Mulberry, IN
Mulberry wildfire risk explained
Mulberry sits at the 3rd 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 680 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Mulberry's burn probability — fire likelihood with no building count factored in — sits at the 3rd percentile nationally.
Where Mulberry's buildings actually sit
USFS classifies 93.1% of Mulberry's buildings as Minimal exposure, the largest of the three zones here by a wide margin over 6.9% Direct and 0% Indirect — a landscape-level risk rather than a building-by-building one.
Mulberry against the rest of the country
Mulberry's 24th-percentile standing inside Indiana outpaces its 3rd 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, Mulberry ranks 30,445 for wildfire risk (1 is highest) and 14,856 by building count (1 is largest). Within Indiana alone, it ranks 728 of 967 places by risk. See the full county-by-county picture for Indiana on its state page.
Mulberry and the insurance market
At the 3rd national percentile, Mulberry 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 Mulberry
Even with 93.1% of Mulberry outside USFS's Direct and Indirect zones, basic hardening — gutter maintenance, ember-resistant vents — is inexpensive relative to the regional burn-probability risk noted above. Details in the home-hardening guide.
Where Mulberry's figures come from
The methodology guide shows exactly how USFS turned 680 counted buildings into the percentiles shown above for Mulberry. The exposure-zones guide covers what Mulberry's dominant minimal exposure actually means, with real examples from across the dataset.