Green Mountain, IA
Green Mountain wildfire risk explained
USFS's Wildfire Risk to Communities model puts Green Mountain at the 35th national percentile for risk to structures, close to the middle of USFS's national wildfire-risk range — a score built from 139 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Green Mountain at the 35th percentile, close to its 35th-percentile risk score.
Green Mountain's building exposure, zone by zone
Most of Green Mountain's buildings (66.9% of 139) fall outside USFS's Direct and Indirect zones entirely — that doesn't zero out the score above, it means the risk is regional, not structure-by-structure.
Green Mountain against the rest of the country
Green Mountain's risk sits at a similar level relative to Iowa (49th percentile statewide) as it does nationally (35th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Green Mountain ranks 20,605 for wildfire risk (1 is highest) and 27,323 by building count (1 is largest). Within Iowa alone, it ranks 516 of 1,017 places by risk. See the full county-by-county picture for Iowa on its state page.
What this risk score means for insurance
Green Mountain's moderate rating (35th percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.
What would actually reduce this score
With 66.9% of buildings rated Minimal exposure, Green Mountain gets less benefit from structure hardening than a Direct- or Indirect-dominant place would — the home-hardening guide explains why the zone matters.
Where Green Mountain's figures come from
Every one of the two percentiles behind Green Mountain's 20,605-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Green Mountain's dominant minimal exposure actually means, with real examples from across the dataset.