Lake Linden, MI
Lake Linden, MI's wildfire risk, in USFS's own numbers
Lake Linden sits at the 46th 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 669 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Lake Linden's burn probability — fire likelihood with no building count factored in — sits at the 48th percentile nationally.
Where Lake Linden's buildings actually sit
USFS puts 94.5% of Lake Linden's 669 buildings in the Indirect exposure zone, versus 5.5% Direct and 0% Minimal — a place where the fire doesn't need to reach the structure directly for embers to.
Lake Linden against the rest of the country
Within Michigan, Lake Linden ranks higher (94th percentile) than it does nationally (46th) — one of the more fire-exposed places in a state that, overall, scores lower than that. Among the 31,521 US communities USFS scores, Lake Linden ranks 17,172 for wildfire risk (1 is highest) and 14,973 by building count (1 is largest). Within Michigan alone, it ranks 49 of 745 places by risk. See the full county-by-county picture for Michigan on its state page.
What this risk score means for insurance
At the 46th national percentile, Lake Linden 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
With ember exposure the dominant pattern in Lake Linden (94.5% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.
Where Lake Linden's figures come from
Lake Linden's 46th-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 Lake Linden's dominant indirect exposure actually means, with real examples from across the dataset.