Canton, MS
Canton wildfire risk explained
USFS scores Canton at the 62nd national percentile for wildfire risk to structures (well above the national norm for wildfire risk), a figure built from 4,761 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Canton's burn probability — fire likelihood with no building count factored in — sits at the 65th percentile nationally.
Canton's building exposure, zone by zone
USFS classifies 44.8% of Canton's buildings as Direct exposure, higher than its 17.6% Indirect share and far above its 37.6% Minimal share — a profile where 2,131 structures sit close enough to vegetation that lot clearing matters most.
Where Canton ranks
Inside Mississippi, Canton sits at just the 37th percentile even though it scores 62nd 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, Canton ranks 12,069 for wildfire risk (1 is highest) and 3,583 by building count (1 is largest). Within Mississippi alone, it ranks 265 of 420 places by risk. See the full county-by-county picture for Mississippi on its state page.
What this risk score means for insurance
At the 62nd percentile nationally, Canton 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
Canton's 44.8% Direct-exposure share means lot clearing around the structure typically outweighs any single material upgrade here. The home-hardening guide ranks the options for a place shaped like this.
Where Canton's figures come from
Canton's 62nd-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 Canton's dominant direct exposure actually means, with real examples from across the dataset.