Tignall, GA
Tignall wildfire risk explained
Tignall's 429 buildings earn a 72nd-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.)
Fire likelihood alone (USFS's burn-probability figure) ranks Tignall at the 75th national percentile — 3 points above its risk-to-structures score, a gap driven by how much is actually built there.
Where Tignall's buildings actually sit
88.1% of Tignall's 429 buildings sit in USFS's Direct exposure zone, roughly 378 structures close enough to burnable vegetation for flame contact, not just embers — 11.9% fall in the Indirect, ember-only zone and 0% are Minimal.
Where Tignall ranks
Tignall scores 72nd nationally and 73rd within Georgia — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, Tignall ranks 8,760 for wildfire risk (1 is highest) and 18,668 by building count (1 is largest). Within Georgia alone, it ranks 180 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
Tignall's 72nd-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
Tignall's 88.1% Direct-exposure share means lot clearing around the structure typically outweighs any single material upgrade here. The home-hardening guide ranks the options for a place shaped like this.
Where Tignall's figures come from
Every one of the two percentiles behind Tignall's 8,760-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Tignall's dominant direct exposure actually means, with real examples from across the dataset.