https://github.com/jwagemann/2017_pydata_tutorial

Hands-on tutorial on OGC web services and big climate data analysis.
https://github.com/jwagemann/2017_pydata_tutorial

climate-data geospatial-analysis jupyter-notebook ogc-services

Last synced: 4 months ago
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Hands-on tutorial on OGC web services and big climate data analysis.

• Host: GitHub
• URL: https://github.com/jwagemann/2017_pydata_tutorial
• Owner: jwagemann
• Created: 2017-05-02T16:03:03.000Z (about 9 years ago)
• Default Branch: master
• Last Pushed: 2019-03-15T09:08:05.000Z (over 7 years ago)
• Last Synced: 2024-06-11T19:39:44.712Z (about 2 years ago)
• Topics: climate-data, geospatial-analysis, jupyter-notebook, ogc-services
• Language: Jupyter Notebook
• Homepage:
• Size: 8.84 MB
• Stars: 8
• Watchers: 2
• Forks: 3
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Pydata Tutorial 2017 - Jupyter Notebooks for Geospatial Data Analysis

This tutorial was given during PyData London on 5 May 2017. 


Examples specifically from Climate Sciences show, how large volumes of geospatial data can be accessed processed and visualised  on-demand, with the help of standardised web services.  


The tutorial can be followed interactively via

https://jupyter.eofrom.space. 

UPDATE 2019: 

* the OGC service this tutorial gives as an example has unfortunately been switched off. However, the tutorial still gives an idea about how OGC WCS requests work.