Landsat ML Cookbook
This Project Pythia Cookbook covers the essential materials for working with Landsat data in the context of machine learning workflows.
Once you complete this cookbook, you will have the skills to access, resample, regrid, reshape, and rescale satellite data, as well as the foundation for applying machine learning to it. You will also learn how to interactively visualize your data at every step in the process.
This cookbook is broken up into two main sections - “Foundations” and “Example Workflows.”
The foundational content includes:
Start Here - Introduction to Landsat data
Data Ingestion - Planetary Computer - Demonstrating a method for loading and accessing Landsat data from Microsoft’s platform
Data Ingestion - Intake - Demonstrating approaches for data access using Intake
Preprocessing - Regrid - Demonstrating common preprocessing approaches such as regridding
Running the Notebooks
You can either run the notebook using Binder or on your local machine.
Running on Binder
The simplest way to interact with a Jupyter Notebook is through Binder, which enables the execution of a Jupyter Book in the cloud. The details of how this works are not important for now. All you need to know is how to launch a Pythia Cookbooks chapter via Binder. Simply navigate your mouse to the top right corner of the book chapter you are viewing and click on the rocket ship icon, (see figure below), and be sure to select “launch Binder”. After a moment you should be presented with a notebook that you can interact with. I.e. you’ll be able to execute and even change the example programs. You’ll see that the code cells have no output at first, until you execute them by pressing Shift+Enter. Complete details on how to interact with a live Jupyter notebook are described in Getting Started with Jupyter.
Running on Your Own Machine
If you are interested in running this material locally on your computer, you will need to follow this workflow:
Clone the Landsat ML Cookbook repository:
git clone https://github.com/ProjectPythia/landsat-ml-cookbook.git
Move into the
Create and activate your conda environment from the
conda env create -f environment.yml conda activate landsat-ml-cookbook
Move into the
notebooksdirectory and start up Jupyterlab
cd notebooks/ jupyter lab