Pipeline Tutorials¶
Tony Cannistra, with support from the ESIP Lab Incubator Program
Planet Snowcover is a project which takes advantage of diverse tools and methods. These tutorials are designed to introduce these methods via an interactive set of steps. Through these tutorials, a user will engage with the entire process of setting up infrastructure, acquiring and processing data, training the ML model, and evaluating performance for this particular snowcover identification task.
Though you can run these tutorials on your local computer, the computational environment is sufficiently complex (and dependent on your local hardware!) that we’ve created an easy-to-use set of cloud infrastructure components that you can use to run through these tutorials. For information on how to deploy these resources, check out the Deployment Guide.
⚠️ Note that GitHub Jupyter notebook rendering is often slow and buggy. If you’re just viewing these notebooks on the web, you may have better luck viewing them with NBViewer.
Tutorial Contents
- Airborne Snow Observatory Data Acquisition and Processing (
1_Acquire_ASO.ipynb, NBViewer Link) - Planet Labs Imagery Acquisition and Processing (
2_Planet_Ordering.ipynb, NBViewer Link) - …