Whiting, IA
Whiting, IA's wildfire risk, in USFS's own numbers
Whiting sits at the 41st percentile nationally for wildfire risk to structures — modestly above the national average for wildfire risk — per USFS's Wildfire Risk to Communities model, built from its 480 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Whiting's burn probability — fire likelihood with no building count factored in — sits at the 36th percentile nationally.
Whiting's building exposure, zone by zone
USFS classifies 83.8% of Whiting's buildings as Minimal exposure, the largest of the three zones here by a wide margin over 16.3% Direct and 0% Indirect — a landscape-level risk rather than a building-by-building one.
Where Whiting ranks
Whiting's 57th-percentile standing inside Iowa outpaces its 41st national percentile — this is a hotter spot than most of its own state, even though the state as a whole runs cooler nationally. Among the 31,521 US communities USFS scores, Whiting ranks 18,492 for wildfire risk (1 is highest) and 17,701 by building count (1 is largest). Within Iowa alone, it ranks 440 of 1,017 places by risk. See the full county-by-county picture for Iowa on its state page.
Whiting and the insurance market
At the 41st national percentile, Whiting rates elevated 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 83.8% of Whiting 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 Whiting's figures come from
Whiting's 41st-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 Whiting's dominant minimal exposure actually means, with real examples from across the dataset.