Primer on Raster Data in R feature image Source: LiDAR data collected over Grand Mesa, Colorado - National Ecological Observatory Network (NEON)
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Series: Primer on Raster Data in R

The tutorials in this series introduces working with raster data in R.
The series introduces the concepts through videos, graphical examples, and text.

Data used in this series are from the National Ecological Observatory Network (NEON) and are in GeoTiff and .csv formats.

If you enjoy this series, we also recommend the more in depth Introduction to Working With Raster Data in R series. The Introduction to Working With Spatio-Temporal Data and Data Management series provides more background and foundational information on understanding and working with spatial data.

Things You’ll Need To Complete This Series

Setup RStudio

To complete some of the tutorials in this series, you will need an updated version of R and, preferably, RStudio installed on your computer.

R is a programming language that specializes in statistical computing. It is a powerful tool for exploratory data analysis. To interact with R, we strongly recommend RStudio, an interactive development environment (IDE).

Download Data

All tutorials in this series use data from the San Joaquin Experimental Range, a NEON field site.

Download NEON Teaching Data Subset: Field Site Spatial Data

These remote sensing data files provide information on the vegetation at the National Ecological Observatory Network’s San Joaquin Experimental Range and Soaproot Saddle field sites. This data is intended for educational purposes, for access to all the data for research purposes visit the NEON Data Portal.


Set Working Directory: This lesson assumes that you have set your working directory to the location of the downloaded and unzipped data subsets. An overview of setting the working directory in R can be found here.

R Script & Challenge Code: NEON data lessons often contain challenges that reinforce learned skills. If available, the code for challenge solutions is found in the downloadable R script of the entire lesson, available in the footer of each lesson page.

Tutorials in the Series