Judah, IN
Judah wildfire risk explained
Judah sits at the 22nd 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 328 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 Judah at the 23rd percentile, close to its 22nd-percentile risk score.
What "at risk" means for the buildings here
USFS classifies 100% of Judah's buildings as Direct exposure, higher than its 0% Indirect share and far above its 0% Minimal share — a profile where 328 structures sit close enough to vegetation that lot clearing matters most.
Judah against the rest of the country
Within Indiana, Judah ranks higher (85th percentile) than it does nationally (22nd) — one of the more fire-exposed places in a state that, overall, scores lower than that. Among the 31,521 US communities USFS scores, Judah ranks 24,673 for wildfire risk (1 is highest) and 20,870 by building count (1 is largest). Within Indiana alone, it ranks 147 of 967 places by risk. See the full county-by-county picture for Indiana on its state page.
Shopping for coverage in Judah
Judah's moderate wildfire rating (22nd 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.
Lowering exposure, not just insuring around it
Because Direct exposure dominates in Judah (100%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.
Where Judah's figures come from
Every one of the two percentiles behind Judah's 24,673-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Judah's dominant direct exposure actually means, with real examples from across the dataset.