Bethel Village, IN
Bethel Village wildfire risk explained
Out of every US place USFS scores, Bethel Village lands at the 8th percentile for wildfire risk to structures — among the lower wildfire-risk places nationally — a figure built from its 227 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Bethel Village at the 9th 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
USFS classifies 65.6% of Bethel Village's buildings as Minimal exposure, the largest of the three zones here by a wide margin over 34.4% Direct and 0% Indirect — a landscape-level risk rather than a building-by-building one.
Where Bethel Village ranks
Bethel Village's 48th-percentile standing inside Indiana outpaces its 8th national percentile — this is a hotter spot than most of its own state, even though the state as a whole runs cooler nationally. Among the 31,521 US communities USFS scores, Bethel Village ranks 29,052 for wildfire risk (1 is highest) and 23,883 by building count (1 is largest). Within Indiana alone, it ranks 496 of 967 places by risk. See the full county-by-county picture for Indiana on its state page.
Bethel Village and the insurance market
At the 8th national percentile, Bethel Village rates low 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 Bethel Village
Bethel Village's 65.6% 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 Bethel Village's figures come from
Bethel Village'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 Bethel Village's dominant minimal exposure actually means, with real examples from across the dataset.