Data Tutorials

Looking to improve your data skills using tools like R or Python? Want to learn more about working with a specific NEON data product? NEON develops online tutorials to help you improve your research. These self-paced tutorials are designed for you to used as standalone help on a single topic or as a series to learn new techniques.

Code for all script based tutorials can be downloaded at the end of the tutorial. Original files can also be found on GitHub.

All material are freely available for you to use and reuse. We suggest the following citation:

[AUTHOR(S)]. Data Tutorial:[TUTORIAL NAME]. Accessed:[DATE OF ACCESS]. National Ecological Observatory Network, Battelle, Boulder, CO, USA. [URL]


Band Stacking, RGB & False Color Images, and Interactive Widgets in Python - Flightline Data

Learn to efficiently work with flightline NEON AOP spectral data using functions.

Calculate NDVI & Extract Spectra Using Masks in Python - Flightline Data

Learn to calculate Normalized Difference Vegetation Index (NDVI) and extract spectral using masks with Python from NEON flighline AOP hyperspectral data products.

Plot a Spectral Signature in Python - Flightline Data

Learn how to extract and plot a spectral profile from a single pixel of a reflectance band using the NEON flightline hyperspectral data.

Document & Publish Your Workflow: Jupyter Notebooks

This tutorial introduces the importance of tools supporting documenting & publishing a workflow using the Python kernel of Jupyter Notebooks.

Assignment: Reproducible Workflows with Jupyter Notebooks

This page details how to complete the assignment for pre-Institute week 3 on documenting your code with Jupyter Notebooks.


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