Code Hub
NEON's data are often complex; working with data can be greatly simplified using software or code. We provide some code to get you started, like with our `neonUtilities` package for R, and also post links to code contributed by members of the community. The NEON-related code resources listed below 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 code resources that were created by and are managed by NEON 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.
Other code resources listed below are created by data users interested in sharing their code. If you have requests for coding resources, challenges with NEON data or ideas for creating NEON data-related code, we encourage you to learn more about how we categorize NEON-related code resources, and how you can submit your own code resources.
Code resources are provided at three tiers, differing in level of review by NEON:
| Tier 1: Community Contributed Code | Community contributed code is reviewed to determine that it is publicly available, generally comprehensible, and involves NEON data. Code functionality is not evaluated. |
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| Tier 2: NEON Certified Code | Certified code goes through a code review, to ensure it performs as described and without error. |
| Tier 3: NEON Production Code | Production code is used in NEON data processing pipelines, to generate NEON data products. It is the end product of a very long and careful development process. |
Search the table below to find code that might be useful for your project.
| Title | Description | Tier | Language | |
|---|---|---|---|---|
ecocomDPA flexible dataset design pattern for ecological community data to facilitate synthesis and reuse Tier 2: NEON certified code R language This R package provides tools to discover and work with biodiversity data that follow the ecocomDP design pattern, including wrapper functions to search for and download data from the NEON and EDI data portals. See O'Brien et al (2021) for an overview. See the GitHub repo for more information about the data model, tools to work with the data model, and information about planned enhancements and updates. Data products:
DP1.10003.001 | Breeding landbird point counts, DP1.10022.001 | Ground beetles sampled from pitfall traps, DP1.10043.001 | Mosquitoes sampled from CO2 traps, DP1.10058.001 | Plant presence and percent cover, DP1.10072.001 | Small mammal box trapping, DP1.10092.001 | Tick pathogen status, DP1.10093.001 | Ticks sampled using drag cloths, DP1.20107.001 | Fish electrofishing, gill netting, and fyke netting counts, DP1.20120.001 | Macroinvertebrate collection, DP1.20219.001 | Zooplankton collection, DP1.20163.001 | Periphyton, seston, and phytoplankton chemical properties
Contributor name:
Eric Sokol
License:
MIT
Related collection system:
AOS (Aquatic Observation System), TOS (Terrestrial Observation System)
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HemiPyA Python module for automated estimation of forest biophysical variables and uncertainties from digital hemispherical photographs. Tier 1: Community contributed code Python For details about HemiPy's algorithms for calculating leaf area index (LAI) and other biophysical metrics from hemispherical photos, see https://doi.org/10.1111/2041-210X.14199 Data products:
DP1.10017.001 | Digital hemispheric photos of plot vegetation
Contributor name:
Courtney Meier
License:
MIT
Related collection system:
TOS (Terrestrial Observation System)
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neonutilitiesAccess NEON data programmatically and stack downloaded files with this handy Python package. Tier 2: NEON certified code Python This package is available to install from PyPi (using pip). It includes functions for accessing and downloading NEON data via the API, including downloading remote sensing data by easting and northing coordinates, and a function to join (stack) the month-by-site files in tabular NEON data. Contributor name:
Claire Lunch
License:
GNU Affero General Public v3.0
Related collection system:
AIS (Aquatic Instrument System), AOP (Airborne Observation Platform), AOS (Aquatic Observation System), SAE (Surface Atmosphere Exchange), TIS (Terrestrial Instrument System), TOS (Terrestrial Observation System)
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neonUtilitiesAccess NEON data programmatically and stack downloaded files with this handy R package. Tier 2: NEON certified code R language This package is available to install directly through CRAN. It includes functions for accessing NEON data via the API, a function to join (stack) the month-by-site files in downloaded NEON data, and functions for more specialized data access and conversion, such as extracting flux data from the published HDF5 format and converting data to geoCSV format. Check out our handy cheat sheet! Contributor name:
Claire Lunch
License:
GNU Affero General Public v3.0
Related collection system:
