Urban sprawl and expansion present significant challenges in the process of sustainable urban management. Urban growth and the escalating complexity of urban challenges have exacerbated environmental impacts, creating pronounced disparities between urban centers and their surrounding regions. During the past few years, these complexities have increased significantly; thus, addressing these challenges has become significantly important for better urban planning and management. Modern urban geography studies increasingly rely on remote sensing data and artificial intelligence to track the pace of urban expansion and spatial patterns. The multi-temporal land use land cover (LULC) maps of urban areas derived from remote sensing data predictive models provide planners and policy makers with valuable insights into the development trajectories of cities, encompassing their systems, functions, and structures. Remote sensing and GIS-based analytical approaches and forecasting models are used for mapping, monitoring, measuring, and analyzing the urban expansion. At a global level, more and more interest groups are getting involved in critical urban environmental issues to support sustainable urban development. These groups use remote sensing and GIS tools to address the issues related to urban planning and policy making. Despite all these, there is still a gap between the urban remote sensing research and the broader theoretical understanding of urban development. This study aims to address and bridge this gap and provide policymakers, local urban authorities, and planners with a better understanding of urbanization through the integration of theoretical insights and research-based results.