WildfireRiskFinder

Boone, NC

Boone wildfire risk explained

High
61stpercentile nationally

USFS scores Boone at the 61st national percentile for wildfire risk to structures (well above the national norm for wildfire risk), a figure built from 3,426 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)

Fire likelihood alone (USFS's burn-probability figure) ranks Boone at the 63rd national percentile — 2 points above its risk-to-structures score, a gap driven by how much is actually built there.

Where Boone's buildings actually sit

3,426Total buildings
45.3%Direct exposure
54.7%Indirect exposure
0%Minimal exposure

Indirect exposure is dominant in Boone (54.7% of 3,426 buildings): far enough from burnable vegetation to avoid flame contact, close enough for wind-blown embers. Only 45.3% sit in the Direct zone.

Where Boone ranks

Boone scores 61st nationally and 59th 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, Boone ranks 12,397 for wildfire risk (1 is highest) and 4,878 by building count (1 is largest). Within North Carolina alone, it ranks 314 of 772 places by risk. See the full county-by-county picture for North Carolina on its state page.

Boone and the insurance market

Boone's high rating (61st percentile) puts it among the places where the national carrier-pullback trend is most relevant — not a guarantee of a coverage problem, but a reason to shop rather than assume.

What would actually reduce this score

With ember exposure the dominant pattern in Boone (54.7% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.

Where Boone's figures come from

Boone's 61st-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 Boone's dominant indirect exposure actually means, with real examples from across the dataset.