Rodeo, CA
How exposed is Rodeo to wildfire?
Rodeo's 3,343 buildings earn a 87th-percentile wildfire-risk score nationally under USFS's model — in USFS's highest wildfire-risk band nationally. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Rodeo's burn probability — fire likelihood with no building count factored in — sits at the 88th percentile nationally.
Rodeo's building exposure, zone by zone
Most of Rodeo's buildings (90.9%) sit in the Indirect zone, where wind-blown embers rather than flame front are the mechanism USFS is scoring — ember-resistant vents and non-combustible roofing are the interventions this pattern favors, more than defensible space alone.
Where Rodeo ranks
Rodeo ranks lower within California (54th percentile statewide) than its 87th national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Rodeo ranks 4,184 for wildfire risk (1 is highest) and 4,989 by building count (1 is largest). Within California alone, it ranks 723 of 1,570 places by risk. See the full county-by-county picture for California on its state page.
Shopping for coverage in Rodeo
Rodeo sits in California, one of two states that legally require a wildfire-risk disclosure at sale. California's FAIR Plan, the state's insurer of last resort, ended 2025 with 668,609 residential policies after adding 21,859 in Q4 alone — the kind of market shift a 87th-percentile score like Rodeo's can end up mattering for. More on the disclosure law.
Hardening a home in Rodeo
Rodeo's 90.9% Indirect-exposure share points at embers, not flame contact, as the main pathway — ember-resistant vents and non-combustible roofing rank ahead of defensible space here. Detail in the home-hardening guide.
Where Rodeo's figures come from
The methodology guide shows exactly how USFS turned 3,343 counted buildings into the percentiles shown above for Rodeo. The exposure-zones guide covers what Rodeo's dominant indirect exposure actually means, with real examples from across the dataset.