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  1. 3401

    Git 06: Sync GitHub Repos with Pull Requests

    Git 06: Sync GitHub Repos with Pull Requests This tutorial covers adding new edits or contents from your forked repo on github.com and a central repo. ## Learning Objectives At the end of this activity, you will be able to: Explain the concept of base 鈥�
  2. 3402

    Document & Publish Your Workflow: Jupyter Notebooks

    Document & Publish Your Workflow: Jupyter Notebooks In this tutorial we learn how to effectively and efficiently document and publish our workflows online. Learning Objectives At the end of this activity, you will be able to: Explain why documenting and 鈥�
  3. 3403

    Introduction to using Jupyter Notebooks

    Introduction to using Jupyter Notebooks Setting up Jupyter Notebooks You can set up your notebook in several ways. Here we present the Anaconda Python distribution method so as to follow the Data Institute set up instructions . Browser First, make sure 鈥�
  4. 3404

    Assignment: Reproducible Workflows with Jupyter Notebooks

    Assignment: Reproducible Workflows with Jupyter Notebooks In this tutorial you will learn how to open a .tiff file in Jupyter Notebook and learn about kernels. The goal of the activity is simply to ensure that you have basic familiarity with Jupyter 鈥�
  5. 3405

    The Importance of Reproducible Science

    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 鈥�
  6. 3406

    Document & Publish Your Workflow: R Markdown & knitr

    Document & Publish Your Workflow: R Markdown & knitr This tutorial we will work with the knitr and rmarkdown packages within RStudio to learn how to effectively and efficiently document and publish our workflows online. Learning Objectives At the end of 鈥�
  7. 3407

    Document Code with R Markdown

    Document Code with R Markdown You will need to have the rmarkdown and knitr packages installed on your computer prior to completing this tutorial. Refer to the setup materials to get these installed. Learning Objectives At the end of this activity, you 鈥�
  8. 3408

    Publish Code - From R Markdown to HTML with knitr

    Publish Code - From R Markdown to HTML with knitr In this tutorial, we will cover the R knitr package that is used to convert R Markdown into a rendered document (HTML, PDF, etc). Learning Objectives At the end of this activity, you will: Be able to 鈥�
  9. 3409

    Introduction to the National Ecological Observatory Network (NEON)

    Introduction to the National Ecological Observatory Network (NEON) Here we will provide an overview of the National Ecological Observatory Network (NEON). Please carefully read through these materials and links that discuss NEON鈥檚 mission and design. 鈥�
  10. 3410

    Install QGIS & HDF5View

    Install QGIS & HDF5View Install HDFView The free HDFView application allows you to explore the contents of an HDF5 file. To install HDFView: Click to go to the download page . From the section titled HDF-Java 2.1x Pre-Built Binary Distributions select the 鈥�
  11. 3411

    Data Institute: Install Required R Packages

    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鈥檛 get any error messages. Then, install the needed R packages. 鈥�
  12. 3412

    Install Git, Bash Shell, Python

    Install Git, Bash Shell, Python This page outlines the tools and resources that you will need to install Git, Bash and Python applications onto your computer as the first step of our Python skills tutorial series. Checklist Detailed directions to 鈥�
  13. 3413

    Install Git, Bash Shell, R & RStudio

    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 鈥�
  14. 3414

    Set up GitHub Working Directory - Quick Intro to Bash

    Set up GitHub Working Directory - Quick Intro to Bash Checklist Once you have Git and Bash installed, you are ready to configure Git. On this page you will: Create a directory for all future GitHub repositories created on your computer To ensure Git is 鈥�
  15. 3415

    Interactive Data Vizualization with R and Plotly

    Interactive Data Vizualization with R and Plotly Plotly - Interactive (and Online) Plots Plotly bills itself as "a collaborative platform for modern data science". You can use it to build interactive plots that can easily be shared with others (like the 鈥�
  16. 3416

    AG真人百家乐官方网站 Hyperspectral Remote Sensing Data

    AG真人百家乐官方网站 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 鈥�
  17. 3417

    Plot Spectral Signatures Derived from Hyperspectral Remote Sensing Data in HDF5 Format in R

    Plot Spectral Signatures Derived from Hyperspectral Remote Sensing Data in HDF5 Format in R Learning Objectives After completing this tutorial, you will be able to: Extract and plot a single spectral signature from an HDF5 file. Work with groups and 鈥�
  18. 3418

    Creating a Raster Stack from Hyperspectral Imagery in HDF5 Format in R

    Creating a Raster Stack from Hyperspectral Imagery in HDF5 Format in R In this tutorial, we will learn how to create multi (3) band images from hyperspectral data. We will also learn how to perform some basic raster calculations (known as raster math in 鈥�
  19. 3419

    Intro to Working with Hyperspectral Remote Sensing Data in HDF5 Format in R

    Intro to Working with Hyperspectral Remote Sensing Data in HDF5 Format in R In this tutorial, we will show how to read and extract NEON reflectance data stored within an HDF5 file using R. Learning Objectives After completing this tutorial, you will be 鈥�
  20. 3420

    Create a Canopy Height Model from Lidar-derived rasters in R

    Create a Canopy Height Model from Lidar-derived rasters in R A common analysis using lidar data are to derive top of the canopy height values from the lidar data. These values are often used to track changes in forest structure over time, to calculate 鈥�
  21. 3421

    The Basics of LiDAR - Light Detection and Ranging - Remote Sensing

    The Basics of LiDAR - Light Detection and Ranging - Remote Sensing LiDAR or Li ght D etection a nd R anging is an active remote sensing system that can be used to measure vegetation height across wide areas. This page will introduce fundamental LiDAR (or 鈥�
  22. 3422

    Plas.io: Free Online Data Viz to Explore LiDAR Data

    Plas.io: Free Online Data Viz to Explore LiDAR Data In this tutorial, we will explore LiDAR point cloud data using the free, online Plas.io viewer . Learning Objectives At the end of this tutorial, you will be able to: Visualize lidar point clouding using 鈥�
  23. 3423

    Going On The Grid -- An Intro to Gridding & Spatial Interpolation

    Going On The Grid -- An Intro to Gridding & Spatial Interpolation In this tutorial was originally created for an ESA brown-bag workshop. Here we present the main graphics and topics covered in the workshop. Additional Resources Learn more about LiDAR data 鈥�
  24. 3424

    What is a CHM, DSM and DTM? AG真人百家乐官方网站 Gridded, Raster LiDAR Data

    What is a CHM, DSM and DTM? AG真人百家乐官方网站 Gridded, Raster LiDAR Data LiDAR Point Clouds Each point in a LiDAR dataset has a X, Y, Z value and other attributes. The points may be located anywhere in space are not aligned within any particular grid. Representative 鈥�
  25. 3425

    Data Activity: Visualize Precipitation Data in R to Better Understand the 2013 Colorado Floods

    Data Activity: Visualize Precipitation Data in R to Better Understand the 2013 Colorado Floods Several factors contributed to extreme flooding that occurred in Boulder, Colorado in 2013. In this data activity, we explore and visualize the data for 鈥�

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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.