This thesis proposes a novel method for understanding occupancy in public indoor spaces by creating hybrid light-syntax zones, based on both simulated illuminance data and simulated configuration data. Yearly illuminance profiles and spatial syntax characteristics such as physical connectivity and visual integration were examined to develop zones which theoretically have similar occupancy rates to one another. To support the light-syntax zone concept, a case study was performed in a student cafe on a university campus. Occupancy and exterior light conditions were observed for thirteen days. Occupancy rates were mapped to each seat within the cafe and analyzed for correlations with the light- syntax zone data. A significant difference was found in the occupancy rates between different exterior light conditions (direct light present, rapidly changing/intermediate, diffuse light present) in the test cafe. A slight negative correlation was found between occupancy rates and integration and physical connectivity values, which seems to indicate that the cafe users are seeking out the most secluded spaces. However, higher illuminance values also show a correlation with higher occupancy ratios. Given the map of the space, it is possible that these two variables are confounded. Further studies are necessary to determine the validity of light-syntax zones as a tool for predicting relative occupancy within an indoor space.