WildfireRiskFinder

North Anson, ME

How exposed is North Anson to wildfire?

Low
7thpercentile nationally

USFS scores North Anson at the 7th national percentile for wildfire risk to structures (among the lower wildfire-risk places nationally), a figure built from 391 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)

Separately from the risk score above, North Anson's burn probability — fire likelihood with no building count factored in — sits at the 7th percentile nationally.

Where North Anson's buildings actually sit

391Total buildings
68.5%Direct exposure
31.5%Indirect exposure
0%Minimal exposure

Of North Anson's 391 counted buildings, 68.5% carry Direct exposure and only 0% carry Minimal — a lopsided split that puts defensible-space clearing ahead of vents or roofing as the intervention worth doing first.

Where North Anson ranks

North Anson scores 7th nationally and 12th within Maine — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, North Anson ranks 29,253 for wildfire risk (1 is highest) and 19,395 by building count (1 is largest). Within Maine alone, it ranks 136 of 155 places by risk. See the full county-by-county picture for Maine on its state page.

North Anson and the insurance market

At the 7th national percentile, North Anson 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

Because Direct exposure dominates in North Anson (68.5%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.

Where North Anson's figures come from

North Anson's 7th-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 North Anson's dominant direct exposure actually means, with real examples from across the dataset.