Depauw, IN
Depauw wildfire risk explained
Depauw sits at the 27th percentile nationally for wildfire risk to structures — close to the middle of USFS's national wildfire-risk range — per USFS's Wildfire Risk to Communities model, built from its 115 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Depauw at the 29th percentile, close to its 27th-percentile risk score.
Depauw's building exposure, zone by zone
83.5% of Depauw's 115 buildings sit in USFS's Direct exposure zone, roughly 96 structures close enough to burnable vegetation for flame contact, not just embers — 16.5% fall in the Indirect, ember-only zone and 0% are Minimal.
Depauw against the rest of the country
Within Indiana, Depauw ranks higher (93rd percentile) than it does nationally (27th) — one of the more fire-exposed places in a state that, overall, scores lower than that. Among the 31,521 US communities USFS scores, Depauw ranks 23,035 for wildfire risk (1 is highest) and 28,406 by building count (1 is largest). Within Indiana alone, it ranks 73 of 967 places by risk. See the full county-by-county picture for Indiana on its state page.
Depauw and the insurance market
Depauw's moderate rating (27th 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
With 83.5% of Depauw in Direct exposure, defensible-space clearing and ember-resistant construction (vents, Class-A roofing) address the exposure this page's own numbers describe, not a generic checklist. See the home-hardening guide.
Where Depauw's figures come from
Every one of the two percentiles behind Depauw's 23,035-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Depauw's dominant direct exposure actually means, with real examples from across the dataset.