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.


Build & Work With Functions in R

This tutorial teaches the basics of creating a function in R.

Vector 01: Explore Shapefile Attributes & Plot Shapefile Objects by Attribute Value in R

This tutorial provides an overview of how to locate and query shapefile attributes as well as subset shapefiles by specific attribute values in R. It also covers plotting multiple shapefiles by attribute and building a custom plot legend.

Raster 00: Intro to Raster Data in R

This tutorial reviews the fundamental principles, packages and metadata/raster attributes that are needed to work with raster data in R. It covers the three core metadata elements that we need to understand to work with rasters in R: CRS, Extent and Resolution. It also explores missing and bad data values as stored in a raster and how R handles these elements. Finally, it introduces the GeoTiff file format.

Vector 03: When Vector Data Don't Line Up - Handling Spatial Projection & CRS in R

This tutorial will cover how to identify the CRS of a spatial vector object in R. It will also explore differences in units associated with different projections and how to reproject data using spTransform in R. Spatial data need to be in the same projection in order to successfully map and process them in non-gui tools such as R.

Vector 05: Crop Raster Data and Extract Summary Pixels Values From Rasters in R

This tutorial covers how to modify (crop) a raster extent using the extent of a vector shapefile. It also covers extracting pixel values from defined locations stored in a spatial object.


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