Lidgerwood, ND
How exposed is Lidgerwood to wildfire?
USFS's Wildfire Risk to Communities model puts Lidgerwood at the 49th national percentile for risk to structures, modestly above the national average for wildfire risk — a score built from 638 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Lidgerwood's burn probability — fire likelihood with no building count factored in — sits at the 46th percentile nationally.
Lidgerwood's building exposure, zone by zone
87.8% of Lidgerwood's 638 buildings fall in USFS's Indirect exposure zone — ember cast rather than direct flame — against 12.2% Direct and 0% Minimal. Vent screens and roofing material matter more here than lot clearing alone.
Lidgerwood against the rest of the country
Lidgerwood's risk sits at a similar level relative to North Dakota (48th percentile statewide) as it does nationally (49th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Lidgerwood ranks 16,146 for wildfire risk (1 is highest) and 15,367 by building count (1 is largest). Within North Dakota alone, it ranks 208 of 402 places by risk. See the full county-by-county picture for North Dakota on its state page.
What this risk score means for insurance
Lidgerwood's elevated rating (49th percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.
Lowering exposure, not just insuring around it
Lidgerwood's 87.8% 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 Lidgerwood's figures come from
Lidgerwood's 49th-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 Lidgerwood's dominant indirect exposure actually means, with real examples from across the dataset.