South Point, TX
How exposed is South Point to wildfire?
South Point sits at the 66th 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 482 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, South Point's burn probability — fire likelihood with no building count factored in — sits at the 67th percentile nationally.
What "at risk" means for the buildings here
USFS classifies 74.9% of South Point's buildings as Direct exposure, higher than its 0% Indirect share and far above its 25.1% Minimal share — a profile where 361 structures sit close enough to vegetation that lot clearing matters most.
South Point against the rest of the country
South Point ranks lower within Texas (23rd percentile statewide) than its 66th national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, South Point ranks 10,731 for wildfire risk (1 is highest) and 17,679 by building count (1 is largest). Within Texas alone, it ranks 1,384 of 1,795 places by risk. See the full county-by-county picture for Texas on its state page.
Shopping for coverage in South Point
South Point's high rating (66th 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
South Point's 74.9% 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 South Point's figures come from
The methodology guide shows exactly how USFS turned 482 counted buildings into the percentiles shown above for South Point. The exposure-zones guide covers what South Point's dominant direct exposure actually means, with real examples from across the dataset.