Welcome to the NEON Data Skills Portal!  feature image Source: National Ecological Observatory Network (NEON)


Devoted to open data and open source in science and education.

View All Tutorials


R programming (52)
Hierarchical Data Formats (HDF5) (15)
Spatial Data & GIS (22)
LiDAR (10)
Raster Data (14)
Remote Sensing (24)
Data Visualization (4)
Hyperspectral Remote Sensing (17)
Time Series (15)
Phenology (7)
Vector Data (6)
Metadata (1)
Git & GitHub (7)
(1) (1) (13)

Tutorial by R Package

dplyr (7)
ggplot2 (16)
h5py (2)
lubridate (time series) (6)
maps (1)
maptools (1)
plyr (2)
raster (26)
rasterVis (raster time series) (3)
rgdal (GIS) (24)
rgeos (2)
rhdf5 (11)
sp (5)
scales (4)
gridExtra (4)
ggtheme (0)
grid (2)
reshape2 (3)
plotly (5)

View ALL Tutorial Series

Twitter Youtube Github


R Bloggers

Welcome to the NEON Data Skills Portal!

This site contains data lessons, background materials and other resources that support working with large spatio-temporal datasets, like those offered by the NEON project.

We welcome any comments and feedback that you have and also materials that support or expand upon what’s available on this site!

Upcoming Events

NEON @ ESA: Using the NEON API

Learn to use the NEON API! The National Ecological Observatory Network (NEON) provides an Application Programming Interface (API); this workshop will guide you through using the API to access NEON data in R.

NEON @ ESA: Working with Time Series in R using NEON Data

This 5-hr workshop is taught at the 2017 meeting of the Ecological Society of America (ESA) in Portland, OR. Learn fundamental skills in R needed to work with and plot time series data in text format including data.frames, converting text format timestamps to an R date or datetime (e.g. POSIX) class, and aggregating data across different time scales (e.g. hourly vs month).

Get Started With Our Data Tutorial Series!

Intro to Raster Data in R Series

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.

Total tutorials: 8

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.

Total tutorials: 6

Tabular Time Series Data 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.

Total tutorials: 9

3 Newest Data Tutorials

Document & Publish Your Workflow: Jupyter Notebooks

This tutorial introduces the importance of tools supporting documenting & publishing a workflow using the Python kernel of Jupyter Notebooks.

Exploring Uncertainty in LiDAR Data

Learn to analyze the several NEON level 3 LIDAR rasters to assess the uncertainty between days.

Classify a Raster Using Threshold Values in Python

Learn how to read NEON lidar raster GeoTIFFs (e.g., CHM, Slope, Aspect) into Python numpy arrays with gdal and create a classified raster object.