The integration of geospatial artificial intelligence for enhancing built environment sustainability

Geospatial artificial intelligence (GeoAI) is an innovative mechanism that uses artificial intelligence (AI) techniques integrated with geospatial information systems (GIS) and geospatial datasets. This study investigates the potential applicability of GeoAI to enhance sustainability, efficiency, and regulatory compliance in built environment projects. A comprehensive review of 72 articles published between 2020 and 2024 revealed four dominant application areas of GeoAI in the built environment: Sustainable Built Environment, Analysis of Built Environment, Environmental and Natural Resource Management, and Sustainable Urban Planning and Smart Cities. GeoAI's applications span diverse domains, including Natural Language Processing for location identification and semantic derivation from geographical information. Geo- visual applications enable visual classification and geo-object recognition. GeoAI analyses facilitate pattern recognition in multidimensional data captured through various techniques. This paper provides an overview of GeoAI integration into design and planning processes, highlighting its ability to extract insights from large- scale geospatial datasets such as satellite imagery, terrain models, and environmental data. AI algorithms can optimize site selection, building orientation, energy efficiency, and infrastructure planning while ensuring adherence to regulations and standards. While GeoAI's full potential in urban design, building design, disaster management, and compliance is yet to be fully explored, it promises significant advancements in these areas. This study also identifies key challenges and opportunities for future research in GeoAI applications within built environments, paving the way for a more sustainable and efficient built environment.