New Carlisle, OH
New Carlisle wildfire risk explained
USFS scores New Carlisle at the 12th national percentile for wildfire risk to structures (among the lower wildfire-risk places nationally), a figure built from 2,656 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, New Carlisle's burn probability — fire likelihood with no building count factored in — sits at the 13th percentile nationally.
Where New Carlisle's buildings actually sit
94.2% of New Carlisle's 2,656 buildings sit in USFS's Minimal exposure zone, with only 5.8% rated Direct — risk here comes from regional burn probability more than proximity to burnable vegetation at the structure itself.
How New Carlisle compares
Within Ohio, New Carlisle ranks higher (36th percentile) than it does nationally (12th) — one of the more fire-exposed places in a state that, overall, scores lower than that. Among the 31,521 US communities USFS scores, New Carlisle ranks 27,748 for wildfire risk (1 is highest) and 6,010 by building count (1 is largest). Within Ohio alone, it ranks 804 of 1,264 places by risk. See the full county-by-county picture for Ohio on its state page.
New Carlisle and the insurance market
New Carlisle's low wildfire rating (12th 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.
Lowering exposure, not just insuring around it
With 94.2% of buildings rated Minimal exposure, New Carlisle gets less benefit from structure hardening than a Direct- or Indirect-dominant place would — the home-hardening guide explains why the zone matters.
Where New Carlisle's figures come from
Every one of the two percentiles behind New Carlisle's 27,748-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what New Carlisle's dominant minimal exposure actually means, with real examples from across the dataset.