Knightstown, IN
Knightstown, IN's wildfire risk, in USFS's own numbers
USFS's Wildfire Risk to Communities model puts Knightstown at the 12th national percentile for risk to structures, among the lower wildfire-risk places nationally — a score built from 1,304 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Knightstown at the 11th percentile, close to its 12th-percentile risk score.
Knightstown's building exposure, zone by zone
USFS classifies 91.4% of Knightstown's buildings as Minimal exposure, the largest of the three zones here by a wide margin over 8.6% Direct and 0% Indirect — a landscape-level risk rather than a building-by-building one.
Where Knightstown ranks
Within Indiana, Knightstown ranks higher (61st 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, Knightstown ranks 27,729 for wildfire risk (1 is highest) and 10,060 by building count (1 is largest). Within Indiana alone, it ranks 375 of 967 places by risk. See the full county-by-county picture for Indiana on its state page.
Knightstown and the insurance market
Knightstown's low rating (12th percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.
Hardening a home in Knightstown
Even with 91.4% of Knightstown 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 Knightstown's figures come from
Every one of the two percentiles behind Knightstown's 27,729-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Knightstown's dominant minimal exposure actually means, with real examples from across the dataset.