The rapid growth of cities worldwide has led to increasing challenges in transportation, health, energy, and the environment. A key component is the collection and analysis of geospatial data for urban planning and operations. This data can provide valuable insights into urban dynamics, land use change, building infrastructure, and environmental conditions in smart cities to support sustainable development goals. This chapter reviews the latest advancements in geospatial data acquisition and processing technologies in urban planning, by integrating geographic information systems with remote sensing, unmanned aerial vehicles, the Internet of Things, big data analytics, and cloud computing. It discusses geospatial datasets and the management of georeferenced data on smart cities and sustainable development, such as integrating geospatial data, data sources and accessibility, and datasets for sustainability in smart cities. Case studies demonstrate how geospatial data addresses various transportation, crime, pollution, and disaster management issues. The chapter concludes by outlining best practices and challenges in using geospatial data for smart-city applications, including data quality, privacy, and interoperability issues. It underscores the need for building comprehensive data governance frameworks and engaging with local communities to ensure geospatial technologies are applied responsibly to support sustainable urban development goals for more livable, efficient, and resilient cities.