Monitoring of carbon-water fluxes at Eurasian meteorological stations using random forest and remote sensing

M Xie; X Ma; Y Wang; C Li; H Shi; X Yuan; O Hellwich; C Chen; W Zhang; C Zhang; Q Ling; R Gao; Y Zhang; FU Ochege; A Frankl; P De Maeyer; N Buchmann; I Feigenwinter; JE Olesen; R Juszczak; A Jacotot; A Korrensalo; A Pitacco; A Varlagin; A Shekhar; A Lohila; A Carrara; A Brut; B Kruijt; B Loubet; B Heinesch; B Chojnicki; C Helfter; C Vincke; C Shao; C Bernhofer; C Brümmer; C Wille; ES Tuittila; E Nemitz; F Meggio; G Dong; G Lanigan; Georg Niedrist; G Wohlfahrt; G Zhou; I Goded; T Gruenwald; J Olejnik; J Jansen; J Neirynck; JP Tuovinen; J Zhang; K Klumpp; K Pilegaard; L Šigut; L Klemedtsson; L Tezza; L Hörtnagl; M Urbaniak; M Roland; M Schmidt; MA Sutton; M Hehn; M Saunders; M Mauder; M Aurela; M Korkiakoski; M Du; N Vendrame; N Kowalska; PG Leahy; P Alekseychik; P Shi; P Weslien; S Chen; S Fares; T Friborg; T Tallec; T Kato; T Sachs; T Maximov; UM di Cella; U Moderow; Y Li; Y He; Y Kosugi; G Luo

doi:10.1038/s41597-023-02473-9

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Monitoring of carbon-water fluxes at Eurasian meteorological stations using random forest and remote sensing

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Monitoring of carbon-water fluxes at Eurasian meteorological stations using random forest and remote sensing

M Xie, X Ma, Y Wang, C Li, H Shi, X Yuan, O Hellwich, C Chen, W Zhang, C Zhang, …

Scientific Data, Vol.10

2023

DOI: https://doi.org/10.1038/s41597-023-02473-9

Handle:

https://hdl.handle.net/10863/36544

Abstract

Carbon fluxes

longterm monitoring

Simulating the carbon-water fluxes at more widely distributed meteorological stations based on the sparsely and unevenly distributed eddy covariance flux stations is needed to accurately understand the carbon-water cycle of terrestrial ecosystems. We established a new framework consisting of machine learning, determination coefficient (R2), Euclidean distance, and remote sensing (RS), to simulate the daily net ecosystem carbon dioxide exchange (NEE) and water flux (WF) of the Eurasian meteorological stations using a random forest model or/and RS. The daily NEE and WF datasets with RS-based information (NEE-RS and WF-RS) for 3774 and 4427 meteorological stations during 2002–2020 were produced, respectively. And the daily NEE and WF datasets without RS-based information (NEE-WRS and WF-WRS) for 4667 and 6763 meteorological stations during 1983–2018 were generated, respectively. For each meteorological station, the carbon-water fluxes meet accuracy requirements and have quasi-observational properties. These four carbon-water flux datasets have great potential to improve the assessments of the ecosystem carbon-water dynamics.

