Geospatial Analysis with Google Earth Engine

In the era of big data, researchers now have access to worldwide datasets from NASA and other research entities. Many datasets have been made accessible from Google Earth Engine (GEE), but the native tools for working with GEE require workflows that are less reproducible, less familiar to most natural resources programmers, and not easily integrated into larger programming projects. This course will focus on bringing GEE datasets into a Python workflow to more easily integrate the data acquisition process into geospatial analysis projects in a reproducible manner, on any operating system, using open-source software. This course will model how to set up a geospatial analysis project workflow that can serve as a template for future projects. We will learn common geospatial data types and programming control flow techniques, how to download and save geospatial data from GEE, how to convert between formats, and how to use Python modules to enhance or speed up geospatial analysis techniques commonly employed manually in other software packages.

Learn at your own pace with instructor support (see Online Course Format Chart below for details).

Fall: October 14, 2025 – January 4, 2026 (Early bird ends September 14th)

*Early bird saves $75

Basic experience with GIS; basic experience in Python (e.g., from CWS’ Python Boot Camp); and a Google Earth Engine account.

Module 1: Getting Started with Python and GEE

• Create and manage a Python environment

• Create, edit, and manage Jupyter Lab notebooks

• Distinguish between and create data structures available in Python

• Construct control flow operations in Python

• Import and access functions in Python modules

• Distinguish between GEE data structures

• Load datasets from the GEE catalog

Module 2: Viewing, Manipulating, and Exporting GEE data

• Perform server-side filtering, summarization, and joining operations

• Download GEE data structures as files

• Create static and interactive maps using GEE data structures

Module 3: Arithmetic and Comparison Operations

• Perform calculations on Images using arithmetic operations

• Detect changes between Images using comparison operations

• Remap Image values to reclassify data

Module 4: Advanced Image Analysis

• Perform classification of Images using the ee.Classifier and ee.Clusterer submodules.

• Calculate aspect, hillshade, slope, and related metrics using elevation data.

• Perform classification of aerial imagery using the geoAI module.

• Perform complex raster and vector analysis techniques using the whitebox module.

FORMAT:

3 months of access to course materials as you work at your own pace

Get instructor support for the 3-month term via email, discussion threads, group meetings, and one-on-one appointments

After working through the course materials, set up an optional meeting with the instructor to discuss your own personal project from work or school

CONTINUING EDUCATION:

16 CEUs with The Wildlife Society

CERTIFICATIONS:

Earn 1 credit toward certification as an Associate/Certified Wildlife Biologist® (at any level) with The Wildlife Society

FORMAT:

12 months of access to course materials as you work at your own pace

Get instructor support for the 3-month term via email, discussion threads, group meetings, and one-on-one appointments

After working through the course materials, set up an optional meeting with the instructor to discuss your own personal project from work or school

CONTINUING EDUCATION:

16 CEUs with The Wildlife Society

Go to our Continuing Education Page for more details

CERTIFICATIONS:

Earn 1 credit toward certification as an Associate/Certified Wildlife Biologist® (at any level) with The Wildlife Society

ACADEMIC CREDIT:

Earn 1 academic credit (go to our Academic Credit Page for details)

Earn an additional 1-2 academic credits with an Applied Project