Moenkopi, AZ
Moenkopi wildfire risk explained
Out of every US place USFS scores, Moenkopi lands at the 13th percentile for wildfire risk to structures — among the lower wildfire-risk places nationally — a figure built from its 368 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Moenkopi's burn probability — fire likelihood with no building count factored in — sits at the 16th percentile nationally.
What "at risk" means for the buildings here
83.4% of Moenkopi's 368 buildings sit in USFS's Direct exposure zone, roughly 307 structures close enough to burnable vegetation for flame contact, not just embers — 16.6% fall in the Indirect, ember-only zone and 0% are Minimal.
Moenkopi against the rest of the country
Moenkopi's risk sits at a similar level relative to Arizona (1st percentile statewide) as it does nationally (13th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Moenkopi ranks 27,503 for wildfire risk (1 is highest) and 19,896 by building count (1 is largest). Within Arizona alone, it ranks 438 of 441 places by risk. See the full county-by-county picture for Arizona on its state page.
What this risk score means for insurance
At the 13th national percentile, Moenkopi rates low for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
What would actually reduce this score
With 83.4% of Moenkopi in Direct exposure, defensible-space clearing and ember-resistant construction (vents, Class-A roofing) address the exposure this page's own numbers describe, not a generic checklist. See the home-hardening guide.
Where Moenkopi's figures come from
Moenkopi's 13th-percentile score and its burn-probability figure both come from the same USFS workbook, documented in the methodology guide. The exposure-zones guide covers what Moenkopi's dominant direct exposure actually means, with real examples from across the dataset.