Union Park, FL
Union Park wildfire risk explained
Union Park sits at the 71st 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 3,381 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Union Park at the 73rd national percentile — 2 points above its risk-to-structures score, a gap driven by how much is actually built there.
Union Park's building exposure, zone by zone
Most of Union Park's buildings (72.8% of 3,381) fall outside USFS's Direct and Indirect zones entirely — that doesn't zero out the score above, it means the risk is regional, not structure-by-structure.
How Union Park compares
Inside Florida, Union Park sits at just the 28th percentile even though it scores 71st 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, Union Park ranks 9,108 for wildfire risk (1 is highest) and 4,939 by building count (1 is largest). Within Florida alone, it ranks 686 of 955 places by risk. See the full county-by-county picture for Florida on its state page.
Union Park and the insurance market
At the 71st percentile nationally, Union Park carries the high rating that has pushed some carriers to limit new business in similarly-scored places elsewhere in the country. Worth comparing quotes rather than assuming last year's renewal terms still apply.
Lowering exposure, not just insuring around it
Union Park's 72.8% 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 Union Park's figures come from
The methodology guide shows exactly how USFS turned 3,381 counted buildings into the percentiles shown above for Union Park. The exposure-zones guide covers what Union Park's dominant minimal exposure actually means, with real examples from across the dataset.