In the modern scenario, urban planning and territorial monitoring have become crucial tasks for regional administrations and local authorities due to rapid city and demographic growth. Combining open data from Earth Observation missions with geospatial data for urban planning, such as geodatabases, orthoimages, and thematic maps, is essential for making well-informed environmental support and natural resource management decisions. This research presents a comprehensive overview of the key topics, approaches, and machine learning applications in urban planning. Reviewing recent literature and EU funding programmes such as Horizon 2020 and the European Space Programme (focusing on the Earth Observation missions Copernicus and IRIDE), we emphasized the significance of integrating and implementing satellite data in the Geographic Information System (GIS) using machine learning for sustainable urban planning and management. Furthermore, the results highlighted the importance of remote sensing, particularly satellite images, in understanding urban forms, territorial planning, and monitoring the evolution of the built environment, nature, and ecosystem.