AIS (Aquatic Instrument System), AOP (Airborne Observation Platform), AOS (Aquatic Observation System), SAE (Surface Atmosphere Exchange), TIS (Terrestrial Instrument System), TOS (Terrestrial Observation System)
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BatchPlanetBatchPlanet is an R package designed to automate workflows for downloading, processing, and visualizing remote sensing imagery in batch from the Planet API. Tier 1: Community contributed code R language BatchPlanet is an R package designed to automate workflows for downloading, processing, and visualizing remote sensing imagery in batch from the Planet API. Originally developed to study tree phenology, the package has been generalized for broader environmental applications. This package can retrieve and process reflectances at the coordinates of tagged NEON observations obtained using the geoNEON package (see vignette). Time series or phenological metrics generated with this package could be compared to NEON datasets such as plant phenology data (DP1.10055.001). Contributor name:
Yiluan Song
License:
MIT
Related collection system:
AOP (Airborne Observation Platform), AOS (Aquatic Observation System), TOS (Terrestrial Observation System)
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NEON tree crown areaCalculate crown area of woody plants as seen from above based on height and diameter measurements. Tier 1: Community contributed code R language The dataset NEON.DOM.SITE.DP1.10098.001 - Woody plant vegetation structure provides structure measurements, including height, canopy diameter, and stem diameter, as well as mapped position of individual woody plants. However, crowns can overlap and they can also be fully contained within other crowns. In this script, overlapping crown areas are assigned to the taller individual, or split among individuals with the same height. Crown areas of smaller individuals completely covered by taller individuals are omitted. Data products:
DP1.10098.001 | Vegetation structure
Contributor name:
Anna Schweiger
License:
MIT
Related collection system:
AOP (Airborne Observation Platform), TOS (Terrestrial Observation System)
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stageQCurveCalculates the Stage-Discharge Rating Curve for a Site and Water Year and creates a continuous discharge record from water level data. Tier 3: NEON production code R language Data products:
DP1.20048.001 | Discharge field collection, DP1.20267.001 | Gauge height, DP4.00130.001 | Continuous discharge, DP4.00133.001 | Stage-discharge rating curves
Contributor name:
Kaelin Cawley
License:
GNU Affero General Public v3.0
Related collection system:
AIS (Aquatic Instrument System), AOS (Aquatic Observation System)
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DeepForestDeepForest is a Python package for training and predicting ecological objects in airborne imagery. Tier 1: Community contributed code Python DeepForest is a Python package for training and predicting ecological objects in airborne imagery. It was originally developed for tree crown object detection using NEON AOP data and includes a tree detection model trained and evaluated entirely on data from across NEON. The software also provides tools for training and applying multi-class models for applications including species classification. Data products:
DP3.30010.001 | High-resolution orthorectified camera imagery mosaic
Contributor name:
Ethan White
License:
MIT
Related collection system:
AOP (Airborne Observation Platform)
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eddy4Reddy4R is a family of open-source packages for eddy-covariance (EC) raw data processing, analyses and modeling in the R Language. Tier 3: NEON production code R language As described in Metzger et al. (2017), eddy4R is being developed by NEON scientists with wide input from the scientific community. eddy4R currently consists of the three public packages eddy4R.base, eddy4R.stor, and eddy4R.qaqc, with several additional packages in preparation (including eddy4R.turb, eddy4R.ucrt and eddy4R.erf). Data products:
DP4.00200.001 | Bundled data products - eddy covariance
Contributor name:
Stefan Metzger
License:
GNU Affero General Public v3.0
Related collection system:
TIS (Terrestrial Instrument System)
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neonOSPerform common transformations on NEON observational data, including table joining and duplicate detection. Tier 2: NEON certified code R language This R package provides functions for standardized duplicate checking and table-joining for NEON observational data products. It uses published metadata from the variables files and Quick Start Guides to determine the correct handling for each data product. neonOS is available via CRAN. Contributor name:
Claire Lunch
License:
GNU Affero General Public v3.0
Related collection system:
AOS (Aquatic Observation System), TOS (Terrestrial Observation System)
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