WildfireRiskFinder

Oley, PA

Oley, PA's wildfire risk, in USFS's own numbers

Low
13thpercentile nationally

Out of every US place USFS scores, Oley lands at the 13th percentile for wildfire risk to structures — among the lower wildfire-risk places nationally — a figure built from its 691 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)

Fire likelihood alone (USFS's burn-probability figure) ranks Oley at the 11th national percentile — 2 points below its risk-to-structures score, a gap driven by how much is actually built there.

Where Oley's buildings actually sit

691Total buildings
43%Direct exposure
36.8%Indirect exposure
20.3%Minimal exposure

Direct exposure dominates in Oley: 43% of its 691 buildings, versus 36.8% Indirect and 20.3% Minimal. Clearing space around a structure changes the outcome here more than any single building-material swap.

How Oley compares

Oley scores 13th nationally and 11th within Pennsylvania — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, Oley ranks 27,558 for wildfire risk (1 is highest) and 14,755 by building count (1 is largest). Within Pennsylvania alone, it ranks 1,770 of 1,991 places by risk. See the full county-by-county picture for Pennsylvania on its state page.

Oley and the insurance market

At the 13th national percentile, Oley 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 Oley (43%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.

Where Oley's figures come from

Oley'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 Oley's dominant direct exposure actually means, with real examples from across the dataset.