Pima, AZ
Pima, AZ's wildfire risk, in USFS's own numbers
Out of every US place USFS scores, Pima lands at the 86th percentile for wildfire risk to structures — in USFS's highest wildfire-risk band nationally — a figure built from its 1,460 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Pima at the 86th national percentile — 0 points above its risk-to-structures score, a gap driven by how much is actually built there.
Pima's building exposure, zone by zone
USFS puts 54.7% of Pima's 1,460 buildings in the Indirect exposure zone, versus 41.2% Direct and 4.1% Minimal — a place where the fire doesn't need to reach the structure directly for embers to.
Pima against the rest of the country
Pima ranks lower within Arizona (58th percentile statewide) than its 86th national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Pima ranks 4,306 for wildfire risk (1 is highest) and 9,352 by building count (1 is largest). Within Arizona alone, it ranks 186 of 441 places by risk. See the full county-by-county picture for Arizona on its state page.
Pima and the insurance market
Pima's 86th-percentile, very 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.
Lowering exposure, not just insuring around it
With ember exposure the dominant pattern in Pima (54.7% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.
Where Pima's figures come from
Every one of the two percentiles behind Pima's 4,306-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Pima's dominant indirect exposure actually means, with real examples from across the dataset.