Cannonsburg, MI
Cannonsburg, MI's wildfire risk, in USFS's own numbers
USFS scores Cannonsburg at the 25th national percentile for wildfire risk to structures (close to the middle of USFS's national wildfire-risk range), a figure built from 146 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Cannonsburg at the 26th national percentile — 1 points above its risk-to-structures score, a gap driven by how much is actually built there.
Cannonsburg's building exposure, zone by zone
Of Cannonsburg's 146 counted buildings, 86.3% carry Direct exposure and only 0% carry Minimal — a lopsided split that puts defensible-space clearing ahead of vents or roofing as the intervention worth doing first.
Where Cannonsburg ranks
Compare Cannonsburg's two percentiles: 75th within Michigan, only 25th nationally — a gap of 51 points that marks it as unusually exposed for its own state. Among the 31,521 US communities USFS scores, Cannonsburg ranks 23,763 for wildfire risk (1 is highest) and 27,024 by building count (1 is largest). Within Michigan alone, it ranks 186 of 745 places by risk. See the full county-by-county picture for Michigan on its state page.
Cannonsburg and the insurance market
Cannonsburg's moderate wildfire rating (25th 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.
What would actually reduce this score
Cannonsburg's 86.3% 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 Cannonsburg's figures come from
Cannonsburg's 25th-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 Cannonsburg's dominant direct exposure actually means, with real examples from across the dataset.