Solsberry, IN
Solsberry wildfire risk explained
Out of every US place USFS scores, Solsberry lands at the 21st percentile for wildfire risk to structures — close to the middle of USFS's national wildfire-risk range — a figure built from its 170 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Solsberry at the 22nd national percentile — 1 points above its risk-to-structures score, a gap driven by how much is actually built there.
What "at risk" means for the buildings here
USFS classifies 100% of Solsberry's buildings as Direct exposure, higher than its 0% Indirect share and far above its 0% Minimal share — a profile where 170 structures sit close enough to vegetation that lot clearing matters most.
How Solsberry compares
Compare Solsberry's two percentiles: 82nd within Indiana, only 21st nationally — a gap of 61 points that marks it as unusually exposed for its own state. Among the 31,521 US communities USFS scores, Solsberry ranks 25,054 for wildfire risk (1 is highest) and 26,019 by building count (1 is largest). Within Indiana alone, it ranks 181 of 967 places by risk. See the full county-by-county picture for Indiana on its state page.
What this risk score means for insurance
Solsberry's moderate wildfire rating (21st 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.
What would actually reduce this score
Solsberry's 100% Direct-exposure share means lot clearing around the structure typically outweighs any single material upgrade here. The home-hardening guide ranks the options for a place shaped like this.
Where Solsberry's figures come from
Solsberry's 21st-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 Solsberry's dominant direct exposure actually means, with real examples from across the dataset.