Luthersburg, PA
Luthersburg wildfire risk explained
Out of every US place USFS scores, Luthersburg lands at the 40th percentile for wildfire risk to structures — close to the middle of USFS's national wildfire-risk range — a figure built from its 297 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Luthersburg at the 41st national percentile — 1 points above its risk-to-structures score, a gap driven by how much is actually built there.
What "at risk" means for the buildings here
Direct exposure dominates in Luthersburg: 95% of its 297 buildings, versus 5.1% Indirect and 0% Minimal. Clearing space around a structure changes the outcome here more than any single building-material swap.
Luthersburg against the rest of the country
Within Pennsylvania, Luthersburg ranks higher (63rd percentile) than it does nationally (40th) — one of the more fire-exposed places in a state that, overall, scores lower than that. Among the 31,521 US communities USFS scores, Luthersburg ranks 18,920 for wildfire risk (1 is highest) and 21,715 by building count (1 is largest). Within Pennsylvania alone, it ranks 744 of 1,991 places by risk. See the full county-by-county picture for Pennsylvania on its state page.
Shopping for coverage in Luthersburg
At the 40th national percentile, Luthersburg rates moderate for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
Lowering exposure, not just insuring around it
Because Direct exposure dominates in Luthersburg (95%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.
Where Luthersburg's figures come from
Every one of the two percentiles behind Luthersburg's 18,920-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Luthersburg's dominant direct exposure actually means, with real examples from across the dataset.