Microbial populations and communities are heterogeneous, yet capturing their diverse activities has proven challenging at the relevant spatiotemporal scales. Here we present par-seqFISH, a targeted transcriptome-imaging approach that records both gene-expression and spatial context within microscale assemblies at a single-cell and molecule resolution. We apply this approach to the opportunistic bacterial pathogen, Pseudomonas aeruginosa, analyzing ~600,000 individuals across dozens of physiological conditions in planktonic and biofilm cultures. We explore the phenotypic landscape of this bacterium and identify metabolic and virulence related cell-states that emerge dynamically during growth. We chart the spatial context of biofilm-related processes including motility and kin-exclusion mechanisms and identify extensive and highly spatially-resolved metabolic heterogeneity. We find that distinct physiological states can co-exist within the same biofilm, just a few microns away, underscoring the importance of the microenvironment. Together, our results illustrate the complexity of microbial populations and present a new way of studying them at high-resolution.