Location data collected by mobile applications is typically aggregated from a heterogeneous sample of mobile devices with varying demographic and behavioral characteristics. In this paper, we present a method for detecting homogenous groups of mobile devices relevant to specific scientific domains. We apply this method to an anonymized in-app location dataset of ~2,000,000 mobile devices in the United Kingdom, to detect homogeneous groups of devices relevant to applications including transport planning and infectious disease modeling.