WildfireRiskFinder

Peak, SC

Peak wildfire risk explained

High
68thpercentile nationally

USFS's Wildfire Risk to Communities model puts Peak at the 68th national percentile for risk to structures, well above the national norm for wildfire risk — a score built from 59 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 Peak at the 70th percentile, close to its 68th-percentile risk score.

Peak's building exposure, zone by zone

59Total buildings
100%Direct exposure
0%Indirect exposure
0%Minimal exposure

Direct exposure dominates in Peak: 100% of its 59 buildings, versus 0% Indirect and 0% Minimal. Clearing space around a structure changes the outcome here more than any single building-material swap.

How Peak compares

Peak ranks lower within South Carolina (50th percentile statewide) than its 68th national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Peak ranks 10,063 for wildfire risk (1 is highest) and 30,693 by building count (1 is largest). Within South Carolina alone, it ranks 239 of 474 places by risk. See the full county-by-county picture for South Carolina on its state page.

Shopping for coverage in Peak

Peak's high rating (68th percentile) puts it among the places where the national carrier-pullback trend is most relevant — not a guarantee of a coverage problem, but a reason to shop rather than assume.

Hardening a home in Peak

Peak's 100% 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 Peak's figures come from

The methodology guide shows exactly how USFS turned 59 counted buildings into the percentiles shown above for Peak. The exposure-zones guide covers what Peak's dominant direct exposure actually means, with real examples from across the dataset.