Florence, MS
How exposed is Florence to wildfire?
USFS's Wildfire Risk to Communities model puts Florence at the 61st national percentile for risk to structures, well above the national norm for wildfire risk — a score built from 2,095 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Florence at the 63rd national percentile — 2 points above its risk-to-structures score, a gap driven by how much is actually built there.
What "at risk" means for the buildings here
USFS puts 51.1% of Florence's 2,095 buildings in the Indirect exposure zone, versus 48.9% Direct and 0% Minimal — a place where the fire doesn't need to reach the structure directly for embers to.
Florence against the rest of the country
Florence ranks lower within Mississippi (37th percentile statewide) than its 61st national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Florence ranks 12,291 for wildfire risk (1 is highest) and 7,207 by building count (1 is largest). Within Mississippi alone, it ranks 267 of 420 places by risk. See the full county-by-county picture for Mississippi on its state page.
Shopping for coverage in Florence
Florence's 61st-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.
Hardening a home in Florence
With ember exposure the dominant pattern in Florence (51.1% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.
Where Florence's figures come from
The methodology guide shows exactly how USFS turned 2,095 counted buildings into the percentiles shown above for Florence. The exposure-zones guide covers what Florence's dominant indirect exposure actually means, with real examples from across the dataset.