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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

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 .
Start Tutorial

Plot a Spectral Signature in Python - Tiled Data

0.5 hours
Learn how to extract and plot a spectral profile from a single pixel of a reflectance band using NEON tiled hyperspectral data.
Start Tutorial

Plot Continuous & Discrete Data Together

30 minutes
This tutorial discusses ways to plot plant phenology (discrete time series) and single-aspirated temperature ((near-)continuous time series) together.
Start Tutorial

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

1.0 - 1.5 Hours
Extract a single pixel's worth of spectra from a hyperspectral dataset stored in HDF5 format in R. Visualize the spectral signature.
Start Tutorial

Plotting a NEON RGB Camera Image (GeoTIFF) in Python

0.5 hour
This lesson is a brief introduction to RGB camera images and the GeoTIFF raster format in Python.
Start Tutorial

Plotting and Clustering Megapit Soils Data

45 minutes
Learn to download, analyze, and visualize NEON soils data.
Start Tutorial

Primer on Raster Data in R

This series provides a brief primer on raster spatial data in R.
Series
5 part series
Start Tutorial

Publish Code - From R Markdown to HTML with knitr

30 minutes
This tutorial introduces how to use the R knitr package to publish from R Markdown files to HTML (or other) file format.
Start Tutorial

Quantifying The Drivers and Impacts of Natural Disturbance Events – The 2013

4 hours
This teaching module demonstrates ways that scientists identify and use
Start Tutorial

Random Forest Species Classification using AOP and TOS data in GEE

1 hour
Classifying species using AOP and observational field data at CLBJ
Start Tutorial

Raster 00: Intro to Raster Data in R

1 hour
This tutorial reviews the fundamental principles, packages and metadata/raster attributes that are needed to work with raster data in R. It covers the three core metadata elements that we need to understand to work with rasters in R: CRS, Extent and Resolution. It also explores missing and bad data values as stored in a raster and how R handles these elements. Finally, it introduces the GeoTiff file format.
Start Tutorial

Raster 01: Plot Raster Data in R

30 minutes
This tutorial explains how to plot a raster in R using R's base plot function. It also covers how to layer a raster on top of a hillshade to produce an eloquent map.
Start Tutorial

Raster 02: When Rasters Don't Line Up - Reproject Raster Data in R

30 minutes
This tutorial explores issues associated with working with rasters in different Coordinate Reference Systems (CRS) & projections. When two rasters are in different CRS, they will not plot nicely together on a map. We will learn how to reproject a raster in R using the projectRaster function in the raster package.
Start Tutorial

Raster 03: Raster Calculations in R - Subtract One Raster from Another and Extract Pixel Values For Defined Locations

30 minutes
This tutorial covers how to subtract one raster from another using efficient methods - the overlay function compared to basic subtraction. We also cover how to extract pixel values from a set of locations - for example a buffer region around plot locations at a field site. Finally, it explains the basic principles of writing functions in R.
Start Tutorial

Raster 04: Work With Multi-Band Rasters - Image Data in R

1 hour
This tutorial explores how to import and plot a multi-band raster in R. It also covers how to plot a three-band color image using the plotRGB function in R.
Start Tutorial

Raster 05: Raster Time Series Data in R

30 minutes
This tutorial covers how to work with and plot a raster time series, using an R RasterStack object. It also covers the basics of practical data quality assessment of remote sensing imagery.
Start Tutorial

Raster 06: Plot Raster Time Series Data in R Using RasterVis and Levelplot

30 minutes
This tutorial covers how to efficiently and effectively plot a stack of rasters using rasterVis package in R. Specifically it covers using levelplot and adding meaningful, custom names to band labels in a RasterStack.
Start Tutorial

Raster 07: Extract NDVI Summary Values from a Raster Time Series

30 minutes
This tutorial covers how to extract and plot NDVI pixel values from a raster time series stack in R. We will use ggplot2 to plot our data.
Start Tutorial

Raster Data in R - The Basics

1 hour
This tutorial explains the fundamental principles, functions and metadata that you need to work with raster data in R.
Start Tutorial

Relating Reflectance Indices to Flux Data

120 minutes
Explore the relationship between NDVI in the flux footprint and NEE. This tutorial is designed as a data exercise for Flux Course.
Start Tutorial

Resources for Learning R

20 minutes
A brief overview of available resource to get started learning R.
Start Tutorial

Select pixels and compare spectral signatures in R

0.5 Hours
Plot and comapre the spectral signatures of multiple different land cover types using an interactive click-to-extract interface to select pixels.
Start Tutorial

Set up GitHub Working Directory - Quick Intro to Bash

1.0 - 1.5 Hours
This page reviews how to check that github is installed on your computer. It also provides a quick overview of Bash shell. Finally, we will setup a working GitHub directory.
Start Tutorial

Spatial Data Tutorial Series Capstone Challenges

0.5 - 1.0 Hours
This page contains capstone activities that complement several spatial data tutorial series.
Start Tutorial

Subsetting NEON HDF5 hyperspectral files to reduce file size

1.0 Hour
Take a large NEON hyperspectral HDF5 file and extract only the information that you need, then save as a new HDF5 file. For an example, we will take an existing hyperspectral dataset (~600Mb) and reduce it in size for subsequent tutorials.

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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.