This study used satellite images and computer models to map where different crops—like rice, cotton, sugarcane, and wheat—were grown in Sindh, Pakistan, during 2022. By analyzing images taken throughout the year from a European satellite (Sentinel-2), researchers could detect changes in vegetation that matched crop growth patterns. They also collected real crop samples from farms to train a machine learning model that helped identify each crop from space. The final map showed where each crop was concentrated and how their planting seasons differed. For example, rice grew mostly in the north, while wheat was more common in the south and west. This work helps farmers, scientists, and policymakers better understand agricultural patterns and plan for food production, especially in regions where data is hard to collect on the ground.