Atalissa, IA
Atalissa wildfire risk explained
Atalissa sits at the 21st 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 217 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Atalissa at the 19th national percentile — 2 points below its risk-to-structures score, a gap driven by how much is actually built there.
Atalissa's building exposure, zone by zone
Only 12% of Atalissa's 217 buildings carry Direct exposure and 0% carry Indirect; the remaining 88% are Minimal, which shifts the risk driving this page's score toward the surrounding landscape rather than any one structure.
Where Atalissa ranks
Atalissa's risk sits at a similar level relative to Iowa (34th percentile statewide) as it does nationally (21st) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Atalissa ranks 24,958 for wildfire risk (1 is highest) and 24,231 by building count (1 is largest). Within Iowa alone, it ranks 674 of 1,017 places by risk. See the full county-by-county picture for Iowa on its state page.
Shopping for coverage in Atalissa
At the 21st national percentile, Atalissa 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
Even with 88% of Atalissa outside USFS's Direct and Indirect zones, basic hardening — gutter maintenance, ember-resistant vents — is inexpensive relative to the regional burn-probability risk noted above. Details in the home-hardening guide.
Where Atalissa's figures come from
Atalissa's 21st-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 Atalissa's dominant minimal exposure actually means, with real examples from across the dataset.