Ashland, AL
Ashland, AL's wildfire risk, in USFS's own numbers
USFS's Wildfire Risk to Communities model puts Ashland at the 90th national percentile for risk to structures, in USFS's highest wildfire-risk band nationally — a score built from 1,220 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 Ashland at the 93rd percentile, close to its 90th-percentile risk score.
Ashland's building exposure, zone by zone
80.4% of Ashland's 1,220 buildings sit in USFS's Direct exposure zone, roughly 981 structures close enough to burnable vegetation for flame contact, not just embers — 19.6% fall in the Indirect, ember-only zone and 0% are Minimal.
Ashland against the rest of the country
Ashland's risk sits at a similar level relative to Alabama (98th percentile statewide) as it does nationally (90th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Ashland ranks 3,201 for wildfire risk (1 is highest) and 10,534 by building count (1 is largest). Within Alabama alone, it ranks 13 of 592 places by risk. See the full county-by-county picture for Alabama on its state page.
Ashland and the insurance market
Ashland's 90th-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.
Lowering exposure, not just insuring around it
Because Direct exposure dominates in Ashland (80.4%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.
Where Ashland's figures come from
Ashland's 90th-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 Ashland's dominant direct exposure actually means, with real examples from across the dataset.