In recent years, it has increasingly been recognized that due to the uncertain geographic context problem caused by daily human mobility, the residential population is too static to serve as a valid measure of the population at risk for criminal victimization. Various alternative measures have been suggested instead. Guided by the routine activity approach, this study furthers the concept of crime risk population and its measurement across space and time. Using exceptionally comprehensive data sets on population mobility and on theft from the person in a large city in China, we select the best indicator of the risk population from the following four candidates: residential population, subway ridership, taxi ridership, and mobile phone users. Controlling for the potentially confounding effects of offender and guardian presence, we show that on both weekdays and weekends, the best indicators of risk population vary over the course of the day. In the morning, residential population outperforms other measures. In the afternoon and evening, taxi ridership and phone users are better indicators. Although the mobile phone user base forms an arguably more representative measure of ambient population, during some periods taxi ridership is superior because it provides a better indicator of outdoor (as opposed to indoor) activities. In terms of practical applications to security policy and law enforcement, these findings can help identify crime hot spots by calculating accurate crime risks.