Nelson, GA
Nelson wildfire risk explained
Nelson's 559 buildings earn a 65th-percentile wildfire-risk score nationally under USFS's model — well above the national norm for wildfire risk. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Nelson at the 67th percentile, close to its 65th-percentile risk score.
What "at risk" means for the buildings here
Of Nelson's 559 counted buildings, 89.1% 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.
Where Nelson ranks
Inside Georgia, Nelson sits at just the 43rd percentile even though it scores 65th nationally — the state's overall wildfire exposure is high enough to make this a relatively quiet corner of it. Among the 31,521 US communities USFS scores, Nelson ranks 10,962 for wildfire risk (1 is highest) and 16,418 by building count (1 is largest). Within Georgia alone, it ranks 384 of 669 places by risk. See the full county-by-county picture for Georgia on its state page.
What this risk score means for insurance
Nelson's 65th-percentile, high rating is the kind of score behind a broader national pattern: insurers pulling back from the highest wildfire-risk markets, non-renewing or declining new policies outright, most visibly in California. Shopping around, not assuming automatic renewal, tends to matter here.
Lowering exposure, not just insuring around it
With 89.1% of Nelson 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 Nelson's figures come from
Nelson's 65th-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 Nelson's dominant direct exposure actually means, with real examples from across the dataset.