This repository has the practical sessions that will demonstrate the fundamentals of remote sensing. The notebooks complement the weekly lectures and are set to follow them as closely as possible.
We will use Google Earth Engine as the main platform, but be aware that there are other platforms that are equally capable (e.g. Geoscience Australia's Digital Earth Australia, Microsoft's Planetary Computer).
- Professor Marta Yebra
- Mr Chad Burton
- Dr Nicolas Younes
- You must have a gmail account to access Google Earth Engine.
- You must request access to Google Earth Engine. Follow this link to do it.
🚀 This course can be run in a GitHub CodeSpace cloud instance by clicking the badge below. The session will contain all the necessary python libraries and the notebooks and code in this repo.
Tip
Allow CodeSpaces a few minutes to bootup and for all python libraries to install.
To open Jupyterlab within the default VSCode session (if you perfer that IDE), in the terminal run jupyter lab --no-browser --NotebookApp.token='', and jupyter lab will open in a seperate browser tab. Note, you may have to disable any pop-up blockers in your browser.
Warning
When you open a Codespace, the compute time is billed to your own GitHub account (using your free monthly allowance or any paid plan you may have). Free users get 120 compute hours per month. The compute size set up for this repo is 2 cores, 8 GB RAM, 15 GB of storage. On a free account, this means you have 60 free hours of usage per month.
The requirements.txt describes the necessary python libraries to run the notebooks in this repository. The Virtual_env_instructions.md describe how to create a python virtual environment on the NCI.
Refer to Wattle site or https://programsandcourses.anu.edu.au/2023/course/ENGN3903
Office Hours: Zoom/Teams and by appointment Class questions / discussion: Wattle (add site)
Each folder contains the practical notebooks for a given week.
Refer to Wattle)