Getting Started

Overview

The notebooks in the Scaling Python on GCP repository are used to demonstrate how to scale Python on GCP for image processing on satellite data. Specifically, these notebooks compute the normalized difference vegetation index (NDVI) on Landsat 8 satellite images using XArray and Dask.

Thanks to the open data policies of USGS and NASA, the Landsat dataset is available for free as part of the Google Public Cloud Data program. It can be used by anyone as part of Google Cloud.

Using Dask at multiple scales, including GCP

The notebooks for this use case exercise Dask and XArray at three different scales:

1. Small-scale computations on a laptop (10s of satellite images)
2. Medium-scale computations on a virtual machine (100s of satellite images)
3. Large-scale computations on a Kubernetes cluster (1,000s of satellite images)

Additional resources

Refer to the respective projects and documentation for more information about Dask, XArray, Dask Kubernetes, GCP, and the publicly available Landsat data on GCP.