WildfireRiskFinder

Tracy, MN

Tracy wildfire risk explained

Low
11thpercentile nationally

Out of every US place USFS scores, Tracy lands at the 11th percentile for wildfire risk to structures — among the lower wildfire-risk places nationally — a figure built from its 1,236 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 Tracy at the 8th percentile, close to its 11th-percentile risk score.

Where Tracy's buildings actually sit

1,236Total buildings
14.3%Direct exposure
0%Indirect exposure
85.7%Minimal exposure

85.7% of Tracy's 1,236 buildings sit in USFS's Minimal exposure zone, with only 14.3% rated Direct — risk here comes from regional burn probability more than proximity to burnable vegetation at the structure itself.

Where Tracy ranks

There's little gap between Tracy's 11th national percentile and its 14th percentile inside Minnesota, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Tracy ranks 28,087 for wildfire risk (1 is highest) and 10,434 by building count (1 is largest). Within Minnesota alone, it ranks 782 of 914 places by risk. See the full county-by-county picture for Minnesota on its state page.

Shopping for coverage in Tracy

At the 11th national percentile, Tracy 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

Tracy's 85.7% 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 Tracy's figures come from

The methodology guide shows exactly how USFS turned 1,236 counted buildings into the percentiles shown above for Tracy. The exposure-zones guide covers what Tracy's dominant minimal exposure actually means, with real examples from across the dataset.