Laconia, IN
Laconia wildfire risk explained
Out of every US place USFS scores, Laconia lands at the 22nd percentile for wildfire risk to structures — close to the middle of USFS's national wildfire-risk range — a figure built from its 52 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Laconia at the 24th national percentile — 2 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 61.5% of Laconia's buildings as Direct exposure, higher than its 38.5% Indirect share and far above its 0% Minimal share — a profile where 32 structures sit close enough to vegetation that lot clearing matters most.
How Laconia compares
Within Indiana, Laconia ranks higher (86th percentile) than it does nationally (22nd) — one of the more fire-exposed places in a state that, overall, scores lower than that. Among the 31,521 US communities USFS scores, Laconia ranks 24,546 for wildfire risk (1 is highest) and 30,870 by building count (1 is largest). Within Indiana alone, it ranks 134 of 967 places by risk. See the full county-by-county picture for Indiana on its state page.
Laconia and the insurance market
At the 22nd national percentile, Laconia 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
Laconia's 61.5% Direct-exposure share means lot clearing around the structure typically outweighs any single material upgrade here. The home-hardening guide ranks the options for a place shaped like this.
Where Laconia's figures come from
Every one of the two percentiles behind Laconia's 24,546-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Laconia's dominant direct exposure actually means, with real examples from across the dataset.