Daisy, GA
Daisy wildfire risk explained
Daisy sits at the 73rd 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 117 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Daisy at the 73rd national percentile — 0 points below its risk-to-structures score, a gap driven by how much is actually built there.
What "at risk" means for the buildings here
USFS classifies 82.9% of Daisy's buildings as Direct exposure, higher than its 17.1% Indirect share and far above its 0% Minimal share — a profile where 97 structures sit close enough to vegetation that lot clearing matters most.
How Daisy compares
There's little gap between Daisy's 73rd national percentile and its 76th percentile inside Georgia, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Daisy ranks 8,469 for wildfire risk (1 is highest) and 28,290 by building count (1 is largest). Within Georgia alone, it ranks 159 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
Daisy's high rating (73rd 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 Daisy
Daisy's 82.9% 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 Daisy's figures come from
Every one of the two percentiles behind Daisy's 8,469-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Daisy's dominant direct exposure actually means, with real examples from across the dataset.