Cellular base station density as a proxy for urban ambient population density: a case study using open data in Tokyo

Accurately estimating ambient population density, which refers to the number of people present in a location at a specific time, is critical for effective urban planning, disaster response, and infrastructure management. However, most existing methods rely on proprietary data sources such as GPS traces or mobile phone records, limiting both accessibility and reproducibility. This study demonstrated that the spatial density of cellular base stations, available as an open infrastructure dataset, can serve as an effective proxy for ambient population density. Additionally, we introduce a practical method for identifying high-demand areas during daytime using only open data, which supports more accurate population estimation without the need for mobility logs or commercial datasets. Using Tokyo Metropolis as a case study, we evaluated the correlation between the cellular base station density, derived from the open dataset OpenCelliD, and ground-truth ambient population data. The results indicate that daytime correlations exceed 0.85 at the citywide level and reach up to 0.90 in estimated high-demand areas, which are higher than those obtained when using points of interest (POI) density as the comparative proxy. These findings confirm that cellular base station density is a reliable and reproducible proxy for ambient population density in urban environments. The proposed method provides a scalable and low-cost alternative for geospatial population analysis, particularly in contexts where proprietary data are unavailable.