WildfireRiskFinder

Vineland, CO

Vineland wildfire risk explained

Elevated
58thpercentile nationally

Out of every US place USFS scores, Vineland lands at the 58th percentile for wildfire risk to structures — modestly above the national average for wildfire risk — a figure built from its 332 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)

Separately from the risk score above, Vineland's burn probability — fire likelihood with no building count factored in — sits at the 58th percentile nationally.

Where Vineland's buildings actually sit

332Total buildings
24.4%Direct exposure
75.6%Indirect exposure
0%Minimal exposure

332 buildings are counted in Vineland, and 75.6% of them are Indirect exposure — ember-driven risk rather than the 24.4% in Direct exposure or the 0% rated Minimal.

How Vineland compares

Inside Colorado, Vineland sits at just the 27th percentile even though it scores 58th nationally — the state's overall wildfire exposure is high enough to make this a relatively quiet corner of it. Among the 31,521 US communities USFS scores, Vineland ranks 13,102 for wildfire risk (1 is highest) and 20,749 by building count (1 is largest). Within Colorado alone, it ranks 343 of 472 places by risk. See the full county-by-county picture for Colorado on its state page.

What this risk score means for insurance

At the 58th national percentile, Vineland 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 Vineland (75.6% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.

Where Vineland's figures come from

The methodology guide shows exactly how USFS turned 332 counted buildings into the percentiles shown above for Vineland. The exposure-zones guide covers what Vineland's dominant indirect exposure actually means, with real examples from across the dataset.