Sipsey, AL
Sipsey wildfire risk explained
USFS's Wildfire Risk to Communities model puts Sipsey at the 76th national percentile for risk to structures, well above the national norm for wildfire risk — a score built from 286 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Sipsey's burn probability — fire likelihood with no building count factored in — sits at the 80th percentile nationally.
What "at risk" means for the buildings here
64.3% of Sipsey's 286 buildings sit in USFS's Direct exposure zone, roughly 184 structures close enough to burnable vegetation for flame contact, not just embers — 35.7% fall in the Indirect, ember-only zone and 0% are Minimal.
Sipsey against the rest of the country
There's little gap between Sipsey's 76th national percentile and its 65th percentile inside Alabama, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Sipsey ranks 7,427 for wildfire risk (1 is highest) and 21,997 by building count (1 is largest). Within Alabama alone, it ranks 211 of 592 places by risk. See the full county-by-county picture for Alabama on its state page.
Sipsey and the insurance market
At the 76th percentile nationally, Sipsey carries the 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.
Hardening a home in Sipsey
With 64.3% of Sipsey in Direct exposure, defensible-space clearing and ember-resistant construction (vents, Class-A roofing) address the exposure this page's own numbers describe, not a generic checklist. See the home-hardening guide.
Where Sipsey's figures come from
Sipsey's 76th-percentile score and its burn-probability figure both come from the same USFS workbook, documented in the methodology guide. The exposure-zones guide covers what Sipsey's dominant direct exposure actually means, with real examples from across the dataset.