Van Meter, IA
How exposed is Van Meter to wildfire?
Out of every US place USFS scores, Van Meter lands at the 55th percentile for wildfire risk to structures — modestly above the national average for wildfire risk — a figure built from its 642 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Van Meter at the 57th national percentile — 2 points above its risk-to-structures score, a gap driven by how much is actually built there.
Van Meter's building exposure, zone by zone
Only 29.1% of Van Meter's 642 buildings carry Direct exposure and 0% carry Indirect; the remaining 70.9% are Minimal, which shifts the risk driving this page's score toward the surrounding landscape rather than any one structure.
Van Meter against the rest of the country
Within Iowa, Van Meter ranks higher (75th percentile) than it does nationally (55th) — one of the more fire-exposed places in a state that, overall, scores lower than that. Among the 31,521 US communities USFS scores, Van Meter ranks 14,114 for wildfire risk (1 is highest) and 15,292 by building count (1 is largest). Within Iowa alone, it ranks 251 of 1,017 places by risk. See the full county-by-county picture for Iowa on its state page.
Shopping for coverage in Van Meter
Van Meter's elevated wildfire rating (55th percentile) isn't the kind of score driving the carrier pullback making news in the highest-risk Western markets — but a standard homeowners quote is still worth comparing on its own terms.
What would actually reduce this score
With 70.9% of buildings rated Minimal exposure, Van Meter gets less benefit from structure hardening than a Direct- or Indirect-dominant place would — the home-hardening guide explains why the zone matters.
Where Van Meter's figures come from
The methodology guide shows exactly how USFS turned 642 counted buildings into the percentiles shown above for Van Meter. The exposure-zones guide covers what Van Meter's dominant minimal exposure actually means, with real examples from across the dataset.