Dearborn, MI
Dearborn wildfire risk explained
Dearborn's 44,180 buildings earn a 6th-percentile wildfire-risk score nationally under USFS's model — among the lower wildfire-risk places nationally. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Dearborn's burn probability — fire likelihood with no building count factored in — sits at the 8th percentile nationally.
Where Dearborn's buildings actually sit
USFS classifies 99% of Dearborn's buildings as Minimal exposure, the largest of the three zones here by a wide margin over 1% Direct and 0% Indirect — a landscape-level risk rather than a building-by-building one. At 44,180 buildings, this is a substantial built environment, so the shares below describe a real population of structures, not a handful of edge cases.
Where Dearborn ranks
There's little gap between Dearborn's 6th national percentile and its 17th percentile inside Michigan, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Dearborn ranks 29,536 for wildfire risk (1 is highest) and 209 by building count (1 is largest). Within Michigan alone, it ranks 618 of 745 places by risk. See the full county-by-county picture for Michigan on its state page.
Shopping for coverage in Dearborn
At the 6th national percentile, Dearborn rates low 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 99% of buildings rated Minimal exposure, Dearborn gets less benefit from structure hardening than a Direct- or Indirect-dominant place would — the home-hardening guide explains why the zone matters.
Where Dearborn's figures come from
Dearborn's 6th-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 Dearborn's dominant minimal exposure actually means, with real examples from across the dataset.