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  1. Resources
  2. Learning Hub
  3. Tutorials

Tutorials

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Looking to improve your data skills using tools like R or Python? Want to learn more about working with a specific NEON data product? NEON develops online tutorials to help you improve your research. These self-paced tutorials are designed for you to used as standalone help on a single topic or as a series to learn new techniques.

Code for all script based tutorials can be downloaded at the end of the tutorial. Original files can also be found on GitHub.

All materials are freely available for you to use and reuse. We suggest the following citation for tutorials: 
[AUTHOR(S), NEON (National Ecological Observatory Network)]. Data Tutorial: [TUTORIAL NAME]. [URL] (accessed [DATE OF ACCESS]). See Citation Guidelines for examples, and for guidance in citing data and code.

Tutorials

Start Tutorial

Hierarchical Data Formats - What is HDF5?

0.25 - 0.5 Hours
An brief introduction to the Hierarchical Data Format 5 (HDF5) file/data model. Learn about how HDF5 is structured and the benefits of using HDF5.
Start Tutorial

Hyperspectral Variation Uncertainty Analysis in Python

0.5 hour
Learn to analyze the difference between rasters taken a few days apart to assess the uncertainty between days.
Start Tutorial

Image Raster Data in R - An Intro

30 minutes
This tutorial explains the fundamental principles, functions and metadata that you need to work with raster data, in image format, in R. Topics include raster stacks, raster bricks, plotting RGB images and exporting an RGB image to a GeoTIFF.
Start Tutorial

Install & Set Up Docker For Use With eddy4R

1 hour
This tutorial provides the basic steps for setting up and using Docker to work with the eddy4R R package in a Docker container.
Start Tutorial

Install Git, Bash Shell, Python

1 hour
This page outlines the tools and resources that you will need to
Start Tutorial

Install Git, Bash Shell, R & RStudio

1.0 - 1.5 Hours
This page outlines the tools and resources that you will need to complete the Data Institute activities.
Start Tutorial

Install QGIS & HDF5View

1.0 - 1.5 Hours
Start Tutorial

Installing & Updating Packages in R

30 minutes
This tutorial provides the basics of installing and working with packages in R.
Start Tutorial

Interacting with the PhenoCam Server using phenocamapi R Package

0.5 hrs
Learn the basics of how to extract PhenoCam data and metadata through the Phenocam API
Start Tutorial

Interactive Data Vizualization with R and Plotly

30 minutes
Learn the basics of how to use the plotly package to create interactive plots and use the Plotly API in R to share these plots.
Start Tutorial

Intro to Vector Data in R

The data tutorials in this series cover how to open, work with and plot with vector-format spatial data (points, lines and polygons) in R. Additional, topics include working with spatial metadata (extent and coordinate reference system), working with spatial attributes and plotting data by attributes.
Series
6 part series
Start Tutorial

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

1.0 - 1.5 Hours
Open up and explore a hyperspectral dataset stored in HDF5 format in
Start Tutorial

Introduction to AOP Data in Google Earth Engine (GEE)

20 minutes
Introductory tutorial on exploring AOP datasets in GEE.
Start Tutorial

Introduction to AOP Hyperspectral Data in GEE

30 minutes
Read in and visualize Surface Directional Reflectance data at NEON site SRER
Start Tutorial

Introduction to AOP Public Datasets in Google Earth Engine (GEE)

20 minutes
Introductory tutorial on exploring AOP Image Collections in Earth Engine.
Start Tutorial

Introduction to HDF5 Files in R

1.0 - 1.5 Hours
Learn how to build a HDF5 file in R from scratch! Add groups, datasets and attributes. Read data out from the file.
Start Tutorial

Introduction to Hierarchical Data Format (HDF5) - Using HDFView and R

In this series we cover what a HDF5 format is, and how to open, read, create HDF5 files in R. We also cover extracting and plotting data from HDF5 files.
Series
7 part series
Start Tutorial

Introduction to Hyperspectral Remote Sensing Data

In this series, we cover the basics of working with NEON hyperspectral remote sensing data. We cover the principles of hyperspectral data, how to open hyperspectral data stored in HDF5 format in R and how to extract bands and create rasters in GeoTiff format.
Finally we explore extracting a hyperspectral - spectral signature from one pixel using R.
Series
6 part series
Start Tutorial

Introduction to Light Detection and Ranging (LiDAR) – Explore Point Clouds and Work with LiDAR Raster Data in R

In this series we cover the basics of lidar data including 3 key lidar data products - the Canopy Height Model, Digital Surface Model (DSM) and the Digital Terrain Model (DTM). We explore lidar point clouds using the free, online 3d point cloud viewer. Finally, we cover working with LiDAR derived rasters in R.
Series
6 part series
Start Tutorial

Introduction to NEON API in Python

1 hour
Use the NEON API in Python, via requests package and json package.
Start Tutorial

Introduction to NEON Discrete Lidar Data in Python

45 minutes - 1 hour
Programmatically download lidar data and metadata and explore discrete lidar point clouds and rasters in Python
Start Tutorial

Introduction to NEON Remote Sensing Data in Google Earth Engine

This series walks new GEE users through working with AOP datasets in Earth Engine, including JavaScript workflows for visualizing and analyzing AOP data.
Series
5 part series
Start Tutorial

Introduction to NEON soil sensor data

1 hour
Create a time series plot of soil temperature, moisture, and CO<sub>2</sub> concentrations
Start Tutorial

Introduction to Small Mammal Data

1.5 hrs
This tutorial will provide an introduction to discovering, accessing and preparing NEON small mammal collection data using R
Start Tutorial

Introduction to the National Ecological Observatory Network (NEON)

1.0 Hour
This page provides an overview of NEON and the data provided by NEON for use with NEON workshops and Data Institutes.
Start Tutorial

Introduction to using Jupyter Notebooks

1 hour
This tutorial cover how to use Jupyter Notebooks to document code.
Start Tutorial

Introduction to working with NEON eddy flux data

1 hour
Download and navigate NEON eddy flux data, including basic transformations and merges
Start Tutorial

Introduction to working with PhenoCam Images

This series provides instruction on how to work with phenocam images, including those from NEON sites. Many of the techniques can be applied to any repeat RGB photography.
Series
4 part series
Start Tutorial

Introduction to Working with Raster Data in R

A series of data tutorials that teach you how to open, plot and perform basic calculations on raster data in R. It also covers key spatial attributes associated with raster data include extent, projection and resolution. Finally we cover dealing with missing and bad data when working with remote sensing imagery.
Series
8 part series
Start Tutorial

Introduction to Working With Time Series Data in Text Formats in R

The tutorials in this series cover how to open, work with and plot with phenology-related micrometeorological data in R. Additional topics include working with time and date classes (e.g., POSIXct, POSIXlt, and Date), subsetting time series data by date and time and created facetted or tiles sets of plots.
Series
8 part series

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Copyright © Battelle, 2019-2020

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

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