Ortonville, MI
Ortonville, MI's wildfire risk, in USFS's own numbers
USFS's Wildfire Risk to Communities model puts Ortonville at the 21st national percentile for risk to structures, close to the middle of USFS's national wildfire-risk range — a score built from 660 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Ortonville at the 23rd national percentile — 1 points above its risk-to-structures score, a gap driven by how much is actually built there.
Ortonville's building exposure, zone by zone
USFS puts 56.8% of Ortonville's 660 buildings in the Indirect exposure zone, versus 43.2% Direct and 0% Minimal — a place where the fire doesn't need to reach the structure directly for embers to.
How Ortonville compares
Ortonville's 69th-percentile standing inside Michigan outpaces its 21st 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, Ortonville ranks 24,835 for wildfire risk (1 is highest) and 15,060 by building count (1 is largest). Within Michigan alone, it ranks 232 of 745 places by risk. See the full county-by-county picture for Michigan on its state page.
Ortonville and the insurance market
At the 21st national percentile, Ortonville rates moderate for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
What would actually reduce this score
Ortonville's 56.8% Indirect-exposure share points at embers, not flame contact, as the main pathway — ember-resistant vents and non-combustible roofing rank ahead of defensible space here. Detail in the home-hardening guide.
Where Ortonville's figures come from
The methodology guide shows exactly how USFS turned 660 counted buildings into the percentiles shown above for Ortonville. The exposure-zones guide covers what Ortonville's dominant indirect exposure actually means, with real examples from across the dataset.