FLUXCOM-X monthly gross primary productivity on global 0.05 degree grid for 2017
11676/E51dDGAO7C6jneZAm3zaVzpc (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.
2017-01-01 12:00:00
2017-12-01 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 gross primary productivity on global 0.05 degree grid for 2017, Miscellaneous, https://hdl.handle.net/11676/E51dDGAO7C6jneZAm3zaVzpc
BibTex
@misc{https://hdl.handle.net/11676/E51dDGAO7C6jneZAm3zaVzpc, 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 gross primary productivity on global 0.05 degree grid for 2017}, 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/E51dDGAO7C6jneZAm3zaVzpc}, publisher={Carbon Portal}, copyright={http://meta.icos-cp.eu/ontologies/cpmeta/icosLicence}, pid={11676/E51dDGAO7C6jneZAm3zaVzpc} }
RIS
TY - DATA T1 - FLUXCOM-X monthly gross primary productivity on global 0.05 degree grid for 2017 ID - 11676/E51dDGAO7C6jneZAm3zaVzpc 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/E51dDGAO7C6jneZAm3zaVzpc 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_2017_005_monthly.nc
421 MB (441381666 bytes)
3
Production
2023-06-21 00:00:00
Basil Kraft,
Gregory Duveiller,
Jacob A. Nelson,
Martin Jung,
Sophia Walther,
Ulrich Weber,
Weijie Zhang,
Zayd Hamdi
Previewable variables
Name | Value type | Unit | Quantity kind | Preview |
---|---|---|---|---|
GPP | gross primary productivity of carbon | gC m-2 d-1 | particle flux | Preview |
Statistics
0
0
Technical information
139d5d0c600eec2ea39de6409b7cda573a5cf4e4a10382fb4b9ca253cbfb6219
E51dDGAO7C6jneZAm3zaVzpc9OShA4L7S5yiU8v7Yhk
S: -90, W: -180, N: 90, E: 180
BIOGEOCHEMICAL CYCLES
CARBON
ECOSYSTEM FUNCTIONS
FLUXCOM
LAND SURFACE
TERRESTRIAL ECOSYSTEMS
VEGETATION
biosphere modeling
carbon flux