WildfireRiskFinder

Diboll, TX

Diboll wildfire risk explained

High
72ndpercentile nationally

USFS scores Diboll at the 72nd national percentile for wildfire risk to structures (well above the national norm for wildfire risk), a figure built from 1,766 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)

Fire likelihood alone (USFS's burn-probability figure) ranks Diboll at the 74th national percentile — 1 points above its risk-to-structures score, a gap driven by how much is actually built there.

What "at risk" means for the buildings here

1,766Total buildings
24%Direct exposure
76.1%Indirect exposure
0%Minimal exposure

USFS puts 76.1% of Diboll's 1,766 buildings in the Indirect exposure zone, versus 24% Direct and 0% Minimal — a place where the fire doesn't need to reach the structure directly for embers to.

How Diboll compares

Diboll ranks lower within Texas (37th percentile statewide) than its 72nd national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Diboll ranks 8,742 for wildfire risk (1 is highest) and 8,175 by building count (1 is largest). Within Texas alone, it ranks 1,127 of 1,795 places by risk. See the full county-by-county picture for Texas on its state page.

What this risk score means for insurance

Diboll's high rating (72nd 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

With ember exposure the dominant pattern in Diboll (76.1% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.

Where Diboll's figures come from

Diboll's 72nd-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 Diboll's dominant indirect exposure actually means, with real examples from across the dataset.