Pinson, AL
How exposed is Pinson to wildfire?
USFS scores Pinson at the 73rd national percentile for wildfire risk to structures (well above the national norm for wildfire risk), a figure built from 3,675 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 Pinson at the 76th percentile, close to its 73rd-percentile risk score.
Where Pinson's buildings actually sit
USFS classifies 73.3% of Pinson's buildings as Direct exposure, higher than its 24.5% Indirect share and far above its 2.2% Minimal share — a profile where 2,694 structures sit close enough to vegetation that lot clearing matters most.
How Pinson compares
Inside Alabama, Pinson sits at just the 54th percentile even though it scores 73rd 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, Pinson ranks 8,530 for wildfire risk (1 is highest) and 4,556 by building count (1 is largest). Within Alabama alone, it ranks 276 of 592 places by risk. See the full county-by-county picture for Alabama on its state page.
What this risk score means for insurance
Pinson's 73rd-percentile, 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 Pinson (73.3%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.
Where Pinson's figures come from
Every one of the two percentiles behind Pinson's 8,530-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Pinson's dominant direct exposure actually means, with real examples from across the dataset.