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Cited by 1,728Plant Water Relations and Carbon DynamicsEnvironmental Monitoring and Data ManagementAtmospheric and Environmental Gas Dynamics

The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

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Pastorello, Gilberto, Trotta, Carlo, Canfora, Eleonora, Chu, Housen, Christianson, Danielle, Cheah, You-Wei, Poindexter, Cristina, Chen, Jiquan +281 more·2020·Scientific Data
DOI 10.1038/s41597-020-0534-3PMC PMC7347557
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Abstract

The FLUXNET2015 dataset provides ecosystem-scale data on CO 2 , water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.

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  • Random forest and XGBoost models using the spatial average of HLS bands across each image and MERRA-2 data represent state-of-the-art approaches.

    “The random forest and XGBoost models use the spatial average of HLS bands across each image and the MERRA-2 data, representing the state-of-the-art approaches [44].”

    From Prithvi-EO-2.0: A Versatile Multitemporal Foundation Model for Earth Observation Applications (2026) · cites this paper as [44]

    The Data Processing Methods > Meteorological products section describes gap-filling with Marginal Distribution Sampling and ERA-Interim, not the models or inputs in the claim. Searches for random forest, XGBoost, HLS bands, MERRA-2, and related terms found no passage addressing whether those models are state-of-the-art. (LLM, conf=0.75)

    Experimental — accuracy not yet measured

  • Random forest and XGBoost baselines use spatial averages of HLS image tiles (1.5 × 1.5 km2) around the tower location, which reflect the current state-of-the-art eddy covariance upscaling approaches using coarse-resolution satellite data.

    “Both random forest and XGBoost baselines use spatial averages of HLS image tiles (1.5 × 1.5 km 2 ) around the tower location, which reflect the current state-of-the-art eddy covariance upscaling approaches using coarse-resolution (e.g., 500 m to 5 km) satellite data [44], [49].”

    From Prithvi-EO-2.0: A Versatile Multitemporal Foundation Model for Earth Observation Applications (2026) · cites this paper as [44]

    The Background & Summary describes eddy-covariance tower footprints and regional-to-global use of tower data, but does not describe satellite-based upscaling. Searches for HLS tiles, random forest, XGBoost, spatial averaging, and coarse-resolution satellite data found no passage supporting the approach attributed to this source. The paper passages have section labels but no page numbers. (LLM, conf=0.76)

    Experimental — accuracy not yet measured

  • Challenges of scale mismatches between in-situ measurements and satellite data, as well as generalization issues, could potentially be mitigated by using foundation models like Prithvi-EO that embed generalized representations of high-resolution data.

    “However, these approaches face challenges due to scale mismatches between in-situ measurements and satellite data, as well as generalization issues, which could potentially be mitigated by using foundation models like Prithvi-EO that embed generalized representations of high-resolution data [44].”

    From Prithvi-EO-2.0: A Versatile Multitemporal Foundation Model for Earth Observation Applications (2026) · cites this paper as [44]

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Research works printed but not linked: 249

