Code Resources

The NEON project provides a wide array of open access data from automated instrument measurements, to observational data to airborne remote sensing data. Working with different types of data presents various challenges depending on the experience users have working with large and varied datasets. Creation and sharing of code resources both supports open science and enables a greater diversity of users to work more easily with data. Learn more about code resources being created by NEON and the NEON user community to use our data.

NEON Code Resources

NEON code resources are designed to make working with all NEON data easier, to perform common algorithms on select data products, and to share the code used to generate select  data products. Most NEON code resources can be found in the NEONScience GitHub organization. The code is free and open access to download and utilize. The code found in the NEONScience GitHub organization is published and maintained by NEON project scientists.

NEON also collaborates with data users to identify and facilitate the creation of coding resources. If you have requests for coding resources, challenges with NEON data or ideas for creating NEON data-related code, we encourage you to contact us.

Featured Code Packages

This list was last updated on November 5, 2018

Super Easy R Stacker Script for Beginners

Are you a beginner R user? This super, simple R script is perfect for data users who want to stack NEON data but are not that familiar with working in R. Using only three lines of code, you will be able to combine multiple months & sites of NEON data downloaded as a .zip file from the NEON data portal. Please note that this script will only work for NEON data products that are delivered as zipped folders of .csv files (most OS and IS data products but not AOP data products).   



If you’ve downloaded data from the portal, you will have discovered that the data download by individual month and site. The first thing you will want to do is “stack” or join those files together. Well, this is the package you want because it includes exactly what you need to get started! You can even use function in the package to directly access NEON data and bypass the portal. This package is available to install directly through CRAN

The neonUtilities R package contains a function to join (stack) the month-by-site files in downloaded NEON data, plus additional functions to convert data to geoCSV format, and to download data from the API through R.

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Use R to handle NEON geolocation data including extracting spatial data from the API based on a named location, and calculating more precise locations for select observational data products.

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Read AOP HDF5 formatted files from our airborne remote sensing surveys in ENVI.

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Are you API savvy? Share ideas and code related to NEON's data API with other coders..

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Community-Contributed Code Resources

The community also creates and shares code and resources to work with NEON data.  While the list of community-created coding resources is extensive, we highlight a few of the more popular resources below.


Access meteorological data from a growing database that contains metadata for >100,000 stations from 219 countries or territories worldwide — including all NEON sites.

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Phenocam & Repeat Photography 

The PhenoCam Network develops and hosts a variety of tools to work with phenocam and other repeat photography images. Tools have been developed in R, Python and interactive GUIs. The tools include: 

  • phenocamapi R package: Access and work with NEON phenocam data (phenology images,  DP1.00033.001; land-water interface images, DP1.20002.001; snow depth and understory phenology images, DP1.00042.001) from the Phenocam Network directly to your R workspace or computer.
  • xROI R package: Delineate Region of Interests (ROI's) and extract time series data from the image. 
  • phenocamr and phenor R packages: Provide phenology modelling tools. 

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Check out more resources from NEONScience on GitHub.

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