WildfireRiskFinder

Gratiot, OH

Gratiot, OH's wildfire risk, in USFS's own numbers

Moderate
39thpercentile nationally

Gratiot sits at the 39th percentile nationally for wildfire risk to structures — close to the middle of USFS's national wildfire-risk range — per USFS's Wildfire Risk to Communities model, built from its 143 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)

Separately from the risk score above, Gratiot's burn probability — fire likelihood with no building count factored in — sits at the 40th percentile nationally.

Where Gratiot's buildings actually sit

143Total buildings
27.3%Direct exposure
72.7%Indirect exposure
0%Minimal exposure

143 buildings are counted in Gratiot, and 72.7% of them are Indirect exposure — ember-driven risk rather than the 27.3% in Direct exposure or the 0% rated Minimal.

Gratiot against the rest of the country

Compare Gratiot's two percentiles: 86th within Ohio, only 39th nationally — a gap of 47 points that marks it as unusually exposed for its own state. Among the 31,521 US communities USFS scores, Gratiot ranks 19,142 for wildfire risk (1 is highest) and 27,173 by building count (1 is largest). Within Ohio alone, it ranks 182 of 1,264 places by risk. See the full county-by-county picture for Ohio on its state page.

Shopping for coverage in Gratiot

At the 39th national percentile, Gratiot rates moderate for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.

Lowering exposure, not just insuring around it

With ember exposure the dominant pattern in Gratiot (72.7% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.

Where Gratiot's figures come from

The methodology guide shows exactly how USFS turned 143 counted buildings into the percentiles shown above for Gratiot. The exposure-zones guide covers what Gratiot's dominant indirect exposure actually means, with real examples from across the dataset.