Miramar, FL
Miramar wildfire risk explained
USFS scores Miramar at the 99th national percentile for wildfire risk to structures (in USFS's highest wildfire-risk band nationally), a figure built from 31,060 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Miramar's burn probability — fire likelihood with no building count factored in — sits at the 99th percentile nationally.
What "at risk" means for the buildings here
83.5% of Miramar's 31,060 buildings sit in USFS's Minimal exposure zone, with only 3.1% rated Direct — risk here comes from regional burn probability more than proximity to burnable vegetation at the structure itself. At 31,060 buildings, this is a substantial built environment, so the shares below describe a real population of structures, not a handful of edge cases.
How Miramar compares
Miramar scores 99th nationally and 100th within Florida — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, Miramar ranks 197 for wildfire risk (1 is highest) and 363 by building count (1 is largest). Within Florida alone, it ranks 4 of 955 places by risk. See the full county-by-county picture for Florida on its state page.
Shopping for coverage in Miramar
Miramar's very high rating (99th 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
Miramar's 83.5% Minimal-exposure share means structure-level hardening matters less here than it would elsewhere — still worth the low-cost basics, per the home-hardening guide.
Where Miramar's figures come from
Miramar's 99th-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 Miramar's dominant minimal exposure actually means, with real examples from across the dataset.