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Install Git, Bash Shell, R & RStudio

This page outlines the tools and resources that you will need to get started working on the many R-based tutorials that NEON provides.

Checklist

This checklist includes the tools that need to be set-up on your computer. Detailed directions to accomplish each objective are below.

  • Install Bash shell (or shell of preference)
  • Install Git
  • Install R & RStudio

Bash/Shell Setup

Install Bash for Windows

  1. Download the Git for Windows installer.
  2. Run the installer and follow the steps below (these may look slightly different depending on Git version number):
    1. Welcome to the Git Setup Wizard: Click on "Next".
    2. Information: Click on "Next".
    3. Select Destination Location: Click on "Next".
    4. Select Components: Click on "Next".
    5. Select Start Menu Folder: Click on "Next".
    6. Adjusting your PATH environment: Select "Use Git from the Windows Command Prompt" and click on "Next". If you forgot to do this programs that you need for the event will not work properly. If this happens rerun the installer and select the appropriate option.
    7. Configuring the line ending conversions: Click on "Next". Keep "Checkout Windows-style, commit Unix-style line endings" selected.
    8. Configuring the terminal emulator to use with Git Bash: Select "Use Windows' default console window" and click on "Next".
    9. Configuring experimental performance tweaks: Click on "Next".
    10. Completing the Git Setup Wizard: Click on "Finish".

This will provide you with both Git and Bash in the Git Bash program.

Install Bash for Mac OS X

The default shell in all versions of Mac OS X is bash, so no need to install anything. You access bash from the Terminal (found in /Applications/Utilities). You may want to keep Terminal in your dock for this workshop.

Install Bash for Linux

The default shell is usually Bash, but if your machine is set up differently you can run it by opening a terminal and typing bash. There is no need to install anything.

Git Setup

Git is a version control system that lets you track who made changes to what when and has options for easily updating a shared or public version of your code on GitHub. You will need a supported web browser (current versions of Chrome, Firefox or Safari, or Internet Explorer version 9 or above).

Git installation instructions borrowed and modified from Software Carpentry.

Git for Windows

Git should be installed on your computer as part of your Bash install.

Git on Mac OS X

Video Tutorial

Install Git on Macs by downloading and running the most recent installer for "mavericks" if you are using OS X 10.9 and higher -or- if using an earlier OS X, choose the most recent "snow leopard" installer, from this list. After installing Git, there will not be anything in your /Applications folder, as Git is a command line program.

**Data Tip:** If you are running Mac OSX El Capitan, you might encounter errors when trying to use git. Make sure you update XCODE. Read more - a Stack Overflow Issue.

Git on Linux

If Git is not already available on your machine you can try to install it via your distro's package manager. For Debian/Ubuntu run sudo apt-get install git and for Fedora run sudo yum install git.

Setting Up R & RStudio

Windows R/RStudio Setup

  • Please visit the CRAN Website to download the latest version of R for windows.
  • Run the .exe file that was just downloaded
  • Go to the RStudio Download page
  • Download the latest version of Rstudio for Windows
  • Double click the file to install it

Once R and RStudio are installed, click to open RStudio. If you don't get any error messages you are set. If there is an error message, you will need to re-install the program.

Mac R/RStudio Setup

  • Go to CRAN and click on Download R for (Mac) OS X
  • Select the .pkg file for the version of OS X that you have and the file will download.
  • Double click on the file that was downloaded and R will install
  • Go to the RStudio Download page
  • Download the latest version of Rstudio for Mac
  • Once it's downloaded, double click the file to install it

Once R and RStudio are installed, click to open RStudio. If you don't get any error messages you are set. If there is an error message, you will need to re-install the program.

Linux R/RStudio Setup

  • R is available through most Linux package managers. You can download the binary files for your distribution from CRAN. Or you can use your package manager (e.g. for Debian/Ubuntu run sudo apt-get install r-base and for Fedora run sudo yum install R).
  • To install RStudio, go to the RStudio Download page
  • Under Installers select the version for your distribution.
  • Once it's downloaded, double click the file to install it

Once R and RStudio are installed, click to open RStudio. If you don't get any error messages you are set. If there is an error message, you will need to re-install the program.

Data Institute: Install Required R Packages

R and RStudio

Once R and RStudio are installed (in Install Git, Bash Shell, R & RStudio ), open RStudio to make sure it works and you don’t get any error messages. Then, install the needed R packages.

Install/Update R Packages

Please make sure all of these packages are installed and up to date on your computer prior to the Institute.

