Inwood, IA
Inwood, IA's wildfire risk, in USFS's own numbers
USFS scores Inwood at the 22nd national percentile for wildfire risk to structures (close to the middle of USFS's national wildfire-risk range), a figure built from 509 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Inwood at the 18th percentile, close to its 22nd-percentile risk score.
Where Inwood's buildings actually sit
80.4% of Inwood's 509 buildings sit in USFS's Minimal exposure zone, with only 19.7% rated Direct — risk here comes from regional burn probability more than proximity to burnable vegetation at the structure itself.
Where Inwood ranks
There's little gap between Inwood's 22nd national percentile and its 35th percentile inside Iowa, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Inwood ranks 24,548 for wildfire risk (1 is highest) and 17,190 by building count (1 is largest). Within Iowa alone, it ranks 658 of 1,017 places by risk. See the full county-by-county picture for Iowa on its state page.
Inwood and the insurance market
At the 22nd national percentile, Inwood rates moderate for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
Lowering exposure, not just insuring around it
Even with 80.4% of Inwood 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 Inwood's figures come from
Every one of the two percentiles behind Inwood's 24,548-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Inwood's dominant minimal exposure actually means, with real examples from across the dataset.