WildfireRiskFinder

Coloma, MI

Coloma, MI's wildfire risk, in USFS's own numbers

Low
8thpercentile nationally

USFS scores Coloma at the 8th national percentile for wildfire risk to structures (among the lower wildfire-risk places nationally), a figure built from 806 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)

Separately from the risk score above, Coloma's burn probability — fire likelihood with no building count factored in — sits at the 8th percentile nationally.

Where Coloma's buildings actually sit

806Total buildings
16.4%Direct exposure
0%Indirect exposure
83.6%Minimal exposure

Most of Coloma's buildings (83.6% of 806) fall outside USFS's Direct and Indirect zones entirely — that doesn't zero out the score above, it means the risk is regional, not structure-by-structure.

How Coloma compares

Coloma's 23rd-percentile standing inside Michigan outpaces its 8th national percentile — this is a hotter spot than most of its own state, even though the state as a whole runs cooler nationally. Among the 31,521 US communities USFS scores, Coloma ranks 29,092 for wildfire risk (1 is highest) and 13,582 by building count (1 is largest). Within Michigan alone, it ranks 573 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 8th national percentile, Coloma rates low for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.

Hardening a home in Coloma

Coloma's 83.6% Minimal-exposure share means structure-level hardening matters less here than it would elsewhere — still worth the low-cost basics, per the home-hardening guide.

Where Coloma's figures come from

Coloma's 8th-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 Coloma's dominant minimal exposure actually means, with real examples from across the dataset.