FLUXCOM-X monthly transpiration on global 0.05 degree grid for 2007
Deprecated data
Latest version(s):
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11676/LHTouOemU9pklZthcvwHXchd (link)
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).
2007-01-01 12:00:00
2007-12-01 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 0.05 degree grid for 2007, Miscellaneous, https://hdl.handle.net/11676/LHTouOemU9pklZthcvwHXchd
BibTex
@misc{https://hdl.handle.net/11676/LHTouOemU9pklZthcvwHXchd, 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 0.05 degree grid for 2007}, 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/LHTouOemU9pklZthcvwHXchd}, publisher={Carbon Portal}, copyright={http://meta.icos-cp.eu/ontologies/cpmeta/icosLicence}, pid={11676/LHTouOemU9pklZthcvwHXchd} }
RIS
TY - DATA T1 - FLUXCOM-X monthly transpiration on global 0.05 degree grid for 2007 ID - 11676/LHTouOemU9pklZthcvwHXchd 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/LHTouOemU9pklZthcvwHXchd 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_2007_005_monthly.nc
414 MB (434440422 bytes)
3
Production
2023-06-21 00:00:00
Gregory Duveiller,
Zayd Hamdi,
Martin Jung,
Basil Kraft,
Jacob A. Nelson,
Sophia Walther,
Ulrich Weber,
Weijie Zhang
Previewable variables
Name | Value type | Unit | Quantity kind | Preview |
---|---|---|---|---|
ET_T | transpiration | mm h-1 | particle flux | Preview |
Statistics
0
0
Technical information
2c74e8b8e7a653da64959b6172fc075dc85d22aae71e788461abcfda5b76ae38
LHTouOemU9pklZthcvwHXchdIqrnHniEYavP2lt2rjg
S: -90, W: -180, N: 90, E: 180
BIOGEOCHEMICAL CYCLES
CARBON
ECOSYSTEM FUNCTIONS
FLUXCOM
LAND SURFACE
TERRESTRIAL ECOSYSTEMS
VEGETATION
biosphere modeling
carbon flux