Salemburg, NC
Salemburg wildfire risk explained
Salemburg sits at the 64th percentile nationally for wildfire risk to structures — well above the national norm for wildfire risk — per USFS's Wildfire Risk to Communities model, built from its 416 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Salemburg's burn probability — fire likelihood with no building count factored in — sits at the 63rd percentile nationally.
Salemburg's building exposure, zone by zone
Of Salemburg's 416 counted buildings, 50.2% 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.
How Salemburg compares
Salemburg scores 64th nationally and 63rd 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, Salemburg ranks 11,356 for wildfire risk (1 is highest) and 18,910 by building count (1 is largest). Within North Carolina alone, it ranks 288 of 772 places by risk. See the full county-by-county picture for North Carolina on its state page.
Shopping for coverage in Salemburg
At the 64th percentile nationally, Salemburg carries the high rating that has pushed some carriers to limit new business in similarly-scored places elsewhere in the country. Worth comparing quotes rather than assuming last year's renewal terms still apply.
Hardening a home in Salemburg
With 50.2% of Salemburg 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 Salemburg's figures come from
The methodology guide shows exactly how USFS turned 416 counted buildings into the percentiles shown above for Salemburg. The exposure-zones guide covers what Salemburg's dominant direct exposure actually means, with real examples from across the dataset.