Machine Learning algorithms have proved to be a powerful tool for analyzing satellite imagery of any resolution and proving better and more comprehensive insights. For example, a machine learning algorithm can be trained to understand rapidly change in land use extract and classify infrastructure service like roads, schools, hospitals. It is evident that the use of machine learning will empower urban authority with near real-time information about urban growth, which in turn will strengthen urban management capacity. This project aims to leverage rapidly expanding sources of satellite data and machine learning algorithms in order to quickly reveal how actual city development aligns with planning. This research project will contribute to urban planning and management in the developing world like Tanzania as well as solving the current challenges of poor planning.