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xcube as a platform for spatiotemporal data analysis and visualization (Python tutorials)

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xcube as a platform for spatiotemporal data analysis and visualization (Python tutorials)
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17
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CC Attribution - NonCommercial - NoDerivatives 3.0 Germany:
You are free to use, copy, distribute and transmit the work or content in unchanged form for any legal and non-commercial purpose as long as the work is attributed to the author in the manner specified by the author or licensor.
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Production PlaceWageningen

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Xcube is an open-source xarray-based Python package and toolkit that has been developed to provide Earth observation (EO) data in an analysis-ready form to users. xcube achieves this by carefully converting EO data sources into self-contained data cubes that can be published in the cloud. In this session you will learn about the ecosystem around xcube, which allows to access different data sources and turning the inputs into data cubes. These data cubes can then be easily used for spatiotemporal data analysis and visualization. After a brief introduction about the software components, we will go step by step though some example Jupyter notebooks and finally we will dive into a hands-on session with a little challenge. For the session you will need a laptop with an internet connection, some basic knowledge about Python and already installed miniconda (https://docs.conda.io/en/latest/miniconda.html) which is used to download the necessary Python packages for the session. Prior experience with Jupyter notebooks will be helpful, but not mandatory.