SPATIAL INTELLIGENCE: FUTURE-READY URBAN NETWORKS, PLANNING, ARCHITECTURE, AND DESIGN

This article conceptualizes spatial intelligence (SI) as an integrative approach that interconnects urban-scale geospatial data, artificial intelligence, GeoAI, sensor networks, urban digital twins, and design interfaces. The study is based on a structured integrative literature review and conceptual synthesis. Peer-reviewed articles, review papers, and relevant documents issued by international organizations such as the ITU and UN-Habitat, published between 2019 and 2026, were thematically analyzed. The analysis resulted in a three-layer model: (1) the data and context layer, (2) the AI/GeoAI analytics and simulation layer, and (3) spatial decision and design interfaces. Data governance, interoperability, privacy, explainability, and human oversight were identified as cross-cutting requirements applicable to all layers of the model. The analysis indicates that SI can strengthen the capacity to compare scenarios related to climate risks, transport, energy, land use, and generative design within a shared environment. However, the practical effectiveness of such systems depends on data quality, standards, validation procedures, and governance mechanisms. The proposed model provides a conceptual basis for coherently linking decisions from the building scale to the urban scale in architecture and urban planning.