  • install.packages(c("raster", "rasterVis", "rgdal", "rgeos", "rmarkdown", "knitr", "plyr", "dplyr", "ggplot2", "plotly"))
  • The rhdf5 package is not on CRAN and must be downloaded directly from Bioconductor. The can be done using these two commands directly in your R console.
    • #install.packages("BiocManager")
    • #BiocManager::install("rhdf5")

Install QGIS & HDF5View

Install HDFView

The free HDFView application allows you to explore the contents of an HDF5 file.

To install HDFView:

  1. Click to go to the download page.

  2. From the section titled HDF-Java 2.1x Pre-Built Binary Distributions select the HDFView download option that matches the operating system and computer setup (32 bit vs 64 bit) that you have. The download will start automatically.

  3. Open the downloaded file.

  • Mac - You may want to add the HDFView application to your Applications directory.
  • Windows - Unzip the file, open the folder, run the .exe file, and follow directions to complete installation.
  1. Open HDFView to ensure that the program installed correctly.
**Data Tip:** The HDFView application requires Java to be up to date. If you are having issues opening HDFView, try to update Java first!

Install QGIS

QGIS is a free, open-source GIS program. Installation is optional for the 2018 Data Institute. We will not directly be working with QGIS, however, some past participants have found it useful to have during the capstone projects.

To install QGIS:

Download the QGIS installer on the QGIS download page here. Follow the installation directions below for your operating system.

Windows

  1. Select the appropriate QGIS Standalone Installer Version for your computer.
  2. The download will automatically start.
  3. Open the .exe file and follow prompts to install (installation may take a while).
  4. Open QGIS to ensure that it is properly downloaded and installed.

Mac OS X

  1. Select KyngChaos QGIS download page. This will take you to a new page.
  2. Select the current version of QGIS. The file download (.dmg format) should start automatically.
  3. Once downloaded, run the .dmg file. When you run the .dmg, it will create a directory of installer packages that you need to run in a particular order. IMPORTANT: read the READ ME BEFORE INSTALLING.rtf file!

Install the packages in the directory in the order indicated.

  1. GDAL Complete.pkg
  2. NumPy.pkg
  3. matplotlib.pkg
  4. QGIS.pkg - NOTE: you need to install GDAL, NumPy and matplotlib in order to successfully install QGIS on your Mac!
**Data Tip:** If your computer doesn't allow you to open these packages because they are from an unknown developer, right click on the package and select Open With >Installer (default). You will then be asked if you want to open the package. Select Open, and the installer will open.

Once all of the packages are installed, open QGIS to ensure that it is properly installed.

LINUX

  1. Select the appropriate download for your computer system.
  2. Note: if you have previous versions of QGIS installed on your system, you may run into problems. Check out
this page from QGIS for additional information. 3. Finally, open QGIS to ensure that it is properly downloaded and installed.

The Importance of Reproducible Science

Verifiability and reproducibility are among the cornerstones of the scientific process. They are what allows scientists to "stand on the shoulder of giants". Maintaining reproducibility requires that all data management, analysis, and visualization steps behind the results presented in a paper are documented and available in full detail. Reproducibility here means that someone else should either be able to obtain the same results given all the documented inputs and the published instructions for processing them, or if not, the reasons why should be apparent. From Reproducible Science Curriculum

## Learning Objectives At the end of this activity, you will be able to:
  • Summarize the four facets of reproducibility.
  • Describe several ways that reproducible workflows can improve your workflow and research.
  • Explain several ways you can incorporate reproducible science techniques into your own research.

Getting Started with Reproducible Science

Please view the online slide-show below which summarizes concepts taught in the Reproducible Science Curriculum.

View Reproducible Science Slideshow

A Gap In Understanding

Image of a Twitter post submitted by Tracy Steal highlighting the obstacles slowing adoption of reproducible science pratices. These are: People are unaware there is a problem, 100% reproducibility is hard, One workflow does not fit all, Lack of motivation, and are scared of intial time investments.
Obstacles slowing adoption of reproducible science practices. Source: Reproducible Science Curriculum

Reproducibility and Your Research

Graphic showing the spectrum of reproducibility for published research. From left to right, left being not reproducible and right being the gold standard, we have publication only, publication plus code, publication plus code and data, publication with linked and executable code and data, and full replication.
Reproducibility spectrum for published research. Source: Peng, RD Reproducible Research in Computational Science Science (2011): 1226–1227 via Reproducible Science Curriculum

How reproducible is your current research?

