WildfireRiskFinder

Lilly, PA

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

Moderate
39thpercentile nationally

Out of every US place USFS scores, Lilly lands at the 39th percentile for wildfire risk to structures — close to the middle of USFS's national wildfire-risk range — a figure built from its 459 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)

Separately from the risk score above, Lilly's burn probability — fire likelihood with no building count factored in — sits at the 39th percentile nationally.

Lilly's building exposure, zone by zone

459Total buildings
39.2%Direct exposure
60.8%Indirect exposure
0%Minimal exposure

459 buildings are counted in Lilly, and 60.8% of them are Indirect exposure — ember-driven risk rather than the 39.2% in Direct exposure or the 0% rated Minimal.

How Lilly compares

Compare Lilly's two percentiles: 61st within Pennsylvania, only 39th nationally — a gap of 22 points that marks it as unusually exposed for its own state. Among the 31,521 US communities USFS scores, Lilly ranks 19,174 for wildfire risk (1 is highest) and 18,086 by building count (1 is largest). Within Pennsylvania alone, it ranks 781 of 1,991 places by risk. See the full county-by-county picture for Pennsylvania on its state page.

Lilly and the insurance market

At the 39th national percentile, Lilly rates moderate 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

Lilly's 60.8% 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 Lilly's figures come from

Every one of the two percentiles behind Lilly's 19,174-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Lilly's dominant indirect exposure actually means, with real examples from across the dataset.