Assignment: Reproducible Workflows with R Markdown

Table of Contents

This tutorial covers the NEON Pre-Institute Week 3 assignment. If you already are familiar with R Markdown and knitr, you may be able to complete the assignment without working through the tutorials.

Deadlines

Due: Please submit your activity R Markdown and HTML files to the NEONScience/DI-NEON-participants GitHub repo as a pull request by 11:59pm on 16 June 2016.

Download Data

Download NEON Teaching Data Subset: TEAK-Data Institute 2016

The LiDAR and imagery data used to create this raster teaching data subset were collected over the National Ecological Observatory Network's (NEON) Lower Teakettle field site and processed at NEON headquarters. The entire dataset can be accessed by request from the NEON Data Portal.

To begin, please do the following:

  1. Download data from the Lower Teakettle field site - from the NEON Data Skills Figshare repository.
  2. Unzip the data into (or transfer the unzipped data into) a data directory on your computer. The path to your data will look like this:

~Documents\data\NEONDI-2016\

The data directory with the TEAK teaching data subset. This is the suggested organization for all Data Institute teaching data subsets. Source: National Ecological Observatory Network (NEON)

We will be using the GeoTIFF raster files in the lidar subdirectory of the teaching data subset.

Create R Markdown File

The three tutorials in this series walk you through how to create, edit, and knit R Markdown files. The components of the finished RMD and HTML files should include:

  • A .Rmd file that will be knit to an HTML output.
  • Your name as an author of the file.
  • At the top of the .Rmd file, add your bio and project summary that you wrote and submitted in Week 2 as a .md file. Please update your project summary if you have changes.

  • In the RMD file, create a script that does the following:

    • Open and plot at least 2 raster files in the lidar directory using the plot() function in the raster R package.
    • Create a histogram for each raster file that shows the distribution of values in the file.
    • All plots should be labelled appropriately.
  • Include 3 or more named R code chunks.
  • OPTIONAL: Code chunk options in at least 1 chunk, e.g.warnings = FALSE.
  • Break up your code into R Markdown chunks that makes sense to you. Use Markdown syntax to document the steps that you are taking to "process" the data. Provide some summary discussion of the results at the end of the document. HINT: the raster TEAK_lidarCHM represents tree height for the field site. You might comment on how tall the trees are on average at the site.

Knitr: RMD to HTML

Once you have completed the steps above:

  • Knit your .Rmd file to HTML.
  • Submit both the .Rmd and the .html documents to the /participants/pre-institute3-rmd directory in the NEONScience/DI-NEON-participants GitHub repository.

Supporting Materials

If you would like a primer on plotting raster files in R, visit the NEON Data Skills tutorial series: Plot Raster Data in R.

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