Working With Raster Time Series Data in R
The tutorials in this series cover how to open, work with and plot raster time series data in
R. This series includes only the more-advanced, time-series
specific tutorials that are also part of the
Introduction to Working With Raster Data in R series.
Data used in this series cover NEON Harvard Forest and San Joaquin Experimental Range field sites and are in GeoTIFF and .csv formats.
After completing the series you will:
- Raster 05
- Understand the format of a time series raster dataset.
- Know how to work with time series rasters.
- Be able to efficiently import a set of rasters stored in a single directory.
- Be able to plot and explore time series raster data using the
- Raster 06
- Be able to assign custom names to bands in a RasterStack for prettier plotting.
- Understand advanced plotting of rasters using the
- Raster 07
- Be able to extract summary pixel values from a raster.
- Know how to save summary values to a .csv file.
- Be able to plot summary pixel values using
- Have experience comparing NDVI values between two different sites.
Things You’ll Need To Complete This Series
To complete the tutorial series you will need an updated version of
preferably, RStudio installed on your computer.
is a programming language that specializes in statistical computing. It is a
powerful tool for exploratory data analysis. To interact with
R, we strongly
an interactive development environment (IDE).
Install R Packages
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.
Working with Raster Time Series Data in R Tutorial Series: This tutorial is part of a series on
working with raster data in R.
It is part also of a
Data Carpentry workshop
on using spatio-temporal in R. Other related series include: intro to spatio-temporal data and data management, working with vector data in R, and working with tabular time series data in R.