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FLUXCOM-X monthly transpiration on global 0.05 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 0.05 degree grid for 2019, Miscellaneous, https://hdl.handle.net/11676/x2ocfK9gG4oPJ7HCX-in1I4C
BibTex
@misc{https://hdl.handle.net/11676/x2ocfK9gG4oPJ7HCX-in1I4C,
  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 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/x2ocfK9gG4oPJ7HCX-in1I4C},
  publisher={Carbon Portal},
  copyright={http://meta.icos-cp.eu/ontologies/cpmeta/icosLicence},
  pid={11676/x2ocfK9gG4oPJ7HCX-in1I4C}
}
RIS
TY - DATA
T1 - FLUXCOM-X monthly transpiration on global 0.05 degree grid for 2019
ID - 11676/x2ocfK9gG4oPJ7HCX-in1I4C
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/x2ocfK9gG4oPJ7HCX-in1I4C
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_005_monthly.nc
416 MB (435890086 bytes)
3

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

Statistics

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Submission

2023-07-25 10:30:00
2023-07-25 10:06:26

Technical information

c76a1c7caf601b8a0f27b1c25fe8a7d48e02284ffeb9ede2c7250e1f5520887b
x2ocfK9gG4oPJ7HCX+in1I4CKE/+ue3ixyUOH1UgiHs
S: -90, W: -180, N: 90, E: 180
BIOGEOCHEMICAL CYCLES CARBON ECOSYSTEM FUNCTIONS FLUXCOM LAND SURFACE TERRESTRIAL ECOSYSTEMS VEGETATION biosphere modeling carbon flux