Lawrence, IN
Lawrence, IN's wildfire risk, in USFS's own numbers
USFS's Wildfire Risk to Communities model puts Lawrence at the 8th national percentile for risk to structures, among the lower wildfire-risk places nationally — a score built from 18,842 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Lawrence's burn probability — fire likelihood with no building count factored in — sits at the 10th percentile nationally.
Where Lawrence's buildings actually sit
88.2% of Lawrence's 18,842 buildings sit in USFS's Minimal exposure zone, with only 11.8% rated Direct — risk here comes from regional burn probability more than proximity to burnable vegetation at the structure itself. At 18,842 buildings, this is a substantial built environment, so the shares below describe a real population of structures, not a handful of edge cases.
Where Lawrence ranks
Compare Lawrence's two percentiles: 50th within Indiana, only 8th nationally — a gap of 42 points that marks it as unusually exposed for its own state. Among the 31,521 US communities USFS scores, Lawrence ranks 28,898 for wildfire risk (1 is highest) and 754 by building count (1 is largest). Within Indiana alone, it ranks 481 of 967 places by risk. See the full county-by-county picture for Indiana on its state page.
Shopping for coverage in Lawrence
At the 8th national percentile, Lawrence rates low 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
Lawrence's 88.2% 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 Lawrence's figures come from
Lawrence's 8th-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 Lawrence's dominant minimal exposure actually means, with real examples from across the dataset.