Verandah, FL
How exposed is Verandah to wildfire?
Verandah's 1,155 buildings earn a 87th-percentile wildfire-risk score nationally under USFS's model — in USFS's highest wildfire-risk band nationally. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Verandah at the 88th national percentile — 2 points above its risk-to-structures score, a gap driven by how much is actually built there.
Where Verandah's buildings actually sit
65.6% of Verandah's 1,155 buildings fall in USFS's Indirect exposure zone — ember cast rather than direct flame — against 34.4% Direct and 0% Minimal. Vent screens and roofing material matter more here than lot clearing alone.
Verandah against the rest of the country
Inside Florida, Verandah sits at just the 71st percentile even though it scores 87th 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, Verandah ranks 4,160 for wildfire risk (1 is highest) and 10,914 by building count (1 is largest). Within Florida alone, it ranks 287 of 955 places by risk. See the full county-by-county picture for Florida on its state page.
What this risk score means for insurance
At the 87th percentile nationally, Verandah carries the very high rating that has pushed some carriers to limit new business in similarly-scored places elsewhere in the country. Worth comparing quotes rather than assuming last year's renewal terms still apply.
What would actually reduce this score
Because 65.6% of Verandah's buildings sit in the Indirect zone, sealing the ember pathway (vents, roofing, gutters) is the intervention this page's data actually supports — see the home-hardening guide.
Where Verandah's figures come from
The methodology guide shows exactly how USFS turned 1,155 counted buildings into the percentiles shown above for Verandah. The exposure-zones guide covers what Verandah's dominant indirect exposure actually means, with real examples from across the dataset.