Jackson, NE
How exposed is Jackson to wildfire?
Jackson sits at the 84th percentile nationally for wildfire risk to structures — in USFS's highest wildfire-risk band nationally — per USFS's Wildfire Risk to Communities model, built from its 160 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Jackson's burn probability — fire likelihood with no building count factored in — sits at the 80th percentile nationally.
What "at risk" means for the buildings here
Only 23.1% of Jackson's 160 buildings carry Direct exposure and 1.9% carry Indirect; the remaining 75% are Minimal, which shifts the risk driving this page's score toward the surrounding landscape rather than any one structure.
Where Jackson ranks
Jackson scores 84th nationally and 92nd within Nebraska — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, Jackson ranks 5,018 for wildfire risk (1 is highest) and 26,439 by building count (1 is largest). Within Nebraska alone, it ranks 49 of 583 places by risk. See the full county-by-county picture for Nebraska on its state page.
Jackson and the insurance market
Jackson's 84th-percentile, very high rating is the kind of score behind a broader national pattern: insurers pulling back from the highest wildfire-risk markets, non-renewing or declining new policies outright, most visibly in California. Shopping around, not assuming automatic renewal, tends to matter here.
What would actually reduce this score
With 75% of buildings rated Minimal exposure, Jackson gets less benefit from structure hardening than a Direct- or Indirect-dominant place would — the home-hardening guide explains why the zone matters.
Where Jackson's figures come from
Jackson's 84th-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 Jackson's dominant minimal exposure actually means, with real examples from across the dataset.