Selma, AL
How exposed is Selma to wildfire?
Selma's 8,544 buildings earn a 55th-percentile wildfire-risk score nationally under USFS's model — modestly above the national average for wildfire risk. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Selma at the 58th percentile, close to its 55th-percentile risk score.
Selma's building exposure, zone by zone
8,544 buildings are counted in Selma, and 67.5% of them are Indirect exposure — ember-driven risk rather than the 28.4% in Direct exposure or the 4.1% rated Minimal. At 8,544 buildings, this is a substantial built environment, so the shares below describe a real population of structures, not a handful of edge cases.
Selma against the rest of the country
Inside Alabama, Selma sits at just the 12th percentile even though it scores 55th 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, Selma ranks 14,202 for wildfire risk (1 is highest) and 1,944 by building count (1 is largest). Within Alabama alone, it ranks 521 of 592 places by risk. See the full county-by-county picture for Alabama on its state page.
Selma and the insurance market
Selma's elevated wildfire rating (55th percentile) isn't the kind of score driving the carrier pullback making news in the highest-risk Western markets — but a standard homeowners quote is still worth comparing on its own terms.
What would actually reduce this score
Because 67.5% of Selma's buildings sit in the Indirect zone, sealing the ember pathway (vents, roofing, gutters) is the intervention this page's data actually supports — see the home-hardening guide.
Where Selma's figures come from
Every one of the two percentiles behind Selma's 14,202-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Selma's dominant indirect exposure actually means, with real examples from across the dataset.