Skip to main content
NSF NEON | Open Data to Understand our Ecosystems logo
Sign In

Main navigation

  • About Us
    • Overview
      • Spatial and Temporal Design
      • History
    • Management
    • Advisory Groups
      • Advisory Committee: STEAC
      • Technical Working Groups (TWGs)
    • FAQ
    • Contact Us
      • Field Offices
    • User Accounts
    • Staff

    About Us

  • Data & Samples
    • Data Portal
      • Explore Data Products
      • Data Availability Charts
      • Spatial Data & Maps
      • Document Library
      • API & GraphQL
      • Prototype Data
      • External Lab Data Ingest (restricted)
    • Samples & Specimens
      • Discover and Use NEON Samples
        • Sample Types
        • Sample Repositories
        • Sample Explorer
        • Megapit and Distributed Initial Characterization Soil Archives
        • Excess Samples
      • Sample Processing
      • Sample Quality
      • Taxonomic Lists
    • Collection Methods
      • Protocols & Standardized Methods
      • AIrborne Remote Sensing
        • Flight Box Design
        • Flight Schedules and Coverage
        • Daily Flight Reports
        • Camera
        • Imaging Spectrometer
        • Lidar
      • Automated Instruments
        • Site Level Sampling Design
        • Sensor Collection Frequency
        • Instrumented Collection Types
          • Meteorology
          • Phenocams
          • Soil Sensors
          • Ground Water
          • Surface Water
      • Observational Sampling
        • Site Level Sampling Design
        • Sampling Schedules
        • Observation Types
          • Aquatic Organisms
            • Aquatic Microbes
            • Fish
            • Macroinvertebrates & Zooplankton
            • Periphyton, Phytoplankton, and Aquatic Plants
          • Terrestrial Organisms
            • Birds
            • Ground Beetles
            • Mosquitoes
            • Small Mammals
            • Soil Microbes
            • Terrestrial Plants
            • Ticks
          • Hydrology & Geomorphology
            • Discharge
            • Geomorphology
          • Biogeochemistry
          • DNA Sequences
          • Pathogens
          • Sediments
          • Soils
            • Soil Descriptions
    • Data Notifications
    • Data Guidelines and Policies
      • Acknowledging and Citing NEON
      • Publishing Research Outputs
      • Usage Policies
    • Data Management
      • Data Availability
      • Data Formats and Conventions
      • Data Processing
      • Data Quality
      • Data Product Revisions and Releases
        • Release 2021
        • Release 2022
      • Externally Hosted Data

    Data & Samples

  • Field Sites
    • About Field Sites and Domains
    • Explore Field Sites
    • Site Management Data Product

    Field Sites

  • Impact
    • Observatory Blog
    • Case Studies
    • Spotlights
    • Papers & Publications
    • Newsroom
      • NEON in the News
      • Newsletter Archive

    Impact

  • Resources
    • Getting Started with NEON Data & Resources
    • Documents and Communication Resources
      • Papers & Publications
      • Document Library
      • Outreach Materials
    • Code Hub
      • Code Resources Guidelines
      • Code Resources Submission
      • NEON's GitHub Organization Homepage
    • Learning Hub
      • Science Videos
      • Tutorials
      • Workshops & Courses
      • Teaching Modules
      • Faculty Mentoring Networks
      • Data Education Fellows
    • Research Support and Assignable Assets
      • Field Site Coordination
      • Letters of Support
      • Mobile Deployment Platforms
      • Permits and Permissions
      • AOP Flight Campaigns
      • Excess Samples
      • Assignable Assets FAQs
    • Funding Opportunities

    Resources

  • Get Involved
    • Advisory Groups
    • Upcoming Events
    • Past Events
    • NEON Ambassador Program
    • Collaborative Works
      • EFI-NEON Ecological Forecasting Challenge
      • NCAR-NEON-Community Collaborations
    • Community Engagement
    • Work Opportunities
      • Careers
      • Seasonal Fieldwork
      • Postdoctoral Fellows
      • Internships
        • Intern Alumni
    • Partners

    Get Involved

  • My Account
  • Search

Search

Learning Hub

  • Science Videos
  • Tutorials
  • Workshops & Courses
  • Teaching Modules
  • Faculty Mentoring Networks
  • Data Education Fellows

Breadcrumb

  1. Resources
  2. Learning Hub
  3. Tutorials

Tutorials

Image
Banner for tutorials

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

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

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 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 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
Start Tutorial

Mask a Raster Using Threshold Values in Python

In this tutorial, we will learn how to remove parts of a raster based on pixel values using a mask we create.
Start Tutorial

Merging GeoTIFF Files to Create a Mosaic

30 minutes
Learn to merge multiple GeoTIFF files to great a larger area of interest.
Start Tutorial

Modeling phenology with the R package phenor

40 min
This tutorial explains how download and format data the model the phenology.
Start Tutorial

NEON AOP Hyperspectral Data in HDF5 format with Python - Flightlines

1 hour
Learn how to read NEON AOP hyperspectral flightline data using Python and develop skills to manipulate and visualize spectral data.
Start Tutorial

NEON AOP Hyperspectral Data in HDF5 format with Python - Tiled Data

1 hour
Learn how to read NEON AOP hyperspectral flightline data using Python and develop skills to manipulate and visualize spectral data.
Start Tutorial

NEON Domain and Site Shapefiles and Maps

20 minutes
Use files available on the NEON data portal and NEON API to create maps of NEON domains and sites.
Start Tutorial

Open HDF5 files with Python Sample Code

0.5 hours
This tutorial provides basic code for opening an HDF5 file in Python using the h5py, numpy, and matplotlib libraries.
Start Tutorial

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

0.5 Hours
Learn about LiDAR point cloud file formats .las and .laz. Explore LiDAR point cloud data using the free, online Plas.io viewer .

Pagination

  • First page
  • Previous page
  • Page 1
  • Page 2
  • Current page 3
  • Page 4
  • Page 5
  • Next page
  • Last page
NEON Logo

Follow Us:

Join Our Newsletter

Get updates on events, opportunities, and how NEON is being used today.

Subscribe Now

Footer

  • My Account
  • About Us
  • Newsroom
  • Contact Us
  • Terms & Conditions
  • Careers

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.