This project presents an interactive satellite image segmentation system designed to analyze historical land cover changes across specified locations. Utilizing Google Earth Engine’s Image API for efficient satellite image retrieval, the system offers a seamless interface to explore historical geographical data. The project revolves around machine learning techniques, employing a customized U-Net neural network for accurate image segmentation. This system visualizes land cover change trends through dynamic animations and charts, offering a tool for observing environmental transformations over time.