Hemphill, TX
Hemphill, TX's wildfire risk, in USFS's own numbers
USFS's Wildfire Risk to Communities model puts Hemphill at the 76th national percentile for risk to structures, well above the national norm for wildfire risk — a score built from 896 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Hemphill's burn probability — fire likelihood with no building count factored in — sits at the 77th percentile nationally.
Where Hemphill's buildings actually sit
Direct exposure dominates in Hemphill: 68.9% of its 896 buildings, versus 31.1% Indirect and 0% Minimal. Clearing space around a structure changes the outcome here more than any single building-material swap.
Where Hemphill ranks
Hemphill ranks lower within Texas (50th percentile statewide) than its 76th national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Hemphill ranks 7,481 for wildfire risk (1 is highest) and 12,765 by building count (1 is largest). Within Texas alone, it ranks 898 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
Hemphill's 76th-percentile, high rating is the kind of score behind a broader national pattern: insurers pulling back from the highest wildfire-risk markets, non-renewing or declining new policies outright, most visibly in California. Shopping around, not assuming automatic renewal, tends to matter here.
Lowering exposure, not just insuring around it
Hemphill's 68.9% 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 Hemphill's figures come from
The methodology guide shows exactly how USFS turned 896 counted buildings into the percentiles shown above for Hemphill. The exposure-zones guide covers what Hemphill's dominant direct exposure actually means, with real examples from across the dataset.