The black-footed ferret (Mustela nigripes) is one of North America’s most endangered mammals and an obligate predator of prairie dogs (Cynomys spp.), depending on them for food and their burrows for shelter and raising young. Estimates of prairie dog colony size and density are key measures biologists use to assess habitat for reintroduction of black-footed ferrets. In this study, automated feature extraction of individual prairie dog burrows from small Unmanned Aircraft Systems (sUAS) multispectral imagery provided assessments of colony size and population density. Based on counts collected by ground survey and through manually digitized burrow counts at 27 plot sites, automated feature extraction using sUAS imagery provided a novel approach to efficiently collect accurate extent and density metrics to assess and monitor black-footed ferret habitat. The benefits of sUAS versus traditional on-the-ground biological surveys are to minimize environmental/behavioral impact on prairie dogs, offer a less time-consuming survey option, reduce count error and bias, provide the ability to cover larger areas, and conduct more frequent repeat surveys. sUAS can explore other potential advantages such as the detailed assessment of vegetation species composition and structure with multispectral and advanced sensors such as hyperspectral and LiDAR.