Description

How do geographers use geospatial technologies to observe the Earth’s surface?

How do geographers use this information to interpret changes in the global environment across space and time?

In this course we will learn how to work with large geographic datasets to explore patterns and changes to the Earth’s surface at local to global scales. Case studies will use remotely-sensed images to study land cover, climate, weather, wildfire, and other topics. Students will learn concepts, methods, and ethics for using a cloud-based geospatial analysis platform to process data, critically interpret workflows and results, and communicate findings with web maps and graphics.

As a textbook, we will mostly use A primer for Earth Engine, an open-source textbook that I am writing. The additional readings that I ask you to do will also be accessible online. The majority (if not entirety) of readings are short and drawn from the Earth Observatory collection.

The course is largely problem-based, where you learn by doing. I assume no previous experience with writing code or interpreting geographic images. I tend to introduce concepts through illustrations and activities before showing you how to implement the concepts by writing code. You will have many opportunities to practice applying the methods with support from peers and instructors before tackling the three independent problem (IP) sets, which function like exams in this course.

Throughout the course, we use Google Earth Engine, a cloud-based geographic information system that is free to use (for education and environmental applications). With a web browser and an internet connection, you should be able to use your personal laptop for all the problems in this course.