Hartland, WI
Hartland wildfire risk explained
Hartland sits at the 32nd percentile nationally for wildfire risk to structures — close to the middle of USFS's national wildfire-risk range — per USFS's Wildfire Risk to Communities model, built from its 3,237 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Hartland at the 35th national percentile — 2 points above its risk-to-structures score, a gap driven by how much is actually built there.
Where Hartland's buildings actually sit
79.9% of Hartland's 3,237 buildings sit in USFS's Minimal exposure zone, with only 20% rated Direct — risk here comes from regional burn probability more than proximity to burnable vegetation at the structure itself.
Hartland against the rest of the country
Within Wisconsin, Hartland ranks higher (73rd percentile) than it does nationally (32nd) — one of the more fire-exposed places in a state that, overall, scores lower than that. Among the 31,521 US communities USFS scores, Hartland ranks 21,324 for wildfire risk (1 is highest) and 5,123 by building count (1 is largest). Within Wisconsin alone, it ranks 220 of 808 places by risk. See the full county-by-county picture for Wisconsin on its state page.
Shopping for coverage in Hartland
Hartland's moderate rating (32nd percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.
What would actually reduce this score
With 79.9% of buildings rated Minimal exposure, Hartland gets less benefit from structure hardening than a Direct- or Indirect-dominant place would — the home-hardening guide explains why the zone matters.
Where Hartland's figures come from
Hartland's 32nd-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 Hartland's dominant minimal exposure actually means, with real examples from across the dataset.