Pittsburg, TX
Pittsburg, TX's wildfire risk, in USFS's own numbers
Pittsburg sits at the 78th percentile nationally for wildfire risk to structures — well above the national norm for wildfire risk — per USFS's Wildfire Risk to Communities model, built from its 2,306 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Pittsburg at the 80th percentile, close to its 78th-percentile risk score.
Where Pittsburg's buildings actually sit
USFS puts 88.7% of Pittsburg's 2,306 buildings in the Indirect exposure zone, versus 11.3% Direct and 0% Minimal — a place where the fire doesn't need to reach the structure directly for embers to.
Pittsburg against the rest of the country
Pittsburg ranks lower within Texas (57th percentile statewide) than its 78th national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Pittsburg ranks 6,853 for wildfire risk (1 is highest) and 6,688 by building count (1 is largest). Within Texas alone, it ranks 778 of 1,795 places by risk. See the full county-by-county picture for Texas on its state page.
Shopping for coverage in Pittsburg
Pittsburg's high rating (78th 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.
Hardening a home in Pittsburg
Pittsburg's 88.7% Indirect-exposure share points at embers, not flame contact, as the main pathway — ember-resistant vents and non-combustible roofing rank ahead of defensible space here. Detail in the home-hardening guide.
Where Pittsburg's figures come from
Every one of the two percentiles behind Pittsburg's 6,853-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Pittsburg's dominant indirect exposure actually means, with real examples from across the dataset.