. Among the 31,521 US communities USFS scores, Gatesville ranks 16,739 for wildfire risk (1 is highest) and 22,276 by building count (1 is largest). Within North Carolina alone, it ranks 532 of 772 places by risk. See the full county-by-county picture for North Carolina on its state page.
Gatesville and the insurance market
At the 47th national percentile, Gatesville rates elevated for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
Lowering exposure, not just insuring around it
With 66.9% of Gatesville in Direct exposure, defensible-space clearing and ember-resistant construction (vents, Class-A roofing) address the exposure this page's own numbers describe, not a generic checklist. See the home-hardening guide.
Where Gatesville's figures come from
Gatesville's 47th-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 Gatesville's dominant direct exposure actually means, with real examples from across the dataset.