WildfireRiskFinder

Fowler, IN

Fowler wildfire risk explained

Low
0thpercentile nationally

USFS's Wildfire Risk to Communities model puts Fowler at the 0th national percentile for risk to structures, among the lower wildfire-risk places nationally — a score built from 1,421 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)

USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Fowler at the 0th percentile, close to its 0th-percentile risk score.

Where Fowler's buildings actually sit

1,421Total buildings
11.3%Direct exposure
0%Indirect exposure
88.7%Minimal exposure

Most of Fowler's buildings (88.7% of 1,421) fall outside USFS's Direct and Indirect zones entirely — that doesn't zero out the score above, it means the risk is regional, not structure-by-structure.

How Fowler compares

There's little gap between Fowler's 0th national percentile and its 2nd percentile inside Indiana, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Fowler ranks 31,395 for wildfire risk (1 is highest) and 9,531 by building count (1 is largest). Within Indiana alone, it ranks 941 of 967 places by risk. See the full county-by-county picture for Indiana on its state page.

Shopping for coverage in Fowler

At the 0th national percentile, Fowler 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

With 88.7% of buildings rated Minimal exposure, Fowler gets less benefit from structure hardening than a Direct- or Indirect-dominant place would — the home-hardening guide explains why the zone matters.

Where Fowler's figures come from

Fowler's 0th-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 Fowler's dominant minimal exposure actually means, with real examples from across the dataset.