Palermo, ND
Palermo, ND's wildfire risk, in USFS's own numbers
Palermo sits at the 66th percentile nationally for wildfire risk to structures — well above the national norm for wildfire risk — per USFS's Wildfire Risk to Communities model, built from its 155 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Palermo's burn probability — fire likelihood with no building count factored in — sits at the 64th percentile nationally.
Palermo's building exposure, zone by zone
USFS classifies 72.9% of Palermo's buildings as Direct exposure, higher than its 27.1% Indirect share and far above its 0% Minimal share — a profile where 113 structures sit close enough to vegetation that lot clearing matters most.
Where Palermo ranks
Compare Palermo's two percentiles: 84th within North Dakota, only 66th nationally — a gap of 18 points that marks it as unusually exposed for its own state. Among the 31,521 US communities USFS scores, Palermo ranks 10,691 for wildfire risk (1 is highest) and 26,674 by building count (1 is largest). Within North Dakota alone, it ranks 65 of 402 places by risk. See the full county-by-county picture for North Dakota on its state page.
Shopping for coverage in Palermo
Palermo's 66th-percentile, high rating is the kind of score behind a broader national pattern: insurers pulling back from the highest wildfire-risk markets, non-renewing or declining new policies outright, most visibly in California. Shopping around, not assuming automatic renewal, tends to matter here.
Hardening a home in Palermo
Because Direct exposure dominates in Palermo (72.9%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.
Where Palermo's figures come from
Every one of the two percentiles behind Palermo's 10,691-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Palermo's dominant direct exposure actually means, with real examples from across the dataset.