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Dask for Geospatial Analysis: Efficient Parallel Workflows for Satellite Imagery in Sherlock Online
This event is part of Love Data Week at Stanford, an annual festival highlighting topics, opportunities and services relevant to data in research.
This workshop will provide an introduction to Dask in Python for satellite image analysis on distributed systems at scale. We will learn workflows for accessing Earth Observation satellite imagery from NASA as we learn to interact efficiently with images that are larger than the onboard memory of a single chip, build and run custom functions targeted at only the pixels needed for our analysis goals, and process targeted, machine learning ready datasets from these images with the help of Dask's parallelization and distributed data capabilities. This workshop is aimed at researchers who have intermediate Python experience or higher, and all levels of experience (beginner-advanced) with HPC computing.
Access to Sherlock is required to participate fully in the session.
- Date:
- Thursday, February 12, 2026
- Time:
- 1:00pm - 2:00pm
- Time Zone:
- Pacific Time - US & Canada (change)
- Location:
- Branner Earth Sciences Library
- Categories:
- Love Data Week
- Online:
- This is an online event. Event URL will be sent via registration email.