Equality, AL
How exposed is Equality to wildfire?
USFS scores Equality at the 85th national percentile for wildfire risk to structures (in USFS's highest wildfire-risk band nationally), a figure built from 185 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Equality at the 88th percentile, close to its 85th-percentile risk score.
What "at risk" means for the buildings here
185 buildings are counted in Equality, and 100% 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.
Where Equality ranks
Equality's risk sits at a similar level relative to Alabama (88th percentile statewide) as it does nationally (85th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Equality ranks 4,651 for wildfire risk (1 is highest) and 25,406 by building count (1 is largest). Within Alabama alone, it ranks 69 of 592 places by risk. See the full county-by-county picture for Alabama on its state page.
Shopping for coverage in Equality
Equality's 85th-percentile, very 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.
Hardening a home in Equality
Equality's 100% 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 Equality's figures come from
Every one of the two percentiles behind Equality's 4,651-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Equality's dominant direct exposure actually means, with real examples from across the dataset.