Urbanization is the long-term problem associated with the growth in urban population due to migration, resulting in social inequalities and loss of natural resources, causing ecological imbalances across developed as well as developing countries. The environmental quality of the cities are affected by the uncontrolled usage of natural resources, the sprawl of settlements, unplanned development and large-scale industrial activities. The urban forms pose the primary challenges to humanity by rapidly depleting natural resources, enhancing climate change, global, regional, and local conflicts resulting in ineffective governance. It’s essential to account for the driving forces contributing to urban growth and their effects on the city’s environment, which aid in sustainability. The present research has assessed the land use change in the CRDA region through machine learning and deep learning approaches. The detailed digital infrastructure portrays the capabilities of sensing, controlling, and analyzing current and likely urban growth forms aids as a foundation for smart planning and sustainable development. The deep learning model shows a greater increase in built-up cover of 13% compared to 10% in the year 2022. The research findings provide valuable insights into urban growth, which aids the decision-makers in determining sustainable developmental measures and effective regional planning.