FLUXCOM-X daily gross primary productivity on global 0.25 degree grid for 2017

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.
Gans, F., Duveiller, G., Hamdi, Z., Jung, M., Kraft, B., Nelson, J., Walther, S., Weber, U., Zhang, W. (2023). FLUXCOM-X daily gross primary productivity on global 0.25 degree grid for 2017, Miscellaneous, https://hdl.handle.net/11676/P-AkqoQ_3l2oqVbNPxcGzEzl

X-BASE GPP（总初级生产力）基于FLUXCOM-X框架构建，该框架通过在原位涡度协方差数据上训练机器学习模型，并利用这些模型生成全球生产力数据。X-BASE实验作为FLUXCOM-X框架的基础配置，用以作为基准，其预测因子包括核心气象数据、植被功能型分类以及基于MODIS的植被指数和地表温度。在此次实验中，采用了XGBoost作为机器学习算法。涡度协方差数据生成的GPP估计基于夜间分割方法。
Gans, F., Duveiller, G., Hamdi, Z., Jung, M., Kraft, B., Nelson, J., Walther, S., Weber, U., Zhang, W. (2023). FLUXCOM-X全球0.25度网格日总初级生产力数据集（2017年），杂项，https://hdl.handle.net/11676/P-AkqoQ_3l2oqVbNPxcGzEzl