Source:
National Ecological Observatory Network (NEON)

This tutorial series explain the background and necessary information for
working with temporal and spatial data in `R`

.

**R Skill Level:** Intermediate - you’ve got the basics of `R`

down but haven’t
worked with temporal or spatial data in `R`

before.

After completing this series, you will:

- know where to find external data
- understand the fundamentals of projection, coordinate reference system, and other spatial metadata to be able to work with spatial data
- know the scientific background material to ask questions related to
phenological data, including:
- NDVI (Normalized Difference Vegetation Index)
- PAR (Photosynthetically-active Radiation)

To complete the tutorial 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).

You can chose to install packages with each lesson or you can download all
of the necessary `R`

Packages now.

More on Packages in R - Adapted from Software Carpentry.

**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.

**Working with Spatio-temporal Data in R Series:** This tutorial series is
part of a larger spatio-temporal metaseries and Data Carpentry workshop.
Included series are
*Introduction to Spatial Data and Spatial Data Management*,
*Introduction to Working With Raster Data in R*,
*Introduction to Working With Vector Data in R*
and
*Introduction to Working With Time Series Data in Text Formats in R*.