ICOS

FLUXCOM-X daily gross primary productivity on global 0.25 degree grid for 2001

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11676/DEOUE1UrVP-eEsbjcdKeK9KF (link)
X-BASE GPP (Gross Primary Productivity) is based on the FLUXCOM-X framework which trains machine learning models on in-situ eddy covariance data and uses them to produce this global product. The X-BASE experiment is a basic configuration to serve as a baseline for the FLUXCOM-X framework and includes as predictors the core meteorlogical data, plant functional type classification as well as MODIS based vegitation indicies and land surface temperature. XGBoost was used as the machine learning algorithm. The GPP estimates from the eddy covariance data was based on the Nighttime Partitioning method.
2001-01-01 12:00:00
2001-12-31 12:00:00
daily
Gans, F., Duveiller, G., Hamdi, Z., Jung, M., Kraft, B., Nelson, J., Walther, S., Weber, U., Zhang, W. (2023). FLUXCOM-X daily gross primary productivity on global 0.25 degree grid for 2001, Miscellaneous, https://hdl.handle.net/11676/DEOUE1UrVP-eEsbjcdKeK9KF
BibTex
@misc{https://hdl.handle.net/11676/DEOUE1UrVP-eEsbjcdKeK9KF,
  author={Gans, Fabian and Duveiller, Gregory and Hamdi, Zayd and Jung, Martin and Kraft, Basil and Nelson, Jacob A. and Walther, Sophia and Weber, Ulrich and Zhang, Weijie},
  title={FLUXCOM-X daily gross primary productivity on global 0.25 degree grid for 2001},
  year={2023},
  note={X-BASE GPP (Gross Primary Productivity) is based on the FLUXCOM-X framework which trains machine learning models on in-situ eddy covariance data and uses them to produce this global product. The X-BASE experiment is a basic configuration to serve as a baseline for the FLUXCOM-X framework and includes as predictors the core meteorlogical data, plant functional type classification as well as MODIS based vegitation indicies and land surface temperature. XGBoost was used as the machine learning algorithm. The GPP estimates from the eddy covariance data was based on the Nighttime Partitioning method.},
  keywords={BIOGEOCHEMICAL CYCLES, ECOSYSTEM FUNCTIONS, TERRESTRIAL ECOSYSTEMS, VEGETATION, CARBON, LAND SURFACE, FLUXCOM},
  url={https://hdl.handle.net/11676/DEOUE1UrVP-eEsbjcdKeK9KF},
  publisher={Carbon Portal},
  copyright={http://meta.icos-cp.eu/ontologies/cpmeta/icosLicence},
  pid={11676/DEOUE1UrVP-eEsbjcdKeK9KF}
}
RIS
TY - DATA
T1 - FLUXCOM-X daily gross primary productivity on global 0.25 degree grid for 2001
ID - 11676/DEOUE1UrVP-eEsbjcdKeK9KF
PY - 2023
AB - X-BASE GPP (Gross Primary Productivity) is based on the FLUXCOM-X framework which trains machine learning models on in-situ eddy covariance data and uses them to produce this global product. The X-BASE experiment is a basic configuration to serve as a baseline for the FLUXCOM-X framework and includes as predictors the core meteorlogical data, plant functional type classification as well as MODIS based vegitation indicies and land surface temperature. XGBoost was used as the machine learning algorithm. The GPP estimates from the eddy covariance data was based on the Nighttime Partitioning method.
UR - https://hdl.handle.net/11676/DEOUE1UrVP-eEsbjcdKeK9KF
PB - Carbon Portal
AU - Gans, Fabian
AU - Duveiller, Gregory
AU - Hamdi, Zayd
AU - Jung, Martin
AU - Kraft, Basil
AU - Nelson, Jacob A.
AU - Walther, Sophia
AU - Weber, Ulrich
AU - Zhang, Weijie
KW - BIOGEOCHEMICAL CYCLES
KW - ECOSYSTEM FUNCTIONS
KW - TERRESTRIAL ECOSYSTEMS
KW - VEGETATION
KW - CARBON
KW - LAND SURFACE
KW - FLUXCOM
ER - 
GPP_2001_025_daily.nc
353 MB (370268078 bytes)
3

Production

2023-06-21 00:00:00

Previewable variables

Name Value type Unit Quantity kind Preview
GPP gross primary productivity of carbon gC m-2 d-1 particle flux Preview

Statistics

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Submission

2023-07-25 11:19:30
2023-07-25 11:18:53

Technical information

0c439413552b54ff9e12c6e371d29e2bd285ec40bdda35b05920d8d0fedcc47b
DEOUE1UrVP+eEsbjcdKeK9KF7EC92jWwWSDY0P7cxHs
S: -90, W: -180, N: 90, E: 180
BIOGEOCHEMICAL CYCLES CARBON ECOSYSTEM FUNCTIONS FLUXCOM LAND SURFACE TERRESTRIAL ECOSYSTEMS VEGETATION biosphere modeling carbon flux