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  158. [166]Valentini R 2016 FLUXNET2015 IT-Ro1 Roccarespampani 1 FLUXNET; University of Tuscia - Vietrbo 10.18140/flx/1440174 · DOI
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  163. [171]Kotani A 2016 FLUXNET2015 JP-MBF Moshiri Birch Forest Site FLUXNET; Nagoya University 10.18140/flx/1440238 · DOI
  164. [172]Kotani A 2016 FLUXNET2015 JP-SMF Seto Mixed Forest Site FLUXNET; Nagoya University 10.18140/flx/1440239 · DOI
  165. [173]Kosugi Y Takanashi S 2016 FLUXNET2015 MY-PSO Pasoh Forest Reserve (PSO) FLUXNET; FRIM(Forest Research Institute of Malaysia); Kyoto University 10.18140/flx/1440240 · DOI
  166. [174]Dolman H 2016 FLUXNET2015 NL-Hor Horstermeer FLUXNET; Vrije Universiteit Amsterdam 10.18140/flx/1440177 · DOI
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  169. [177]Wolf S Eugster W Buchmann N 2016 FLUXNET2015 PA-SPs Sardinilla-Pasture FLUXNET; ETH Zurich 10.18140/flx/1440179 · DOI
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  171. [179]Dolman H 2016 FLUXNET2015 RU-Cok Chokurdakh FLUXNET; Vrije Universiteit Amsterdam 10.18140/flx/1440182 · DOI
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  184. [192]Goldstein A 2016 FLUXNET2015 US-Blo Blodgett Forest FLUXNET; University of California, Berkeley 10.18140/flx/1440068 · DOI
  185. [193]Bowling D 2016 FLUXNET2015 US-Cop Corral Pocket FLUXNET; University of Utah 10.18140/flx/1440100 · DOI
  186. [194]Chen J Chu H 2016 FLUXNET2015 US-CRT Curtice Walter-Berger cropland FLUXNET; University of Toledo/Michigan State University 10.18140/flx/1440117 · DOI
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  194. [202]Drake B Hinkle R 2016 FLUXNET2015 US-KS2 Kennedy Space Center (scrub oak) FLUXNET; Smithsonian Environmental Research Center; University of Central Florida 10.18140/flx/1440075 · DOI
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  196. [204]Desai A 2016 FLUXNET2015 US-Los Lost Creek FLUXNET; University of Wisconsin 10.18140/flx/1440076 · DOI
  197. [205]Meyers T 2016 FLUXNET2015 US-LWW Little Washita Watershed FLUXNET; NOAA/ARL 10.18140/flx/1440077 · DOI
  198. [206]Law B 2016 FLUXNET2015 US-Me1 Metolius - Eyerly burn FLUXNET; Oregon State University 10.18140/flx/1440078 · DOI
  199. [207]Law B 2016 FLUXNET2015 US-Me2 Metolius mature ponderosa pine FLUXNET; Oregon State University 10.18140/flx/1440079 · DOI
  200. [208]Law B 2016 FLUXNET2015 US-Me3 Metolius-second young aged pine FLUXNET; Oregon State University 10.18140/flx/1440080 · DOI

