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.

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R programming (52)
Hierarchical Data Formats (HDF5) (11)
Spatial Data & GIS (22)
LiDAR (7)
Raster Data (11)
Remote Sensing (11)
Data Visualization (4)
Hyperspectral Remote Sensing (7)
Time Series (15)
Phenology (7)
Vector Data (6)
Metadata (1)
Git & GitHub (6)
(1) (1)

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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)

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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).

NEON Data Institute 2017

Our 2017 Institute focuses on remote sensing of vegetation using open source tools to promote reproducible science. The primary computing language of this Institute is Python. This Institute will be held Boulder, CO 19-24 June 2017.

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

Download the Data

This tutorial covers the data and set up the data directory you will need for the 2017 Institute on Remote Sensing.

Interactive Data Vizualization with R and Plotly

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.

Setup GitHub Working Directory - Quick Intro to Bash

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.