Earth Observation Data Analysis
Overview
This unit will give students experience with developing data processing and analysis pipelines for Earth Observation (EO) satellite data. Through hands-on examples involving real-world data, students will learn how to obtain EO imagery and combine it with other georeferenced datasets, how to explore research questions using EO satellite imagery, and how to develop a software pipeline to process, transform, and visualise EO data. Students will work within Python and will become familiar with important GIS software such as the Digital Earth Australia Sandbox, Google Earth Engine, GeoPandas, Xarray, and Folium.
Requisites
16-November-2025
15-November-2026
Unit learning outcomes
Students who successfully complete this unit will be able to:
- Draw on knowledge of fundamental theoretical Earth Observation (EO) satellite concepts to inform selection of appropriate EO satellites, instruments, and bands
- Apply knowledge of available EO datasets to extract, transform, and validate satellite imagery
- Critically evaluate existing Geographic Information System (GIS) software and EO data sources, and construct custom algorithms when necessary
- Build software pipelines capable of visualising EO satellite data and use it to explore real-world research questions
- Identify research questions and manage EO projects
Teaching methods
Hawthorn
| Type | Hours per week | Number of weeks | Total (number of hours) |
|---|---|---|---|
| On-campus Class | 5.20 | 5 weeks | 26 |
| Online Directed Online Learning and Independent Learning | 2.00 | 3 weeks | 6 |
| Unspecified Activities Independent Learning | 19.00 | 6 weeks | 114 |
| TOTAL | 146 |
Assessment
| Type | Task | Weighting | ULO's |
|---|---|---|---|
| Assignment 1 | Individual | 10 - 30% | 1,2,3,4 |
| Assignment 2 | Individual | 10 - 30% | 1,2,3,4,5 |
| Assignment 3 | Individual | 10 - 30% | 1,2,3,4,5 |
| Weekly Exercises | Individual | 30 - 60% | 1,2,3,4,5 |
Content
- Fundamental theoretical concepts related to satellite EO data.
- Intermediate data science techniques relevant for creating EO data pipelines.
- Working with EO data platforms such as Digital Earth Australia and Google Earth Engine.
- Best practices for developing data processing and analysis pipelines for EO satellite imagery.
- Coordinate reference systems and associated transformations.
- Interactive mapping and working with layers in Folium.
- Time-series analysis and change mapping.
- How to investigate real-world research questions using EO data.
Study resources
Reading materials
A list of reading materials and/or required textbooks will be available in the Unit Outline on Canvas.