Pleasant Groves, AL
How exposed is Pleasant Groves to wildfire?
Pleasant Groves's 337 buildings earn a 67th-percentile wildfire-risk score nationally under USFS's model — well above the national norm for wildfire risk. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Pleasant Groves's burn probability — fire likelihood with no building count factored in — sits at the 70th percentile nationally.
What "at risk" means for the buildings here
Of Pleasant Groves's 337 counted buildings, 100% carry Direct exposure and only 0% carry Minimal — a lopsided split that puts defensible-space clearing ahead of vents or roofing as the intervention worth doing first.
Pleasant Groves against the rest of the country
Inside Alabama, Pleasant Groves sits at just the 39th percentile even though it scores 67th 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, Pleasant Groves ranks 10,483 for wildfire risk (1 is highest) and 20,650 by building count (1 is largest). Within Alabama alone, it ranks 363 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
At the 67th percentile nationally, Pleasant Groves 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.
Lowering exposure, not just insuring around it
Because Direct exposure dominates in Pleasant Groves (100%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.
Where Pleasant Groves's figures come from
Every one of the two percentiles behind Pleasant Groves's 10,483-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Pleasant Groves's dominant direct exposure actually means, with real examples from across the dataset.