May, TX
May, TX's wildfire risk, in USFS's own numbers
USFS scores May at the 91st national percentile for wildfire risk to structures (in USFS's highest wildfire-risk band nationally), a figure built from 292 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks May at the 90th national percentile — 1 points below its risk-to-structures score, a gap driven by how much is actually built there.
May's building exposure, zone by zone
82.5% of May's 292 buildings sit in USFS's Direct exposure zone, roughly 241 structures close enough to burnable vegetation for flame contact, not just embers — 17.5% fall in the Indirect, ember-only zone and 0% are Minimal.
May against the rest of the country
There's little gap between May's 91st national percentile and its 87th percentile inside Texas, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, May ranks 2,815 for wildfire risk (1 is highest) and 21,868 by building count (1 is largest). Within Texas alone, it ranks 240 of 1,795 places by risk. See the full county-by-county picture for Texas on its state page.
May and the insurance market
May's very high rating (91st 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.
Lowering exposure, not just insuring around it
With 82.5% of May in Direct exposure, defensible-space clearing and ember-resistant construction (vents, Class-A roofing) address the exposure this page's own numbers describe, not a generic checklist. See the home-hardening guide.
Where May's figures come from
May's 91st-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 May's dominant direct exposure actually means, with real examples from across the dataset.