Interactive Analysis of Big Earth Data with Jupyter Notebooks

A short course given at EGU 2019 | 10 April 2019

Link to nbviewer

Outline

• Introducing Jupyter Notebooks - Data analysis made simple
• Data access with Jupyter Notebooks from different data repositories
• Introducing Jupyter widgets - Make your data analysis and visualisation interactive
• Jupyterlab, JupyterHub, ... - Getting to know the Jupyter environment

At the end of this short course

• you hopefully have an idea about the benefits of Jupyter notebooks and understand the Jupyter environment better
• you got an overview of different data platforms to retrieve large volumes of environmental data (meteorological, climate, Earth Observation)
• You got an overview of different python libraries to efficiently access and process Big Earth Data
• You were shown some options to make your analysis / visualization interactive

Required libraries:

• xarray
• cdsapi (requires registration)
• Earth Engine Python API (requires registration)
• Plotly (requires registration)
• widgets
• ipyleaflet

Links to open data repositories:

• Copernicus Climate Data Store
• Google Earth Engine
• Earth on AWS
• ECMWF Public datasets