FLUXCOM-X monthly diurnal cycle of gross primary productivity on global 0.25 degree grid for 2005

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 monthly diurnal cycle of gross primary productivity on global 0.25 degree grid for 2005, Miscellaneous, https://hdl.handle.net/11676/BLSGplMlFA_SSYqgqH23oO2v

X-BASE GPP（总初级生产力）基于FLUXCOM-X框架，该框架通过在原位涡度相关数据上训练机器学习模型，并利用这些模型生成全球性的产品。X-BASE实验作为FLUXCOM-X框架的基本配置，旨在作为基准，其中包含核心气象数据、植物功能型分类以及基于MODIS的植被指数和地表温度作为预测因子。实验中采用了XGBoost作为机器学习算法。涡度协方差数据估计的总初级生产力基于夜间分割方法。Gans, F., Duveiller, G., Hamdi, Z., Jung, M., Kraft, B., Nelson, J., Walther, S., Weber, U., Zhang, W. (2023). FLUXCOM-X在全球0.25度网格上对2005年的总初级生产力的月日循环，杂项，https://hdl.handle.net/11676/BLSGplMlFA_SSYqgqH23oO2v