Junction, TX
Junction, TX's wildfire risk, in USFS's own numbers
USFS scores Junction at the 72nd national percentile for wildfire risk to structures (well above the national norm for wildfire risk), a figure built from 1,841 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Junction at the 70th percentile, close to its 72nd-percentile risk score.
Junction's building exposure, zone by zone
81.8% of Junction's 1,841 buildings fall in USFS's Indirect exposure zone — ember cast rather than direct flame — against 18.3% Direct and 0% Minimal. Vent screens and roofing material matter more here than lot clearing alone.
Junction against the rest of the country
Junction 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, Junction ranks 8,837 for wildfire risk (1 is highest) and 7,950 by building count (1 is largest). Within Texas alone, it ranks 1,138 of 1,795 places by risk. See the full county-by-county picture for Texas on its state page.
Junction and the insurance market
Junction'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
Junction's 81.8% 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 Junction's figures come from
Every one of the two percentiles behind Junction's 8,837-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Junction's dominant indirect exposure actually means, with real examples from across the dataset.