WildfireRiskFinder

Princeton, IA

Princeton wildfire risk explained

Elevated
48thpercentile nationally

Princeton's 604 buildings earn a 48th-percentile wildfire-risk score nationally under USFS's model — modestly above the national average for wildfire risk. (Source: USFS's Wildfire Risk to Communities methodology.)

Separately from the risk score above, Princeton's burn probability — fire likelihood with no building count factored in — sits at the 49th percentile nationally.

Where Princeton's buildings actually sit

604Total buildings
32.3%Direct exposure
65.9%Indirect exposure
1.8%Minimal exposure

Indirect exposure is dominant in Princeton (65.9% of 604 buildings): far enough from burnable vegetation to avoid flame contact, close enough for wind-blown embers. Only 32.3% sit in the Direct zone.

Where Princeton ranks

Compare Princeton's two percentiles: 66th within Iowa, only 48th nationally — a gap of 18 points that marks it as unusually exposed for its own state. Among the 31,521 US communities USFS scores, Princeton ranks 16,384 for wildfire risk (1 is highest) and 15,787 by building count (1 is largest). Within Iowa alone, it ranks 345 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

At the 48th national percentile, Princeton 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

With ember exposure the dominant pattern in Princeton (65.9% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.

Where Princeton's figures come from

Every one of the two percentiles behind Princeton's 16,384-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Princeton's dominant indirect exposure actually means, with real examples from across the dataset.