Spatial data plays a foundational role in urban design and architecture by capturing the physical, social, and environmental dimensions of urban contexts. The proliferation of spatial data has introduced challenges in data quality, granularity, and interoperability: a profound methodological turn especially for disciplines ordinarily confronted to spatial "challenges" such as architecture, urbanism and engineering. We can surely state that within these disciplines the increased employment of GIS platforms and spatial programming frameworks is enabling a revolution of the means of spatial representation, yet the mathematical disciplines informing spatial data analysis remain obscure for many users. The article aims to unveil the complex analytical operations underpinning spatial analysis tools to reveal how spatial analysis is informing decision-making across urban planning and infrastructure management in increasingly complex urban environments.
Tsionas, I. (2025). Spatial data and methods for urban planning and architecture. Lieux dits, 28, 30-35. https://doi.org/10.14428/ld.vi28.90703 (Original work published 2025)