Florence, KS
Florence wildfire risk explained
Out of every US place USFS scores, Florence lands at the 82nd percentile for wildfire risk to structures — in USFS's highest wildfire-risk band nationally — a figure built from its 415 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Florence at the 78th national percentile — 5 points below its risk-to-structures score, a gap driven by how much is actually built there.
Where Florence's buildings actually sit
USFS puts 87.5% of Florence's 415 buildings in the Indirect exposure zone, versus 12.5% Direct and 0% Minimal — a place where the fire doesn't need to reach the structure directly for embers to.
How Florence compares
Florence's risk sits at a similar level relative to Kansas (81st percentile statewide) as it does nationally (82nd) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Florence ranks 5,576 for wildfire risk (1 is highest) and 18,923 by building count (1 is largest). Within Kansas alone, it ranks 136 of 721 places by risk. See the full county-by-county picture for Kansas on its state page.
Florence and the insurance market
Florence's 82nd-percentile, very 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 87.5% of Florence'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 Florence's figures come from
Florence's 82nd-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 Florence's dominant indirect exposure actually means, with real examples from across the dataset.