Urban Prediction

Urban prediction focuses on forecasting various aspects of urban environments, from infrastructure development and population density to traffic flow and economic activity, using diverse data sources like satellite imagery, sociodemographic data, and textual information. Current research emphasizes the development of sophisticated machine learning models, including transformer networks, graph-based approaches, and diffusion models, to capture complex spatial and temporal dependencies within urban data. These advancements aim to improve the accuracy and efficiency of urban planning, resource management, and the development of smart city technologies, ultimately leading to more sustainable and resilient urban environments.