Putney, GA
Putney wildfire risk explained
USFS scores Putney at the 67th national percentile for wildfire risk to structures (well above the national norm for wildfire risk), a figure built from 1,795 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Putney's burn probability — fire likelihood with no building count factored in — sits at the 67th percentile nationally.
What "at risk" means for the buildings here
1,795 buildings are counted in Putney, and 92% of them sit in USFS's Direct exposure zone — flame contact, not just ember cast, is the live possibility for most of them, against 0% rated Minimal.
How Putney compares
There's little gap between Putney's 67th national percentile and its 52nd percentile inside Georgia, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Putney ranks 10,459 for wildfire risk (1 is highest) and 8,083 by building count (1 is largest). Within Georgia alone, it ranks 318 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
Putney's 67th-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.
What would actually reduce this score
Putney's 92% 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 Putney's figures come from
Every one of the two percentiles behind Putney's 10,459-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Putney's dominant direct exposure actually means, with real examples from across the dataset.