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Author: e-marshall

readme.md

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 [![Jupyter Book Badge](https://jupyterbook.org/badge.svg)](https://e-marshall.github.io/itslive)
 [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/e-marshall/itslive/HEAD?labpath=accessing_s3_data.ipynb)
 
+The Inter-mission Time Series of Land Ice Velocity and Elevation (ITS_LIVE) [@Gardner et al:2022] 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 [@Miles et al:2020] 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. 
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 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).