You will have access to a dataset of satellite images from publicly available source, such as NASA’s Earth Observing System Data and Information System (EOSDIS) through easy to use Geospatial API provided by the IBM Environmental Intelligence. Using a simple programming environment like Python with libraries such as NumPy and Matplotlib, this project guides you through the process of extracting relevant spectral bands, calculating NDVI values, and visualizing the spatial distribution of plant health across a specific agricultural area. You’ll learn how technology can transform raw satellite data into actionable insights for agriculture.

The project will highlight the scalability of satellite data analysis, showcasing how the same techniques can be applied to different regions or over time to track changes in vegetation health. You’ll gain practical skills in data manipulation and visualization, empowering you to apply these methods in various fields that require environmental monitoring.

Note: To complete this project, you must register to receive free access to the IBM Environmental Intelligence API keys. The process is simple and steps are provided in the project.