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Title: Monitoring of carbon-water fluxes at Eurasian meteorological stations using random forest and remote sensing
Creators: M Xie - Ghent University
X Ma - Xinjiang Institute of Ecology and Geography
Y Wang - Xinjiang Institute of Ecology and Geography
C Li - Nanjing University of Information Science and Technology
H Shi - Hohai University
X Yuan - Xinjiang Institute of Ecology and Geography
O Hellwich - Technische Universität Berlin
C Chen - Xinjiang Institute of Ecology and Geography
W Zhang - Ghent University
C Zhang - Xinjiang Institute of Ecology and Geography
Q Ling - Xinjiang Institute of Ecology and Geography
R Gao - Xinjiang Institute of Ecology and Geography
Y Zhang - Ghent University
FU Ochege - Xinjiang Institute of Ecology and Geography
A Frankl - Ghent University
P De Maeyer - Ghent University
N Buchmann - ETH Zurich
I Feigenwinter - ETH Zurich
JE Olesen - Aarhus University
R Juszczak - University of Life Sciences in Poznań
A Jacotot - Soil Agro and Hydrosystems Spatialization
A Korrensalo - Natural Resources Institute Finland
A Pitacco - University of Padua
A Varlagin - Severtsov Institute of Ecology and Evolution
A Shekhar - ETH Zurich
A Lohila - University of Helsinki
A Carrara - Fundación General
A Brut - Université de Toulouse
B Kruijt - Wageningen University & Research
B Loubet - ParisTech
B Heinesch - Gembloux Agro-Bio Tech
B Chojnicki - University of Life Sciences in Poznań
C Helfter - UK Centre for Ecology & Hydrology
C Vincke - UCLouvain
C Shao - Institute of Agricultural Resources and Regional Planning
C Bernhofer - TU Dresden
C Brümmer - Johann Heinrich von Thünen-Institut
C Wille - Helmholtz Centre Potsdam - GFZ German Research Centre for Geosciences
ES Tuittila - University of Eastern Finland
E Nemitz - UK Centre for Ecology & Hydrology
F Meggio - University of Padua
G Dong - Shanxi University
G Lanigan - Teagasc - The Irish Agriculture and Food Development Authority
Georg Niedrist - Eurac Research
G Wohlfahrt - Universität Innsbruck
G Zhou - Nanjing University of Information Science and Technology
I Goded - Joint Research Centre
T Gruenwald
J Olejnik - University of Life Sciences in Poznań
J Jansen - Uppsala University
J Neirynck - Research Institute for Nature and Forest
JP Tuovinen - Finnish Meteorological Institute
J Zhang - Qufu Normal University
K Klumpp - VetAgro Sup
K Pilegaard - Technical University of Denmark
L Šigut - Czech Academy of Sciences, Global Change Research Institute
L Klemedtsson - University of Gothenburg
L Tezza - University of Padua
L Hörtnagl - ETH Zurich
M Urbaniak - University of Life Sciences in Poznań
M Roland - University of Antwerp
M Schmidt - Forschungszentrum Jülich
MA Sutton - UK Centre for Ecology & Hydrology
M Hehn - TU Dresden
M Saunders - Trinity College Dublin
M Mauder - TU Dresden
M Aurela - Finnish Meteorological Institute
M Korkiakoski - Finnish Meteorological Institute
M Du - National Agriculture and Food Research Organization
N Vendrame - University of Trento
N Kowalska - Czech Academy of Sciences, Global Change Research Institute
PG Leahy - University College Cork
P Alekseychik - Natural Resources Institute Finland
P Shi - Institute of Geographic Sciences and Natural Resources Research
P Weslien - University of Gothenburg
S Chen - Institute of Botany
S Fares - Istituto per il Sistema Produzione Animale in Ambiente Mediterraneo
T Friborg - University of Copenhagen
T Tallec - Université de Toulouse
T Kato - Hokkaido University
T Sachs - Helmholtz Centre Potsdam - GFZ German Research Centre for Geosciences
T Maximov - Institute of Oil and Gas Problems of the Siberian Branch of the RAS
UM di Cella - Agenzia Regionale per la Protezione Ambientale
U Moderow - TU Dresden
Y Li - Chinese Academy of Sciences
Y He - Institute of Geographic Sciences and Natural Resources Research
Y Kosugi - Kyoto University
G Luo - Xinjiang Institute of Ecology and Geography
Publication Details: Scientific Data, Vol.10
EISSN: 2052-4463
Series / Volume: 10
Publisher: Nature Research
Number of pages: 18
Identifiers: (EURAC)27708271
991006609495201241
Web of Science ID: WOS:001065045600002
Copyright: Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Academic Unit: Institute for Alpine Environment
Language: English
Resource Type: Journal article
Description coverage: international
Description audience: Scientific
Local Fields: Scientific
Author Names String: Xie M, Ma X, Wang Y, Li C, Shi H, Yuan X, Hellwich O, Chen C, Zhang W, Zhang C, Ling Q, Gao R, Zhang Y, Ochege FU, Frankl A, De Maeyer P, Buchmann N, Feigenwinter I, Olesen JE, Juszczak R, Jacotot A, Korrensalo A, Pitacco A, Varlagin A, Shekhar A, Lohila A, Carrara A, Brut A, Kruijt B, Loubet B, Heinesch B, Chojnicki B, Helfter C, Vincke C, Shao C, Bernhofer C, Brümmer C, Wille C, Tuittila ES, Nemitz E, Meggio F, Dong G, Lanigan G, Niedrist G, Wohlfahrt G, Zhou G, Goded I, Gruenwald T, Olejnik J, Jansen J, Neirynck J, Tuovinen JP, Zhang J, Klumpp K, Pilegaard K, Šigut L, Klemedtsson L, Tezza L, Hörtnagl L, Urbaniak M, Roland M, Schmidt M, Sutton MA, Hehn M, Saunders M, Mauder M, Aurela M, Korkiakoski M, Du M, Vendrame N, Kowalska N, Leahy PG, Alekseychik P, Shi P, Weslien P, Chen S, Fares S, Friborg T, Tallec T, Kato T, Sachs T, Maximov T, di Cella UM, Moderow U, Li Y, He Y, Kosugi Y, Luo G

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