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Authors
Pastorello, G., Trotta, C., Canfora, E., Chu, H., Christianson, D., Cheah, Y.-W., Poindexter, C., Chen, J., Elbashandy, A., Humphrey, M., Isaac, P., Polidori, D., Reichstein, M., Ribeca, A., van Ingen, C., Vuichard, N., Zhang, L., Amiro, B., Ammann, C., Arain, M. A., Ardö, J., Arkebauer, T., Arndt, S. K., Arriga, N., Aubinet, M., Aurela, M., Baldocchi, D., Barr, A., Beamesderfer, E., Marchesini, L. B., Bergeron, O., Beringer, J., Bernhofer, C., Berveiller, D., Billesbach, D., Black, T. A., Blanken, P. D., Bohrer, G., Boike, J., Bolstad, P. V., Bonal, D., Bonnefond, J.-M., Bowling, D. R., Bracho, R., Brodeur, J., Brümmer, C., Buchmann, N., Burban, B., Burns, S. P., Buysse, P., Cale, P., Cavagna, M., Cellier, P., Chen, S., Chini, I., Christensen, T. R., Cleverly, J., Collalti, A., Consalvo, C., Cook, B. D., Cook, D., Coursolle, C., Cremonese, E., Curtis, P. S., D’Andrea, E., da Rocha, H., Dai, X., Davis, K. J., Cinti, B. D., Grandcourt, A. D., Ligne, A. D., De Oliveira, R. C., Delpierre, N., Desai, A. R., Di Bella, C. M., Tommasi, P. D., Dolman, H., Domingo, F., Dong, G., Dore, S., Duce, P., Dufrêne, E., Dunn, A., Dušek, J., Eamus, D., Eichelmann, U., ElKhidir, H. A. M., Eugster, W., Ewenz, C. M., Ewers, B., Famulari, D., Fares, S., Feigenwinter, I., Feitz, A., Fensholt, R., Filippa, G., Fischer, M., Frank, J., Galvagno, M., Gharun, M., Gianelle, D., Gielen, B., Gioli, B., Gitelson, A., Goded, I., Goeckede, M., Goldstein, A. H., Gough, C. M., Goulden, M. L., Graf, A., Griebel, A., Gruening, C., Grünwald, T., Hammerle, A., Han, S., Han, X., Hansen, B. U., Hanson, C., Hatakka, J., He, Y., Hehn, M., Heinesch, B., Hinko-Najera, N., Hörtnagl, L., Hutley, L., Ibrom, A., Ikawa, H., Jackowicz-Korczynski, M., Janouš, D., Jans, W., Jassal, R., Jiang, S., Kato, T., Khomik, M., Klatt, J., Knohl, A., Knox, S., Kobayashi, H., Koerber, G., Kolle, O., Kosugi, Y., Kotani, A., Kowalski, A., Kruijt, B., Kurbatova, J., Kutsch, W. L., Kwon, H., Launiainen, S., Laurila, T., Law, B., Leuning, R., Li, Y., Liddell, M., Limousin, J.-M., Lion, M., Liska, A. J., Lohila, A., López-Ballesteros, A., López-Blanco, E., Loubet, B., Loustau, D., Lucas-Moffat, A., Lüers, J., Ma, S., Macfarlane, C., Magliulo, V., Maier, R., Mammarella, I., Manca, G., Marcolla, B., Margolis, H. A., Marras, S., Massman, W., Mastepanov, M., Matamala, R., Matthes, J. H., Mazzenga, F., McCaughey, H., McHugh, I., McMillan, A. M. S., Merbold, L., Meyer, W., Meyers, T., Miller, S. D., Minerbi, S., Moderow, U., Monson, R. K., Montagnani, L., Moore, C. E., Moors, E., Moreaux, V., Moureaux, C., Munger, J. W., Nakai, T., Neirynck, J., Nesic, Z., Nicolini, G., Noormets, A., Northwood, M., Nosetto, M., Nouvellon, Y., Novick, K., Oechel, W., Olesen, J. E., Ourcival, J.-M., Papuga, S. A., Parmentier, F.-J., Paul-Limoges, E., Pavelka, M., Peichl, M., Pendall, E., Phillips, R. P., Pilegaard, K., Pirk, N., Posse, G., Powell, T., Prasse, H., Prober, S. M., Rambal, S., Rannik, Ü., Raz-Yaseef, N., Rebmann, C., Reed, D., Dios, V. R. D., Restrepo-Coupe, N., Reverter, B. R., Roland, M., Sabbatini, S., Sachs, T., Saleska, S. R., Sánchez-Cañete, E. P., Sanchez-Mejia, Z. M., Schmid, H. P., Schmidt, M., Schneider, K., Schrader, F., Schroder, I., Scott, R. L., Sedlák, P., Serrano-Ortíz, P., Shao, C., Shi, P., Shironya, I., Siebicke, L., Šigut, L., Silberstein, R., Sirca, C., Spano, D., Steinbrecher, R., Stevens, R. M., Sturtevant, C., Suyker, A., Tagesson, T., Takanashi, S., Tang, Y., Tapper, N., Thom, J., Tomassucci, M., Tuovinen, J.-P., Urbanski, S., Valentini, R., van der Molen, M., van Gorsel, E., van Huissteden, K., Varlagin, A., Verfaillie, J., Vesala, T., Vincke, C., Vitale, D., Vygodskaya, N., Walker, J. P., Walter-Shea, E., Wang, H., Weber, R., Westermann, S., Wille, C., Wofsy, S., Wohlfahrt, G., Wolf, S., Woodgate, W., Li, Y., Zampedri, R., Zhang, J., Zhou, G., Zona, D., Agarwal, D., Biraud, S., Torn, M., & Papale, D.
Affiliations
  • Università degli Studi della Tuscia (IT)
  • Lawrence Berkeley National Laboratory (US)
  • California State University, Sacramento (US)
  • Michigan State University (US)
  • University of Virginia (US)
  • Terrestrial Ecosystem Research Network (AU)
  • Max Planck Institute for Biogeochemistry (DE)
  • Centre National de la Recherche Scientifique (FR)
  • Chinese Academy of Sciences (CN)
  • University of Manitoba (CA)
  • Agroscope (CH)
  • McMaster University (CA)
  • Lund University (SE)
  • University of Nebraska–Lincoln (US)
