ICOS

FLUXCOM-X-BASE gross primary productivity for 2015

Collection
10.18160/5NZG-JMJE (target, metadata)
The X-BASE products are global fluxes based on the FLUXCOM-X framework which trains machine learning models on in-situ eddy covariance data and uses them to produce these global products. The X-BASE experiment is a basic configuration to serve as a baseline for the FLUXCOM-X framework and includes as predictors the core meteorological data, plant functional type classification as well as MODIS based vegetation indices and land surface temperature. XGBoost was used as the machine learning algorithm. Published paper: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-165/
2023
ICOS ERIC -- Carbon Portal
BIOGEOCHEMICAL CYCLES, CARBON, ECOSYSTEM FUNCTIONS, FLUXCOM, LAND SURFACE, TERRESTRIAL ECOSYSTEMS, VEGETATION, biosphere modeling, carbon flux, FLUXCOM-X
Nelson, J.A., Walther, S., Jung, M., Gans, F., Kraft, B., Weber, U., Hamdi, Z., Duveiller, G., Zhang, W., 2023. FLUXCOM-X-BASE. https://doi.org/10.18160/5NZG-JMJE
BibTex
@misc{https://doi.org/10.18160/5nzg-jmje,
  doi = {10.18160/5NZG-JMJE},
  url = {https://meta.icos-cp.eu/collections/zfwf1Ak2I7OlziGDTX8Xl6_T},
  author = {Nelson, Jacob A. and Walther, Sophia and Jung, Martin and Gans, Fabian and Kraft, Basil and Weber, Ulrich and Hamdi, Zayd and Duveiller, Gregory and Zhang, Weijie},
  keywords = {BIOGEOCHEMICAL CYCLES, CARBON, ECOSYSTEM FUNCTIONS, FLUXCOM, LAND SURFACE, TERRESTRIAL ECOSYSTEMS, VEGETATION, biosphere modeling, carbon flux, FLUXCOM-X},
  title = {FLUXCOM-X-BASE},
  publisher = {ICOS ERIC -- Carbon Portal},
  year = {2023},
  copyright = {ICOS CCBY4 Data Licence}
}
RIS
TY  - DATA
T1  - FLUXCOM-X-BASE
AU  - Nelson, Jacob A.
AU  - Walther, Sophia
AU  - Jung, Martin
AU  - Gans, Fabian
AU  - Kraft, Basil
AU  - Weber, Ulrich
AU  - Hamdi, Zayd
AU  - Duveiller, Gregory
AU  - Zhang, Weijie
DO  - 10.18160/5NZG-JMJE
UR  - https://meta.icos-cp.eu/collections/zfwf1Ak2I7OlziGDTX8Xl6_T
AB  - The X-BASE products are global fluxes based on the FLUXCOM-X framework which trains machine learning models on in-situ eddy covariance data and uses them to produce these global products. The X-BASE experiment is a basic configuration to serve as a baseline for the FLUXCOM-X framework and includes as predictors the core meteorological data, plant functional type classification as well as MODIS based vegetation indices and land surface temperature. XGBoost was used as the machine learning algorithm.

Published paper: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-165/
KW  - BIOGEOCHEMICAL CYCLES
KW  - CARBON
KW  - ECOSYSTEM FUNCTIONS
KW  - FLUXCOM
KW  - LAND SURFACE
KW  - TERRESTRIAL ECOSYSTEMS
KW  - VEGETATION
KW  - biosphere modeling
KW  - carbon flux
KW  - FLUXCOM-X
PY  - 2023
PB  - ICOS ERIC -- Carbon Portal
ER  -

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