Tutorials | NSF NEON | Open Data to Understand our Ecosystems

Open HDF5 files with Python Sample Code

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

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

0.25 - 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 .

Series

6 part series

Start Tutorial

Plot a Spectral Signature in Python - Tiled Data

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

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

Series

8 part series

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.

Series

6 part series

Start Tutorial

Plotting a NEON RGB Camera Image (GeoTIFF) in Python

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.

Start Tutorial

Publish Code - From R Markdown to HTML with knitr

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

Series

3 part series

Start Tutorial

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

Start Tutorial

Raster 00: Intro to Raster Data in R

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.

Series

8 part series

Start Tutorial

Raster 01: Plot Raster Data in R

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.

Series

8 part series

Start Tutorial

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

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.

Series

8 part series

Start Tutorial

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

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.

Series

8 part series

Start Tutorial

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

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.

Series

8 part series

Start Tutorial

Raster 05: Raster Time Series Data in R

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.

Series

3 part series

Start Tutorial

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

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.

Series

3 part series

Start Tutorial

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

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.

Series

3 part series

Start Tutorial

Raster Data in R - The Basics

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

Series

5 part series

Start Tutorial

Resources for Learning R

A brief overview of available resource to get started learning R.

Series

4 part series

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.

Series

6 part series

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.

Series

5 part 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.

Series

7 part series

Start Tutorial

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

0.25 Hours

Explore the basics of how a LiDAR system works and what a LiDAR system measures.

Series

6 part series

Start Tutorial

The Importance of Reproducible Science

1.0 Hour

This page outlines the tools and resources that you will need to complete the Data Institute activities.

Start Tutorial

The Relationship Between Raster Resolution, Spatial Extent & Number of Pixels

Learn about the key attributes needed to work with raster data in non-GUI programs. Examples in R.

Series

5 part series

Start Tutorial

Time Series 00: Intro to Time Series Data in R - Managing Date/Time Formats & Simple Plots using ggplot2

This tutorial will demonstrate how to import a time series dataset stored in .csv format into R. It will explore data classes and will walk through how to convert date data, stored as a character string, into a date class that R can recognize and plot efficiently.

Series

8 part series

Start Tutorial

Time Series 01: Why Metadata Are Important: How to Work with Metadata in Text & EML Format

This tutorial covers what metadata are, and why we need to work with metadata. It covers the 3 most common metadata formats: text file format, web page format and Ecological Metadata Language (EML).

Series

8 part series

Start Tutorial

Time Series 02: Dealing With Dates & Times in R - as.Date, POSIXct, POSIXlt

This tutorial explores working with date and time classes in R. We will overview the differences between As.Date, POSIXct and POSIXlt as used to convert a date/time field in character (string) format to a date-time format that is recognized by R. This conversion supports efficient plotting, subsetting and analysis of time series data.

Series

8 part series