SUSTAINABLE URBAN FUTURES: HOW AI CAN PREDICT AND SHAPE CITY EXPANSION
DOI:
https://doi.org/10.5281/zenodo.15698220Keywords:
Machine Learning, Artificial Intelligence, Land Use Land Cover, Predictive Modelling, Predictive AnalyticsAbstract
The swift expansion of urban populations and limited space has stimulated innovative and groundbreaking solutions for efficient city management and sustainability. AI-driven implementations have surfaced as robust tools for optimizing smart city operations, including environmental monitoring and infrastructure planning. These simulations harness machine learning, digital twins, IoT data, and geospatial analytics, predictive analytics for planning realistic urban models. This study explores the role of AI in forecasting city expansion, analyzing key machine learning models, geospatial analytics, and their integration into smart urban planning. This research paper aims to explore the use of machine learning models to predict urban expansion, population growth, and changes in land use to guide long-term urban planning strategies.
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