Lake Victoria, MI
Lake Victoria wildfire risk explained
Out of every US place USFS scores, Lake Victoria lands at the 13th percentile for wildfire risk to structures — among the lower wildfire-risk places nationally — a figure built from its 425 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Lake Victoria at the 14th percentile, close to its 13th-percentile risk score.
Lake Victoria's building exposure, zone by zone
USFS classifies 62.8% of Lake Victoria's buildings as Direct exposure, higher than its 24% Indirect share and far above its 13.2% Minimal share — a profile where 267 structures sit close enough to vegetation that lot clearing matters most.
Where Lake Victoria ranks
Within Michigan, Lake Victoria ranks higher (45th percentile) than it does nationally (13th) — 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 Victoria ranks 27,422 for wildfire risk (1 is highest) and 18,748 by building count (1 is largest). Within Michigan alone, it ranks 410 of 745 places by risk. See the full county-by-county picture for Michigan on its state page.
Lake Victoria and the insurance market
Lake Victoria's low rating (13th 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
Lake Victoria's 62.8% Direct-exposure share means lot clearing around the structure typically outweighs any single material upgrade here. The home-hardening guide ranks the options for a place shaped like this.
Where Lake Victoria's figures come from
Lake Victoria's 13th-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 Victoria's dominant direct exposure actually means, with real examples from across the dataset.