wekeo4oceans is a repository of Python based tools to introduce you to marine/ocean data on the WEkEO DIAS (Data Information and Access System) and its Jupyter Lab. The content includes notebooks explaining WEkEO and the Jupyter Lab environment and how to use the Harmonised Data Access (HDA) API that is fundamental to WEkEO. Within this repository are tutorials and case studies, using data from the Copernicus Programme that are available on WEkEO and written by expert trainers from Mercator Ocean International, ECMWF and EUMETSAT.
The content provided is mostly based on Jupyter Notebooks, which allow a high-level of interactive learning, as code, text description and visualisation is combined in one place.
The notebooks contained within the repository feature data from the OLCI, SLSTR and SRAL sensors aboard the Sentinel-3 satellite.
The content of this repository is suitable for those completely new to WEkEO, Python, Copernicus data and hosted processing environments.
Below is a summary of the files provided, with recommendations on where to start:
If you are on GitHub/Lab you can visit www.wekeo.eu, register for an account and enter the JupyterLab - then follow the instructions below.
If you are currently on the WEkEO JupyterLab you're already in the right place and can start. To clone this repository in to the WEkEO JupyterLab environment open a terminal in the WEkEO JupyterLab, type
cd work
git clone --recurse-submodules https://github.com/wekeo/wekeo4oceans.git
This will create a clone of this repository of notebooks in the work directory on your Jupyterlab instance. You can use the same command to clone any external repository you like.
You can also use this code on your own computer/Jupyter Lab server, however you won't have the fast access provided by the Harmonized Data Access as part of the WEkEO infrastructure.
This repository supports Python 3.9. We highly recommend that users working on their own systems install the appropriate Anaconda distribution for their operating system. Here is a link to the Anaconda distribution of Python 3.9.
Python allows users to create specific environments that suit their applications. The tutorials included in this collection require a number of non-standard packages - by which we refer to those no included by default in Anaconda. These are included in the JupyterLab environment but you may need to install them for local working. You can create the environment locally using the supplied environment.yml file.