FLUXCOM-X monthly gross primary productivity on global 0.05 degree grid for 2001
11676/spNOdnEphx4tNvPqe2J7PjXJ (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
2001-12-01 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 2001, Miscellaneous, https://hdl.handle.net/11676/spNOdnEphx4tNvPqe2J7PjXJ
BibTex
@misc{https://hdl.handle.net/11676/spNOdnEphx4tNvPqe2J7PjXJ, 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 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/spNOdnEphx4tNvPqe2J7PjXJ}, publisher={Carbon Portal}, copyright={http://meta.icos-cp.eu/ontologies/cpmeta/icosLicence}, pid={11676/spNOdnEphx4tNvPqe2J7PjXJ} }
RIS
TY - DATA T1 - FLUXCOM-X monthly gross primary productivity on global 0.05 degree grid for 2001 ID - 11676/spNOdnEphx4tNvPqe2J7PjXJ 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/spNOdnEphx4tNvPqe2J7PjXJ 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_005_monthly.nc
421 MB (441815666 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
1
Technical information
b2934e767129871e2d36f3ea7b627b3e35c9792522fca9f54e410432335c23f7
spNOdnEphx4tNvPqe2J7PjXJeSUi/Kn1TkEEMjNcI/c
S: -90, W: -180, N: 90, E: 180
BIOGEOCHEMICAL CYCLES
CARBON
ECOSYSTEM FUNCTIONS
FLUXCOM
LAND SURFACE
TERRESTRIAL ECOSYSTEMS
VEGETATION
biosphere modeling
carbon flux