Mitchell, GA
Mitchell, GA's wildfire risk, in USFS's own numbers
USFS scores Mitchell at the 66th national percentile for wildfire risk to structures (well above the national norm for wildfire risk), a figure built from 169 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Mitchell at the 67th national percentile — 1 points above its risk-to-structures score, a gap driven by how much is actually built there.
Mitchell's building exposure, zone by zone
USFS classifies 88.8% of Mitchell's buildings as Direct exposure, higher than its 11.2% Indirect share and far above its 0% Minimal share — a profile where 150 structures sit close enough to vegetation that lot clearing matters most.
Where Mitchell ranks
Mitchell's 66th national percentile looks worse in isolation than its 51st ranking inside Georgia does — this place is on the milder end for its own state, by 16 points. Among the 31,521 US communities USFS scores, Mitchell ranks 10,583 for wildfire risk (1 is highest) and 26,062 by building count (1 is largest). Within Georgia alone, it ranks 331 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
Mitchell's high rating (66th 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 88.8% of Mitchell 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 Mitchell's figures come from
Every one of the two percentiles behind Mitchell's 10,583-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Mitchell's dominant direct exposure actually means, with real examples from across the dataset.