Franklin, AL
Franklin wildfire risk explained
Franklin sits at the 74th percentile nationally for wildfire risk to structures — well above the national norm for wildfire risk — per USFS's Wildfire Risk to Communities model, built from its 491 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Franklin's burn probability — fire likelihood with no building count factored in — sits at the 75th percentile nationally.
Franklin's building exposure, zone by zone
491 buildings are counted in Franklin, 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.
Franklin against the rest of the country
Franklin ranks lower within Alabama (56th percentile statewide) than its 74th national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Franklin ranks 8,244 for wildfire risk (1 is highest) and 17,505 by building count (1 is largest). Within Alabama alone, it ranks 264 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
Franklin's 74th-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.
What would actually reduce this score
Because Direct exposure dominates in Franklin (100%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.
Where Franklin's figures come from
Franklin's 74th-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 Franklin's dominant direct exposure actually means, with real examples from across the dataset.