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FLUXCOM-X monthly transpiration on global 0.5 degree grid for 2019

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X-BASE ET_T (Transpiration) 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 transpiration estimates from the eddy covariance data was based on the Transpiration Estimation Algorithm (TEA).
2019-01-01 12:00:00
2019-12-01 12:00:00
monthly
Gans, F., Duveiller, G., Hamdi, Z., Jung, M., Kraft, B., Nelson, J., Walther, S., Weber, U., Zhang, W. (2023). FLUXCOM-X monthly transpiration on global 0.5 degree grid for 2019, Miscellaneous, https://hdl.handle.net/11676/baN7j1meZf_m_oAOLlya5zTS
BibTex
@misc{https://hdl.handle.net/11676/baN7j1meZf_m_oAOLlya5zTS,
  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 monthly transpiration on global 0.5 degree grid for 2019},
  year={2023},
  note={X-BASE ET_T (Transpiration) 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 transpiration estimates from the eddy covariance data was based on the Transpiration Estimation Algorithm (TEA).},
  keywords={BIOGEOCHEMICAL CYCLES, ECOSYSTEM FUNCTIONS, TERRESTRIAL ECOSYSTEMS, VEGETATION, CARBON, LAND SURFACE, FLUXCOM},
  url={https://hdl.handle.net/11676/baN7j1meZf_m_oAOLlya5zTS},
  publisher={Carbon Portal},
  copyright={http://meta.icos-cp.eu/ontologies/cpmeta/icosLicence},
  pid={11676/baN7j1meZf_m_oAOLlya5zTS}
}
RIS
TY - DATA
T1 - FLUXCOM-X monthly transpiration on global 0.5 degree grid for 2019
ID - 11676/baN7j1meZf_m_oAOLlya5zTS
PY - 2023
AB - X-BASE ET_T (Transpiration) 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 transpiration estimates from the eddy covariance data was based on the Transpiration Estimation Algorithm (TEA).
UR - https://hdl.handle.net/11676/baN7j1meZf_m_oAOLlya5zTS
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 - 
ET_T_2019_monthly_halfdeg.nc
5 MB (5016249 bytes)
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Production

2023-06-21 00:00:00

Previewable variables

Name Value type Unit Quantity kind Preview
ET_T transpiration mm h-1 particle flux Preview

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Submission

2023-07-25 10:30:27
2023-07-25 10:06:26

Technical information

6da37b8f599e65ffe6fe800e2e5c9ae734d28a48663a5a35acffe4c5dc1a8764
baN7j1meZf/m/oAOLlya5zTSikhmOlo1rP/kxdwah2Q
S: -90, W: -180, N: 90, E: 180
BIOGEOCHEMICAL CYCLES CARBON ECOSYSTEM FUNCTIONS FLUXCOM LAND SURFACE TERRESTRIAL ECOSYSTEMS VEGETATION biosphere modeling carbon flux