Gulf Stream, FL
Gulf Stream wildfire risk explained
Gulf Stream sits at the 55th percentile nationally for wildfire risk to structures — modestly above the national average for wildfire risk — per USFS's Wildfire Risk to Communities model, built from its 492 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Gulf Stream at the 60th percentile, close to its 55th-percentile risk score.
Gulf Stream's building exposure, zone by zone
USFS classifies 90.9% of Gulf Stream's buildings as Minimal exposure, the largest of the three zones here by a wide margin over 9.2% Direct and 0% Indirect — a landscape-level risk rather than a building-by-building one.
Where Gulf Stream ranks
Gulf Stream's 55th national percentile looks worse in isolation than its 8th ranking inside Florida does — this place is on the milder end for its own state, by 47 points. Among the 31,521 US communities USFS scores, Gulf Stream ranks 14,050 for wildfire risk (1 is highest) and 17,493 by building count (1 is largest). Within Florida alone, it ranks 875 of 955 places by risk. See the full county-by-county picture for Florida on its state page.
What this risk score means for insurance
Gulf Stream's elevated rating (55th percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.
Hardening a home in Gulf Stream
Even with 90.9% of Gulf Stream outside USFS's Direct and Indirect zones, basic hardening — gutter maintenance, ember-resistant vents — is inexpensive relative to the regional burn-probability risk noted above. Details in the home-hardening guide.
Where Gulf Stream's figures come from
The methodology guide shows exactly how USFS turned 492 counted buildings into the percentiles shown above for Gulf Stream. The exposure-zones guide covers what Gulf Stream's dominant minimal exposure actually means, with real examples from across the dataset.