Regent, ND
Regent, ND's wildfire risk, in USFS's own numbers
Regent sits at the 44th 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 256 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Regent at the 42nd percentile, close to its 44th-percentile risk score.
What "at risk" means for the buildings here
81.3% of Regent's 256 buildings fall in USFS's Indirect exposure zone — ember cast rather than direct flame — against 18.8% Direct and 0% Minimal. Vent screens and roofing material matter more here than lot clearing alone.
Regent against the rest of the country
Regent scores 44th nationally and 35th within North Dakota — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, Regent ranks 17,659 for wildfire risk (1 is highest) and 22,951 by building count (1 is largest). Within North Dakota alone, it ranks 262 of 402 places by risk. See the full county-by-county picture for North Dakota on its state page.
Shopping for coverage in Regent
At the 44th national percentile, Regent 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
Regent's 81.3% Indirect-exposure share points at embers, not flame contact, as the main pathway — ember-resistant vents and non-combustible roofing rank ahead of defensible space here. Detail in the home-hardening guide.
Where Regent's figures come from
The methodology guide shows exactly how USFS turned 256 counted buildings into the percentiles shown above for Regent. The exposure-zones guide covers what Regent's dominant indirect exposure actually means, with real examples from across the dataset.