https://github.com/e-marshall/itslive
Jupyter book tutorial demonstrating working with ITS_LIVE dataset
https://github.com/e-marshall/itslive
aws-s3 climate glaciology remote-sensing xarray
Last synced: 24 days ago
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Jupyter book tutorial demonstrating working with ITS_LIVE dataset
- Host: GitHub
- URL: https://github.com/e-marshall/itslive
- Owner: e-marshall
- Created: 2022-05-18T03:44:21.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2025-03-31T23:43:10.000Z (about 1 month ago)
- Last Synced: 2025-04-01T00:27:53.301Z (about 1 month ago)
- Topics: aws-s3, climate, glaciology, remote-sensing, xarray
- Language: Jupyter Notebook
- Homepage: https://e-marshall.github.io/itslive/intro.html
- Size: 226 MB
- Stars: 10
- Watchers: 3
- Forks: 4
- Open Issues: 5
-
Metadata Files:
- Readme: readme.md
- Contributing: Contributing.md
- Citation: CITATION.cff
Awesome Lists containing this project
README
# ITS_LIVE + Xarray Tutorial Jupyter Book
[](https://zenodo.org/badge/latestdoi/493498539)
[](https://e-marshall.github.io/itslive)
[](https://mybinder.org/v2/gh/e-marshall/itslive/HEAD?labpath=accessing_s3_data.ipynb)
❗❗This book is no longer maintained. Please see [cloud-open-source-geospatial-datacube-workflows](https://github.com/e-marshall/cloud-open-source-geospatial-datacube-workflows) instead.❗❗
The Inter-mission Time Series of Land Ice Velocity and Elevation ([ITS_LIVE](https://its-live.jpl.nasa.gov/)) is a dataset of global ice velocity measurements derived from displacement between pairs of satellite images generated by feature tracking algorithms. The dataset ingests NASA Landsat 7, 8, 9 and European Space Agency (ESA) Sentinel-1 & 2 image pairs and produces low-latency ice surface velocity data. It is available for access and download in multiple forms; this tutorial accesses the data stored as [Zarr](https://zarr.readthedocs.io/en/stable/index.html) data cubes in S3 (Amazon Simple Storage Service) buckets on AWS. Users are provided instructions outlining two ways to follow along with the tutorial material. One option is running the tutorial locally. We provide an environment.yml file to configure a local computing environment. Alternatively, the tutorial has a preconfigured JupyterLab environment hosted on www.mybinder.org that enables users to run the tutorial in the cloud with no requirement for local computational resources.
Thanks for visiting the github repo for this [tutorial](https://e-marshall.github.io/itslive/intro.html) demonstrating accessing + working with [ITS_LIVE](https://its-live.jpl.nasa.gov/) ice velocity data using [Xarray](https://xarray.dev/) and other python packages. If you have questions about the tutorial's content, please feel free to start a [Discussions](https://github.com/e-marshall/itslive/discussions) topic. If you find a bug or error, you can raise an [Issue](https://github.com/e-marshall/itslive/issues).