Nicholson, PA
Nicholson, PA's wildfire risk, in USFS's own numbers
USFS scores Nicholson at the 51st national percentile for wildfire risk to structures (modestly above the national average for wildfire risk), a figure built from 412 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Nicholson's burn probability — fire likelihood with no building count factored in — sits at the 52nd percentile nationally.
Where Nicholson's buildings actually sit
Indirect exposure is dominant in Nicholson (51.7% of 412 buildings): far enough from burnable vegetation to avoid flame contact, close enough for wind-blown embers. Only 48.3% sit in the Direct zone.
Nicholson against the rest of the country
Nicholson's 83rd-percentile standing inside Pennsylvania outpaces its 51st national percentile — this is a hotter spot than most of its own state, even though the state as a whole runs cooler nationally. Among the 31,521 US communities USFS scores, Nicholson ranks 15,550 for wildfire risk (1 is highest) and 18,993 by building count (1 is largest). Within Pennsylvania alone, it ranks 337 of 1,991 places by risk. See the full county-by-county picture for Pennsylvania on its state page.
What this risk score means for insurance
At the 51st national percentile, Nicholson rates elevated for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
Hardening a home in Nicholson
Nicholson's 51.7% Indirect-exposure share points at embers, not flame contact, as the main pathway — ember-resistant vents and non-combustible roofing rank ahead of defensible space here. Detail in the home-hardening guide.
Where Nicholson's figures come from
Nicholson's 51st-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 Nicholson's dominant indirect exposure actually means, with real examples from across the dataset.