  • The University of Melbourne (AU)
  • University of Antwerp (BE)
  • University of Liège (BE)
  • Finnish Meteorological Institute (FI)
  • University of California, Berkeley (US)
  • Environment and Climate Change Canada (CA)
  • Fondazione Edmund Mach (IT)
  • Ministère de l’Environnement, de la Lutte contre les changements climatiques, de la Faune et des Parcs (CA)
  • The University of Western Australia (AU)
  • Technische Universität Dresden (DE)
  • University of British Columbia (CA)
  • University of Colorado Boulder (US)
  • The Ohio State University (US)
  • Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung (DE)
  • University of Minnesota (US)
  • AgroParisTech (FR)
  • Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR)
  • University of Utah (US)
  • University of Florida (US)
  • Johann Heinrich von Thünen-Institut (DE)
  • ETH Zurich (CH)
  • NSF National Center for Atmospheric Research (US)
  • Aarhus University (DK)
  • University of Technology Sydney (AU)
  • Goddard Space Flight Center (US)
  • Argonne National Laboratory (US)
  • Canadian Forest Service (CA)
  • National Research Council (IT)
  • Pennsylvania State University (US)
  • University of Wisconsin–Madison (US)
  • Consejo Superior de Investigaciones Científicas (ES)
  • Shanxi University (CN)
  • Worcester State University (US)
  • Czech Academy of Sciences, Global Change Research Institute (CZ)
  • Agricultural Research Corporation (SD)
  • University of Wyoming (US)
  • Consiglio per la ricerca in agricoltura e l’analisi dell’economia agraria (IT)
  • Geoscience Australia (AU)
  • University of Copenhagen (DK)
  • Rocky Mountain Research Station (US)
  • European Commission (BE)
  • Virginia Commonwealth University (US)
  • University of California, Irvine (US)
  • Forschungszentrum Jülich (DE)
  • Universität Innsbruck (AT)
  • Henan University (CN)
  • Oregon State University (US)
  • Charles Darwin University (AU)
  • Technical University of Denmark (DK)
  • National Agriculture and Food Research Organization (JP)
  • Wageningen University & Research (NL)
  • Northeast Normal University (CN)
  • Hokkaido University (JP)
  • University of Waterloo (CA)
  • Karlsruhe Institute of Technology (DE)
  • University of Göttingen (DE)
  • Japan Agency for Marine-Earth Science and Technology (JP)
  • The University of Adelaide (AU)
  • Kyoto University (JP)
  • Nagoya University (JP)
  • Universidad de Granada (ES)
  • Russian Academy of Sciences (RU)
  • Integrated Carbon Observation System (FI)
  • Natural Resources Institute Finland (FI)
  • James Cook University (AU)
  • Forest Research Institute Malaysia (MY)
  • Deutscher Wetterdienst (DE)
  • University of Bayreuth (DE)
  • CSIRO Land and Water (AU)
  • University of Helsinki (FI)
  • Université Laval (CA)
  • University of Sassari (IT)
  • Wellesley College (US)
  • Queen's University (CA)
  • International Livestock Research Institute (KE)
  • National Oceanic and Atmospheric Administration (US)
  • State University of New York (US)
  • Provincia autonoma di Bolzano - Alto Adige (IT)
  • University of Arizona (US)
  • Free University of Bozen-Bolzano (IT)
  • University of Illinois Urbana-Champaign (US)
  • IHE Delft Institute for Water Education (NL)
  • Harvard University (US)
  • University of Alaska Fairbanks (US)
  • Research Institute for Nature and Forest (BE)
  • Consejo Nacional de Investigaciones Científicas y Técnicas (AR)
  • Centre de Coopération Internationale en Recherche Agronomique pour le Développement (FR)
  • Indiana University Bloomington (US)
  • University of Exeter (GB)
  • Wayne State University (US)
  • University of Oslo (NO)
  • Swedish University of Agricultural Sciences (SE)
  • Western Sydney University (AU)
  • Commonwealth Scientific and Industrial Research Organisation (AU)
  • National Agricultural Technology Institute (AR)
  • Universidade Federal da Paraíba (BR)
  • GFZ Helmholtz Centre for Geosciences (DE)
  • Sonora Institute of Technology (MX)
  • University of Cologne (DE)
  • Agricultural Research Service (US)
  • Czech Academy of Sciences (CZ)
  • Institute of Agricultural Resources and Regional Planning (CN)
  • Edith Cowan University (AU)
  • South Australian Water Corporation (AU)
  • National Ecological Observatory Network (US)
  • Forestry and Forest Products Research Institute (JP)
  • Peking University (CN)
  • Monash University (AU)
  • US Forest Service (US)
  • UCLouvain (BE)
  • The University of Queensland (AU)
