Mixing productive economic activities with housing is a hot topic in academic and policy discourses on the redevelopment of large cities today. Mixed-use is proposed to reduce adverse effects of modernist planning such as single-use zoning, traffic congestion, and loss of quality in public space. Moreover, productive city discourses plead for the re-integration of industry and manufacturing in the urban tissue. Often, historical examples of successful mixed-use in urban areas serve as a guiding image, with vertical symbiosis appearing as the holy grail of the live-work mix-discourse. This article examines three recent live-work mix projects developed by a public real estate agency in Brussels. We investigate how different spatial layouts shape the links between productive, residential, and other land uses and how potential conflicts between residents and economic actors are mediated. We develop a theoretical framework based on earlier conceptualisations of mixed-use development to analyse the spatial and functional relationships within the projects. We situate them within the housing and productive city policies in Brussels. From this analysis, we conclude that mixed-use should be understood by considering spatial and functional relationships at various scales and by studying the actual spatial layout of shared spaces, logistics and nuisance mitigation. Mixed-use is highly contextual, depending on the characteristics of the area as well as policy goals. The vertical symbiosis between different land uses is but one example of valid mixed-use strategies along with good neighbourship, overlap, and tolerance. As such, future commercial and industrial areas will occur in various degrees of mixity in our cities.

To limit additional (net) land take for economic activities, the reality of space use needs to be properly understood. This was assessed by comparing the spatial patterns obtained from a field inventory with those from existing data for five case areas in Flanders (Belgium). Each case area is a transect from a high-density urban area to a suburban neighborhood or even a semi-rural zone. The statistics on these areas, based on official data, mostly derived from tax returns, social security contributions, and on commercial retail data, were checked with field observations. The location of economic activities and the patterns of space use vary in different settlement environments, resulting in the identification of typical characteristics for eight location environment types. While in, for example, core shopping centers a strong convergence can be noticed between existing statistics and the field inventory (71% of companies and 93% of parcels are detected on the field), in residential areas (21% of companies and 17% of parcels are detected on the field) the convergence is very limited. In other words, in some environments, (the combination of) data and statistics give a good understanding of the space use while, in other environments, gaps with realities in the field are obvious. Therefore, a field inventory system can enrich the picture and present another reality to complement both existing statistics and other land-use data methods such as remote sensing and web data extraction.