Pixel Classification for Pre-College Students Using GOES-R Proxy Data

In preparation for the next generation of operational geostationary satellites, researchers rely on proxy data available from current orbital platforms in the development of algorithms used in pixel-based classification for mapping land cover, land surface types and sea ice. As seen from a science education perspective, the various tools and pixel-based classification methods using GOES-R proxy datasets offers an opportunity for pre-college students to engage in authentic Earth system science and engineering practices. An activity will be developed that introduces pre-college educators and students to some of the tools and datasets used by researchers. These datasets are publicly available. The tools are free of cost, free of hassle to install, and user-friendly. In this activity, students will learn how channels in the proxy data are associated with the GOES-R Advanced Baseline Imager (ABI). Students will use remote sensing tools; such as, ImageJ, MultiSpec, and Bilko to explore satellite datasets, navigate the Hierarchical Data Format (HDF) – the official file format for NASA's Earth Observing System (EOS) data products – identify, extract, and visualize usable data. Students will learn to implement these data into some of the algorithms used in pixel-based classification and build their own classification maps.