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]

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Create a Canopy Height Model from LiDAR-derived Rasters in R

0.5 Hours
In this tutorial, you will bring LiDAR-derived raster data (DSM and DTM) into R to create a canopy height model (CHM).

The Basics of LiDAR - Light Detection and Ranging - Remote Sensing

0.25 Hours
Explore the basics of how a LiDAR system works and what a LiDAR system measures.

Extract Values from a Raster in R

0.5 Hours
Learn to extract data from a raster using circular or square buffers created around a x,y location or from a shapefile. With this will will learn to convert x,y locations in a .csv file into a SpatialPointsDataFrame so that they can be

Plas.io: Free Online Data Viz to Explore LiDAR Data

0.25 - 0.5 Hours
Learn about LiDAR point cloud file formats .las and .laz. Explore LiDAR point cloud data using the free, online Plas.io viewer .

What is a CHM, DSM and DTM? About Gridded, Raster LiDAR Data

0.25 - 0.5 Hours
Understand LiDAR data product formats and learn the basics of how a LiDAR data are processed.

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