Los Indios, TX
Los Indios, TX's wildfire risk, in USFS's own numbers
USFS scores Los Indios at the 53rd national percentile for wildfire risk to structures (modestly above the national average for wildfire risk), a figure built from 439 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Los Indios at the 53rd national percentile — 0 points above its risk-to-structures score, a gap driven by how much is actually built there.
Los Indios's building exposure, zone by zone
Los Indios rates 74% Minimal exposure against just 26% Direct and 0% Indirect — of 439 buildings counted, few sit close enough to burnable vegetation for USFS to flag them individually.
How Los Indios compares
Inside Texas, Los Indios sits at just the 8th percentile even though it scores 53rd nationally — the state's overall wildfire exposure is high enough to make this a relatively quiet corner of it. Among the 31,521 US communities USFS scores, Los Indios ranks 14,955 for wildfire risk (1 is highest) and 18,495 by building count (1 is largest). Within Texas alone, it ranks 1,656 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
Los Indios's elevated wildfire rating (53rd percentile) isn't the kind of score driving the carrier pullback making news in the highest-risk Western markets — but a standard homeowners quote is still worth comparing on its own terms.
Lowering exposure, not just insuring around it
With 74% of buildings rated Minimal exposure, Los Indios gets less benefit from structure hardening than a Direct- or Indirect-dominant place would — the home-hardening guide explains why the zone matters.
Where Los Indios's figures come from
Los Indios's 53rd-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 Los Indios's dominant minimal exposure actually means, with real examples from across the dataset.