WildfireRiskFinder

Marston, MO

Marston wildfire risk explained

Low
4thpercentile nationally

USFS scores Marston at the 4th national percentile for wildfire risk to structures (among the lower wildfire-risk places nationally), a figure built from 382 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)

Separately from the risk score above, Marston's burn probability — fire likelihood with no building count factored in — sits at the 3rd percentile nationally.

What "at risk" means for the buildings here

382Total buildings
28.5%Direct exposure
0%Indirect exposure
71.5%Minimal exposure

Marston rates 71.5% Minimal exposure against just 28.5% Direct and 0% Indirect — of 382 buildings counted, few sit close enough to burnable vegetation for USFS to flag them individually.

Marston against the rest of the country

Marston scores 4th nationally and 4th within Missouri — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, Marston ranks 30,422 for wildfire risk (1 is highest) and 19,595 by building count (1 is largest). Within Missouri alone, it ranks 1,023 of 1,062 places by risk. See the full county-by-county picture for Missouri on its state page.

What this risk score means for insurance

At the 4th national percentile, Marston 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

With 71.5% of buildings rated Minimal exposure, Marston gets less benefit from structure hardening than a Direct- or Indirect-dominant place would — the home-hardening guide explains why the zone matters.

Where Marston's figures come from

Marston's 4th-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 Marston's dominant minimal exposure actually means, with real examples from across the dataset.