A skill that is sometimes overlooked in geoscience curricula is coding. Basic literacy in languages such as Python or Javascript can be useful for automating tedious tasks and can provide access to open source libraries that provide powerful data analysis and presentation tools, but often we do not include scripting in our courses.

The goal of this project is to develop an undergraduate-level satellite image analysis course that utilizes active learning actvities to present remote sensing concepts while introducing basic scripting: adding some unexpected content ("broccoli") to a course on another topic (our "mac and cheese"). By pairing introductory remote sensing concepts with in-class exercises requiring basic scripting skills, we provide students with an opportunity to gain knowledge in both. For example, topics such as extracting image metadata pair well with exploration of variable types, while selecting and processing images requires use of object methods and setting parameters.

Course exercises will be presented via interactive Python (Jupyter) notebooks. These include both code cells and formatted text (markdown cells). Each code cell can be run separately, allowing the instructor to provide nearly complete scripts with a few cells for the student to complete. Students can add notes directly to markdown cells and observe results as they make small changes to code cells. By using a cloud-based interpreter such as Google Colaboratory (or Colab: https://colab.research.google.com), we avoid the need to install applications. The only requirement needed to use Colab is a Google account, and it can be accessed in any modern web browser, avoiding some of the variability introduced by different operating systems. 

An additional resource we will utilize is Google Earth Engine (https://code.earthengine.google.com), which provides cloud-based access to datasets such as Landsat, Sentinel and USGS 3DEP DEM's via a scriptable interface. Although Earth Engine's native interface uses Javascript, it can also be accessed via a Python API, the functionality of which has been further extended by open source projects such as geemap (https://geemap.org).

While we don't expect students to master scripting through such limited exposure, this type of experience should help overcome anxiety about coding and  provide them with a  foundation to expand their skills, should they choose.