WildfireRiskFinder

Bagtown, MD

How exposed is Bagtown to wildfire?

High
63rdpercentile nationally

USFS's Wildfire Risk to Communities model puts Bagtown at the 63rd national percentile for risk to structures, well above the national norm for wildfire risk — a score built from 194 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)

USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Bagtown at the 59th percentile, close to its 63rd-percentile risk score.

Bagtown's building exposure, zone by zone

194Total buildings
100%Direct exposure
0%Indirect exposure
0%Minimal exposure

Of Bagtown's 194 counted buildings, 100% carry Direct exposure and only 0% carry Minimal — a lopsided split that puts defensible-space clearing ahead of vents or roofing as the intervention worth doing first.

How Bagtown compares

Within Maryland, Bagtown ranks higher (89th percentile) than it does nationally (63rd) — one of the more fire-exposed places in a state that, overall, scores lower than that. Among the 31,521 US communities USFS scores, Bagtown ranks 11,568 for wildfire risk (1 is highest) and 25,078 by building count (1 is largest). Within Maryland alone, it ranks 60 of 527 places by risk. See the full county-by-county picture for Maryland on its state page.

Shopping for coverage in Bagtown

Bagtown's high rating (63rd percentile) puts it among the places where the national carrier-pullback trend is most relevant — not a guarantee of a coverage problem, but a reason to shop rather than assume.

What would actually reduce this score

Bagtown's 100% 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 Bagtown's figures come from

The methodology guide shows exactly how USFS turned 194 counted buildings into the percentiles shown above for Bagtown. The exposure-zones guide covers what Bagtown's dominant direct exposure actually means, with real examples from across the dataset.