  • Nanjing University of Information Science and Technology (CN)
  • San Diego State University (US)
ORCID
Venue
Scientific Data
Publisher
Springer Science and Business Media LLC
Published
2020-07-09
Volume
7
Issue
1
Pages
225-225
ISSN
2052-4463 (ISSN-L)
DOI
10.1038/s41597-020-0534-3
PMC
PMC7347557
OpenAlex
W3040739689
Cited by
1,728
References
0
Citations by year
2026: 193 · 2025: 357 · 2024: 304 · 2023: 295 · 2022: 309 · 2021: 243 · 2020: 27
Type
data paper
Language
en
Update notices
correction (2021-02-25)
Open access
Licence
Locations
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  • PubMed Central (publishedVersion, cc-by)
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  • White Rose Research Online (University of Leeds, The University of Sheffield, University of York) (acceptedVersion)
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  • UA Campus Repository (The University of Arizona) (acceptedVersion, cc-by)
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  • Lincoln (University of Nebraska) (submittedVersion, cc-by)
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  • NOAA Institutional Repository (submittedVersion, cc-by)
  • CINECA IRIS Institutional Research Information System (Fondazione Edmund Mach) (submittedVersion, cc-by)
  • OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion, cc-by)
  • MPG.PuRe (Max Planck Society) (submittedVersion, cc-by)
  • Repository for Publications and Research Data (ETH Zurich) (submittedVersion, cc-by)
  • Human Biology (submittedVersion)
  • Australasian Journal of Paramedicine (submittedVersion, cc-by)
  • HAL (submittedVersion)
  • Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B)) (submittedVersion, other-oa)
  • Institutional Repository of the University of Granada (University of Granada) (submittedVersion, cc-by)
  • LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (submittedVersion, cc-by)
  • Helmholtz-Zentrum für Polar-und Meeresforschung (Alfred-Wegener-Institut) (submittedVersion, cc-by)
  • eScholarship (California Digital Library) (submittedVersion)
  • Publication Database GFZ (GFZ German Research Centre for Geosciences) (submittedVersion, cc-by)
  • Institute of Botany, CAS Institutional Repository (submittedVersion)
  • IRIS Research product catalog (Sapienza University of Rome) (submittedVersion, cc-by)
  • CNR ExploRA (submittedVersion)
  • Jukuri (Natural Resources Institute Finland (Luke)) (submittedVersion)
  • Minerva Access (University of Melbourne) (submittedVersion, cc-by)
  • LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (submittedVersion, cc-by-nc-sa)
  • Lund University Publications (Lund University) (submittedVersion, cc-by)
  • UTS ePRESS (University of Technology Sydney) (submittedVersion, cc-by)
  • ORBi (University of Liège) (submittedVersion, cc-by)
  • GoeScholar The Publication Server of the Georg-August-Universität Göttingen (Georg-August-Universität Göttingen) (submittedVersion, cc-by)
  • Joint Research Centre (European Commission) (submittedVersion, cc-by)
  • UWA Profiles and Research Repository (UWA) (submittedVersion, cc-by)
  • Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU) (submittedVersion, cc-by)
  • Repositori ObertUDL (University of Lleida) (submittedVersion, cc-by)
  • Open Research (University of Surrey) (submittedVersion, cc-by)
  • LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (submittedVersion, cc-by-nc-nd)
  • NORA - Norwegian Open Research Archives (submittedVersion, cc-by)
  • OpenAgrar (submittedVersion, cc-by)
  • Data Archiving and Networked Services (DANS) (submittedVersion, cc-by)
  • ETH Zürich Research Collection (cc-by)
  • Zurich Open Repository and Archive (University of Zurich)
Funders
  • U.S. Department of Energy
  • European Commission
  • Office of Science
  • Horizon 2020 Framework Programme
  • Natural Environment Research Council (NE/P003028/1, NE/P002552/1)
Topics
  • Physical Sciences › Environmental Science › Global and Planetary Change › Plant Water Relations and Carbon Dynamics
  • Physical Sciences › Earth and Planetary Sciences › Geology › Environmental Monitoring and Data Management
  • Physical Sciences › Environmental Science › Global and Planetary Change › Atmospheric and Environmental Gas Dynamics
Keywords
FLUXNET2015, eddy covariance, biosphere-atmosphere exchange, ecosystem respiration, net ecosystem exchange, data quality control, gap filling, uncertainty estimation

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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