Sycamore, GA
Sycamore, GA's wildfire risk, in USFS's own numbers
USFS's Wildfire Risk to Communities model puts Sycamore at the 59th national percentile for risk to structures, modestly above the national average for wildfire risk — a score built from 416 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Sycamore at the 57th percentile, close to its 59th-percentile risk score.
What "at risk" means for the buildings here
Indirect exposure is dominant in Sycamore (61.3% of 416 buildings): far enough from burnable vegetation to avoid flame contact, close enough for wind-blown embers. Only 36.3% sit in the Direct zone.
Sycamore against the rest of the country
Sycamore ranks lower within Georgia (16th percentile statewide) than its 59th national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Sycamore ranks 13,074 for wildfire risk (1 is highest) and 18,905 by building count (1 is largest). Within Georgia alone, it ranks 562 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
At the 59th national percentile, Sycamore rates elevated for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
What would actually reduce this score
Sycamore's 61.3% Indirect-exposure share points at embers, not flame contact, as the main pathway — ember-resistant vents and non-combustible roofing rank ahead of defensible space here. Detail in the home-hardening guide.
Where Sycamore's figures come from
Every one of the two percentiles behind Sycamore's 13,074-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Sycamore's dominant indirect exposure actually means, with real examples from across the dataset.