Georgetown, IN
Georgetown, IN's wildfire risk, in USFS's own numbers
Out of every US place USFS scores, Georgetown lands at the 24th percentile for wildfire risk to structures — close to the middle of USFS's national wildfire-risk range — a figure built from its 1,716 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Georgetown's burn probability — fire likelihood with no building count factored in — sits at the 26th percentile nationally.
What "at risk" means for the buildings here
75.6% of Georgetown's 1,716 buildings sit in USFS's Direct exposure zone, roughly 1,297 structures close enough to burnable vegetation for flame contact, not just embers — 24.4% fall in the Indirect, ember-only zone and 0% are Minimal.
How Georgetown compares
Compare Georgetown's two percentiles: 90th within Indiana, only 24th nationally — a gap of 66 points that marks it as unusually exposed for its own state. Among the 31,521 US communities USFS scores, Georgetown ranks 23,824 for wildfire risk (1 is highest) and 8,364 by building count (1 is largest). Within Indiana alone, it ranks 96 of 967 places by risk. See the full county-by-county picture for Indiana on its state page.
Georgetown and the insurance market
At the 24th national percentile, Georgetown rates moderate for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
What would actually reduce this score
With 75.6% of Georgetown 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 Georgetown's figures come from
Georgetown's 24th-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 Georgetown's dominant direct exposure actually means, with real examples from across the dataset.