Leonardo, NJ
How exposed is Leonardo to wildfire?
USFS scores Leonardo at the 67th national percentile for wildfire risk to structures (well above the national norm for wildfire risk), a figure built from 1,148 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Leonardo at the 66th percentile, close to its 67th-percentile risk score.
Leonardo's building exposure, zone by zone
Leonardo rates 91.9% Minimal exposure against just 8.1% Direct and 0% Indirect — of 1,148 buildings counted, few sit close enough to burnable vegetation for USFS to flag them individually.
How Leonardo compares
Leonardo's risk sits at a similar level relative to New Jersey (77th percentile statewide) as it does nationally (67th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Leonardo ranks 10,280 for wildfire risk (1 is highest) and 10,972 by building count (1 is largest). Within New Jersey alone, it ranks 158 of 700 places by risk. See the full county-by-county picture for New Jersey on its state page.
What this risk score means for insurance
Leonardo's 67th-percentile, high rating is the kind of score behind a broader national pattern: insurers pulling back from the highest wildfire-risk markets, non-renewing or declining new policies outright, most visibly in California. Shopping around, not assuming automatic renewal, tends to matter here.
Hardening a home in Leonardo
Leonardo's 91.9% 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 Leonardo's figures come from
Every one of the two percentiles behind Leonardo's 10,280-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Leonardo's dominant minimal exposure actually means, with real examples from across the dataset.