Casa Loma, CA
How exposed is Casa Loma to wildfire?
USFS scores Casa Loma at the 75th national percentile for wildfire risk to structures (well above the national norm for wildfire risk), a figure built from 862 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 Casa Loma at the 76th percentile, close to its 75th-percentile risk score.
What "at risk" means for the buildings here
Most of Casa Loma's buildings (85.9% of 862) 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.
Where Casa Loma ranks
Casa Loma's 75th national percentile looks worse in isolation than its 33rd ranking inside California does — this place is on the milder end for its own state, by 42 points. Among the 31,521 US communities USFS scores, Casa Loma ranks 7,905 for wildfire risk (1 is highest) and 13,054 by building count (1 is largest). Within California alone, it ranks 1,055 of 1,570 places by risk. See the full county-by-county picture for California on its state page.
Casa Loma and the insurance market
Because Casa Loma is in California, a wildfire-hazard disclosure is legally required before a sale closes here — unusual nationally, since only these two states mandate it. The state's FAIR Plan alone carried 668,609 policies by the end of 2025. Full detail in the disclosure-law guide.
What would actually reduce this score
Even with 85.9% of Casa Loma 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 Casa Loma's figures come from
The methodology guide shows exactly how USFS turned 862 counted buildings into the percentiles shown above for Casa Loma. The exposure-zones guide covers what Casa Loma's dominant minimal exposure actually means, with real examples from across the dataset.