Cedar Crest, PA
How exposed is Cedar Crest to wildfire?
USFS scores Cedar Crest at the 54th national percentile for wildfire risk to structures (modestly above the national average for wildfire risk), a figure built from 130 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Cedar Crest at the 52nd national percentile — 2 points below its risk-to-structures score, a gap driven by how much is actually built there.
Where Cedar Crest's buildings actually sit
130 buildings are counted in Cedar Crest, and 51.5% of them sit in USFS's Direct exposure zone — flame contact, not just ember cast, is the live possibility for most of them, against 0% rated Minimal.
How Cedar Crest compares
Within Pennsylvania, Cedar Crest ranks higher (89th percentile) than it does nationally (54th) — one of the more fire-exposed places in a state that, overall, scores lower than that. Among the 31,521 US communities USFS scores, Cedar Crest ranks 14,572 for wildfire risk (1 is highest) and 27,730 by building count (1 is largest). Within Pennsylvania alone, it ranks 219 of 1,991 places by risk. See the full county-by-county picture for Pennsylvania on its state page.
Shopping for coverage in Cedar Crest
At the 54th national percentile, Cedar Crest 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 Cedar Crest
Cedar Crest's 51.5% Direct-exposure share means lot clearing around the structure typically outweighs any single material upgrade here. The home-hardening guide ranks the options for a place shaped like this.
Where Cedar Crest's figures come from
Every one of the two percentiles behind Cedar Crest's 14,572-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Cedar Crest's dominant direct exposure actually means, with real examples from across the dataset.