Parks, NE
Parks wildfire risk explained
Out of every US place USFS scores, Parks lands at the 79th percentile for wildfire risk to structures — well above the national norm for wildfire risk — a figure built from its 34 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Parks's burn probability — fire likelihood with no building count factored in — sits at the 76th percentile nationally.
Where Parks's buildings actually sit
34 buildings are counted in Parks, and 100% of them sit in USFS's Direct exposure zone — flame contact, not just ember cast, is the live possibility for most of them, against 0% rated Minimal.
Where Parks ranks
Parks's risk sits at a similar level relative to Nebraska (84th percentile statewide) as it does nationally (79th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Parks ranks 6,713 for wildfire risk (1 is highest) and 31,295 by building count (1 is largest). Within Nebraska alone, it ranks 94 of 583 places by risk. See the full county-by-county picture for Nebraska on its state page.
Shopping for coverage in Parks
Parks's 79th-percentile, 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.
Lowering exposure, not just insuring around it
With 100% of Parks 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 Parks's figures come from
Parks's 79th-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 Parks's dominant direct exposure actually means, with real examples from across the dataset.