View Reproducible Science Checklist

**Thought Questions:** Have a look at the reproducible science check list linked, above and answer the following questions:
  • Do you currently apply any of the items in the checklist to your research?
  • Are there elements in the list that you are interested in incorporating into your workflow? If so, which ones?

Additional Readings (optional)

  • Nature has collated and published (with open-access) a special archive on the Challenges of Irreproducible Science .
  • The Nature Publishing group has also created a Reporting Checklist for its authors that focuses primaily on reporting issues but also includes sections for sharing code.
  • Recent open-access issue of Ecography focusing on reproducible ecology and software packages available for use.
  • A nice short blog post with an annotated bibliography of "Top 10 papers discussing reproducible research in computational science" from Lorena Barba: Barba group reproducibility syllabus.

About Hyperspectral Remote Sensing Data

Learning Objectives

After completing this tutorial, you will be able to:

  • Define hyperspectral remote sensing.
  • Explain the fundamental principles of hyperspectral remote sensing data.
  • Describe the key attributes that are required to effectively work with hyperspectral remote sensing data in tools like R or Python.
  • Describe what a "band" is.

Mapping the Invisible

About Hyperspectral Remote Sensing Data

The electromagnetic spectrum is composed of thousands of bands representing different types of light energy. Imaging spectrometers (instruments that collect hyperspectral data) break the electromagnetic spectrum into groups of bands that support classification of objects by their spectral properties on the earth's surface. Hyperspectral data consists of many bands -- up to hundreds of bands -- that cover the electromagnetic spectrum.

The NEON imaging spectrometer collects data within the 380nm to 2510nm portions of the electromagnetic spectrum within bands that are approximately 5nm in width. This results in a hyperspectral data cube that contains approximately 426 bands - which means big, big data.

Key Metadata for Hyperspectral Data

Bands and Wavelengths

A band represents a group of wavelengths. For example, the wavelength values between 695nm and 700nm might be one band as captured by an imaging spectrometer. The imaging spectrometer collects reflected light energy in a pixel for light in that band. Often when you work with a multi or hyperspectral dataset, the band information is reported as the center wavelength value. This value represents the center point value of the wavelengths represented in that band. Thus in a band spanning 695-700 nm, the center would be 697.5).

Graphic showing an example of how bands or regions of visible light, within the electromagnetic spectrum, are devided when captured by imaging spectrometers.
Imaging spectrometers collect reflected light information within defined bands or regions of the electromagnetic spectrum. Source: National Ecological Observatory Network (NEON)

Spectral Resolution

The spectral resolution of a dataset that has more than one band, refers to the width of each band in the dataset. In the example above, a band was defined as spanning 695-700nm. The width or spatial resolution of the band is thus 5 nanometers. To see an example of this, check out the band widths for the Landsat sensors.

Full Width Half Max (FWHM)

The full width half max (FWHM) will also often be reported in a multi or hyperspectral dataset. This value represents the spread of the band around that center point.

Graphic showing an example of the Full Width Half Max value of a band. The full width half band value is determined by the relative distance in nanometers between the band center and the edge of the band.
The Full Width Half Max (FWHM) of a band relates to the distance in nanometers between the band center and the edge of the band. In this case, the FWHM for Band C is 5 nm.

In the illustration above, the band that covers 695-700nm has a FWHM of 5 nm. While a general spectral resolution of the sensor is often provided, not all sensors create bands of uniform widths. For instance bands 1-9 of Landsat 8 are listed below (Courtesy of USGS)

Band Wavelength range (microns) Spatial Resolution (m) Spectral Width (microns)
Band 1 - Coastal aerosol 0.43 - 0.45 30 0.02
Band 2 - Blue 0.45 - 0.51 30 0.06
Band 3 - Green 0.53 - 0.59 30 0.06
Band 4 - Red 0.64 - 0.67 30 0.03
Band 5 - Near Infrared (NIR) 0.85 - 0.88 30 0.03
Band 6 - SWIR 1 1.57 - 1.65 30 0.08
Band 7 - SWIR 2 2.11 - 2.29 30 0.18
Band 8 - Panchromatic 0.50 - 0.68 15 0.18
Band 9 - Cirrus 1.36 - 1.38 30 0.02

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The National Ecological Observatory Network is a major facility fully funded by the U.S. National Science Foundation.

Any opinions, findings and conclusions or recommendations expressed in this material do not necessarily reflect the views of the U.S. National Science Foundation.