Canton, IN
Canton, IN's wildfire risk, in USFS's own numbers
Canton sits at the 10th percentile nationally for wildfire risk to structures — among the lower wildfire-risk places nationally — per USFS's Wildfire Risk to Communities model, built from its 133 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Canton at the 10th national percentile — 0 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 classifies 93.2% of Canton's buildings as Direct exposure, higher than its 0% Indirect share and far above its 6.8% Minimal share — a profile where 124 structures sit close enough to vegetation that lot clearing matters most.
Canton against the rest of the country
Canton's 55th-percentile standing inside Indiana outpaces its 10th national percentile — this is a hotter spot than most of its own state, even though the state as a whole runs cooler nationally. Among the 31,521 US communities USFS scores, Canton ranks 28,389 for wildfire risk (1 is highest) and 27,574 by building count (1 is largest). Within Indiana alone, it ranks 432 of 967 places by risk. See the full county-by-county picture for Indiana on its state page.
Canton and the insurance market
Canton's low wildfire rating (10th 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.
Hardening a home in Canton
Because Direct exposure dominates in Canton (93.2%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.
Where Canton's figures come from
Every one of the two percentiles behind Canton's 28,389-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Canton's dominant direct exposure actually means, with real examples from across the dataset.