South Salem, OH
South Salem wildfire risk explained
USFS scores South Salem at the 27th national percentile for wildfire risk to structures (close to the middle of USFS's national wildfire-risk range), a figure built from 145 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks South Salem at the 30th national percentile — 3 points above its risk-to-structures score, a gap driven by how much is actually built there.
South Salem's building exposure, zone by zone
USFS puts 51% of South Salem's 145 buildings in the Indirect exposure zone, versus 49% Direct and 0% Minimal — a place where the fire doesn't need to reach the structure directly for embers to.
How South Salem compares
Within Ohio, South Salem ranks higher (61st percentile) than it does nationally (27th) — one of the more fire-exposed places in a state that, overall, scores lower than that. Among the 31,521 US communities USFS scores, South Salem ranks 22,894 for wildfire risk (1 is highest) and 27,095 by building count (1 is largest). Within Ohio alone, it ranks 499 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
South Salem's moderate rating (27th percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.
Lowering exposure, not just insuring around it
South Salem's 51% 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 South Salem's figures come from
Every one of the two percentiles behind South Salem's 22,894-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what South Salem's dominant indirect exposure actually means, with real examples from across the dataset.