Ivanhoe, NC
Ivanhoe, NC's wildfire risk, in USFS's own numbers
USFS scores Ivanhoe at the 84th national percentile for wildfire risk to structures (in USFS's highest wildfire-risk band nationally), a figure built from 226 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 Ivanhoe at the 83rd percentile, close to its 84th-percentile risk score.
What "at risk" means for the buildings here
Of Ivanhoe's 226 counted buildings, 100% carry Direct exposure and only 0% carry Minimal — a lopsided split that puts defensible-space clearing ahead of vents or roofing as the intervention worth doing first.
Ivanhoe against the rest of the country
There's little gap between Ivanhoe's 84th national percentile and its 93rd 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, Ivanhoe ranks 4,988 for wildfire risk (1 is highest) and 23,922 by building count (1 is largest). Within North Carolina alone, it ranks 56 of 772 places by risk. See the full county-by-county picture for North Carolina on its state page.
What this risk score means for insurance
Ivanhoe's very high rating (84th 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 100% of Ivanhoe 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 Ivanhoe's figures come from
The methodology guide shows exactly how USFS turned 226 counted buildings into the percentiles shown above for Ivanhoe. The exposure-zones guide covers what Ivanhoe's dominant direct exposure actually means, with real examples from across the dataset.