Five Guiding Principles to Make Jupyter Notebooks Fit for Earth Observation Data Education

Five Guiding Principles to Make Jupyter Notebooks Fit for Earth Observation Data Education

There is a growing demand to train Earth Observation (EO) data users in how to access and use existing and upcoming data. A promising tool for data-related training is computational notebooks, which are interactive web applications that combine text, code and computational output. Here, we present t...

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Bibliographic Details
Main Authors: Julia Wagemann, Federico Fierli, Simone Mantovani, Stephan Siemen, Bernhard Seeger, Jörg Bendix
Format: Article
Language:English
Published: MDPI AG 2022-07-01
Series:Remote Sensing
Subjects:
Earth Observation data
training
atmospheric composition
computational notebooks
Jupyter
Python
Online Access:https://www.mdpi.com/2072-4292/14/14/3359

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https://www.mdpi.com/2072-4292/14/14/3359

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