FLUXCOM-X monthly gross primary productivity on global 0.05 degree grid for 2020
11676/nL7GbNKuHie8T7hT6T8kXYlB (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.
2020-01-01 12:00:00
2020-12-01 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 2020, Miscellaneous, https://hdl.handle.net/11676/nL7GbNKuHie8T7hT6T8kXYlB
BibTex
@misc{https://hdl.handle.net/11676/nL7GbNKuHie8T7hT6T8kXYlB, 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 2020}, 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/nL7GbNKuHie8T7hT6T8kXYlB}, publisher={Carbon Portal}, copyright={http://meta.icos-cp.eu/ontologies/cpmeta/icosLicence}, pid={11676/nL7GbNKuHie8T7hT6T8kXYlB} }
RIS
TY - DATA T1 - FLUXCOM-X monthly gross primary productivity on global 0.05 degree grid for 2020 ID - 11676/nL7GbNKuHie8T7hT6T8kXYlB 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/nL7GbNKuHie8T7hT6T8kXYlB 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_2020_005_monthly.nc
421 MB (441129525 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
9cbec66cd2ae1e27bc4fb853e93f245d8941140862e1f2900212874ec85ad24b
nL7GbNKuHie8T7hT6T8kXYlBFAhi4fKQAhKHTsha0ks
S: -90, W: -180, N: 90, E: 180
BIOGEOCHEMICAL CYCLES
CARBON
ECOSYSTEM FUNCTIONS
FLUXCOM
LAND SURFACE
TERRESTRIAL ECOSYSTEMS
VEGETATION
biosphere modeling
carbon flux