Plainfield, OH
How exposed is Plainfield to wildfire?
USFS's Wildfire Risk to Communities model puts Plainfield at the 38th national percentile for risk to structures, close to the middle of USFS's national wildfire-risk range — a score built from 132 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Plainfield's burn probability — fire likelihood with no building count factored in — sits at the 40th percentile nationally.
What "at risk" means for the buildings here
Most of Plainfield's buildings (58.3%) sit in the Indirect zone, where wind-blown embers rather than flame front are the mechanism USFS is scoring — ember-resistant vents and non-combustible roofing are the interventions this pattern favors, more than defensible space alone.
How Plainfield compares
Plainfield's 84th-percentile standing inside Ohio outpaces its 38th 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, Plainfield ranks 19,422 for wildfire risk (1 is highest) and 27,640 by building count (1 is largest). Within Ohio alone, it ranks 207 of 1,264 places by risk. See the full county-by-county picture for Ohio on its state page.
What this risk score means for insurance
Plainfield's moderate wildfire rating (38th 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 Plainfield
Because 58.3% of Plainfield'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 Plainfield's figures come from
The methodology guide shows exactly how USFS turned 132 counted buildings into the percentiles shown above for Plainfield. The exposure-zones guide covers what Plainfield's dominant indirect exposure actually means, with real examples from across the dataset.