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 reach out to us on GitHub.
Featured GitHub Repos
This list was last updated on April 30, 2018
Here is a selection of some of our current repos. Make sure to explore the full list of tools on GitHub.
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, bookmark this repo because it includes exactly what you need to get started!
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.
This code package may be used for handling NEON geolocation data. It includes functions to extract spatial data from the API based on a named location, and to calculate more precise locations for select observational data products.
This repo includes an ENVI Extension for reading AOP HDF5 formatted files from our airborne remote sensing surveys of field sites.
Are you API savvy? This repo is a forum for users to share ideas and code related to NEON's data API.
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.
Another wrapper for using the NEON API in R, available from CRAN.