Talmo, GA
Talmo, GA's wildfire risk, in USFS's own numbers
Talmo sits at the 61st 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 255 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Talmo at the 65th national percentile — 4 points above its risk-to-structures score, a gap driven by how much is actually built there.
Where Talmo's buildings actually sit
96.5% of Talmo's 255 buildings sit in USFS's Direct exposure zone, roughly 246 structures close enough to burnable vegetation for flame contact, not just embers — 3.5% fall in the Indirect, ember-only zone and 0% are Minimal.
Talmo against the rest of the country
Inside Georgia, Talmo sits at just the 23rd percentile even though it scores 61st 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, Talmo ranks 12,259 for wildfire risk (1 is highest) and 22,974 by building count (1 is largest). Within Georgia alone, it ranks 519 of 669 places by risk. See the full county-by-county picture for Georgia on its state page.
Shopping for coverage in Talmo
Talmo'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.
Hardening a home in Talmo
With 96.5% of Talmo 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 Talmo's figures come from
The methodology guide shows exactly how USFS turned 255 counted buildings into the percentiles shown above for Talmo. The exposure-zones guide covers what Talmo's dominant direct exposure actually means, with real examples from across the dataset.