Risingsun, OH
Risingsun, OH's wildfire risk, in USFS's own numbers
Out of every US place USFS scores, Risingsun lands at the 2nd percentile for wildfire risk to structures — among the lower wildfire-risk places nationally — a figure built from its 386 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Risingsun at the 2nd national percentile — 0 points below its risk-to-structures score, a gap driven by how much is actually built there.
Risingsun's building exposure, zone by zone
Only 5.4% of Risingsun's 386 buildings carry Direct exposure and 0% carry Indirect; the remaining 94.6% are Minimal, which shifts the risk driving this page's score toward the surrounding landscape rather than any one structure.
How Risingsun compares
There's little gap between Risingsun's 2nd national percentile and its 11th percentile inside Ohio, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Risingsun ranks 30,999 for wildfire risk (1 is highest) and 19,504 by building count (1 is largest). Within Ohio alone, it ranks 1,128 of 1,264 places by risk. See the full county-by-county picture for Ohio on its state page.
Shopping for coverage in Risingsun
Risingsun's low rating (2nd percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.
What would actually reduce this score
Even with 94.6% of Risingsun outside USFS's Direct and Indirect zones, basic hardening — gutter maintenance, ember-resistant vents — is inexpensive relative to the regional burn-probability risk noted above. Details in the home-hardening guide.
Where Risingsun's figures come from
Risingsun's 2nd-percentile score and its burn-probability figure both come from the same USFS workbook, documented in the methodology guide. The exposure-zones guide covers what Risingsun's dominant minimal exposure actually means, with real examples from across the dataset.