EDS 220, Working With Environmental Data

Instructor

Samantha Stevenson
sstevenson@ucsb.edu

Office Hours: Tuesday 2-3pm, Bren Hall 3412
if this time does not work for you, please let me know and we can schedule something else!

Important Links

Course Syllabus and Code of Conduct

Course Github Repository

Recommendations for avoiding Git merge conflicts

Installing Google Earth Engine on your local machine

Readings/Resources

There is no required textbook for this course. However, there are some excellent (free!) online books covering some of our course material, which make good references if something is confusing:

An Introduction to Earth and Environmental Data Science (online textbook using Python)

Earth Observation Using Python: A Practical Programming Guide (PDF textbook)

Use Data for Earth and Environmental Science in Open Source Python

Learning Objectives

The goal of EDS 220 (Working With Environmental Datasets) is to provide MEDS students with the skills needed to efficiently locate, process, and manipulate the diverse sets of data encountered in environmental data science. Since these datasets are constantly evolving and encompass an enormous number of possible data sources, this course CANNOT provide a background in every possible source of data! But it will provide a grounding in best practices for searching and downloading datasets, as well as workflows for quality control and common postprocessing steps.

By the end of the course, students should be able to:

• Locate Environmental Datasets on major cloud computing platforms (Google Earth Engine) and API servers
• Read In Datasets from these platforms onto a local machine
• Perform Quality Control as needed, including infilling or interpolation of missing data
• Subset/Aggregate Data according to the needs of a given application (spatial/temporal averaging, upsampling, etc)
• Visualize Data including through creation of georeferenced maps, time series, and other basic metrics
• Describe Data Pros/Cons: which datasets are most appropriate for a given application, and why?
• Work with Peers to create use case examples for datasets, and communicate to the rest of the class.

Course Schedule (subject to change)