Lebanon, PA
Lebanon wildfire risk explained
Lebanon sits at the 14th percentile nationally for wildfire risk to structures — among the lower wildfire-risk places nationally — per USFS's Wildfire Risk to Communities model, built from its 5,574 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Lebanon's burn probability — fire likelihood with no building count factored in — sits at the 14th percentile nationally.
Where Lebanon's buildings actually sit
Most of Lebanon's buildings (97.4% of 5,574) fall outside USFS's Direct and Indirect zones entirely — that doesn't zero out the score above, it means the risk is regional, not structure-by-structure. At 5,574 buildings, this is a substantial built environment, so the shares below describe a real population of structures, not a handful of edge cases.
How Lebanon compares
Lebanon scores 14th nationally and 13th 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, Lebanon ranks 27,239 for wildfire risk (1 is highest) and 3,090 by building count (1 is largest). Within Pennsylvania alone, it ranks 1,740 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
Lebanon's low rating (14th percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.
Hardening a home in Lebanon
Lebanon's 97.4% Minimal-exposure share means structure-level hardening matters less here than it would elsewhere — still worth the low-cost basics, per the home-hardening guide.
Where Lebanon's figures come from
Lebanon's 14th-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 Lebanon's dominant minimal exposure actually means, with real examples from across the dataset.