Putnamville, IN
Putnamville, IN's wildfire risk, in USFS's own numbers
Putnamville sits at the 18th percentile nationally for wildfire risk to structures — among the lower wildfire-risk places nationally — per USFS's Wildfire Risk to Communities model, built from its 237 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Putnamville's burn probability — fire likelihood with no building count factored in — sits at the 18th percentile nationally.
Where Putnamville's buildings actually sit
USFS classifies 58.2% of Putnamville's buildings as Direct exposure, higher than its 41.8% Indirect share and far above its 0% Minimal share — a profile where 138 structures sit close enough to vegetation that lot clearing matters most.
Where Putnamville ranks
Compare Putnamville's two percentiles: 73rd within Indiana, only 18th nationally — a gap of 56 points that marks it as unusually exposed for its own state. Among the 31,521 US communities USFS scores, Putnamville ranks 26,000 for wildfire risk (1 is highest) and 23,553 by building count (1 is largest). Within Indiana alone, it ranks 259 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
Putnamville's low wildfire rating (18th 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.
Hardening a home in Putnamville
Putnamville's 58.2% 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 Putnamville's figures come from
Putnamville's 18th-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 Putnamville's dominant direct exposure actually means, with real examples from across the dataset.