Troy, IN
Troy, IN's wildfire risk, in USFS's own numbers
USFS's Wildfire Risk to Communities model puts Troy at the 31st national percentile for risk to structures, close to the middle of USFS's national wildfire-risk range — a score built from 304 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Troy at the 33rd national percentile — 2 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
Most of Troy's buildings (59.5%) sit in the Indirect zone, where wind-blown embers rather than flame front are the mechanism USFS is scoring — ember-resistant vents and non-combustible roofing are the interventions this pattern favors, more than defensible space alone.
Where Troy ranks
Troy's 94th-percentile standing inside Indiana outpaces its 31st national percentile — this is a hotter spot than most of its own state, even though the state as a whole runs cooler nationally. Among the 31,521 US communities USFS scores, Troy ranks 21,769 for wildfire risk (1 is highest) and 21,519 by building count (1 is largest). Within Indiana alone, it ranks 63 of 967 places by risk. See the full county-by-county picture for Indiana on its state page.
Shopping for coverage in Troy
Troy's moderate rating (31st 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
Troy's 59.5% 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 Troy's figures come from
The methodology guide shows exactly how USFS turned 304 counted buildings into the percentiles shown above for Troy. The exposure-zones guide covers what Troy's dominant indirect exposure actually means, with real examples from across the dataset.