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Daily Urban Systems (DUSs) are not only an attractive concept for planning locations for jobs, housing, schools and retail, but also for managing services such as public transportation and health care. If we can match geographically demand and supply of goods and services, higher levels of spatial efficiency can be reached. Since 50 years most of the research delineating DUSs uses thresholds of commuting levels, thus identifying labor markets polarized towards central cities. Few research grasps the more recent complex interactions within metropolitan areas due to growth and decentralization of activities. In this paper, we use techniques of complex network theory, namely community detection, on nearly 4,500,000 Belgian commuting links to define DUSs. Secondly, we explore differences for DUSs by gender and by income group. The results confirm the usefulness of community detection techniques for delineating Daily Urban Systems. Commuting patterns of females and low and very low income commuters are geographically more restricted than those of male and high and very high income commuters.