FLUXCOM-X daily gross primary productivity on global 0.25 degree grid for 2009

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 2009, Miscellaneous, https://hdl.handle.net/11676/abBFUTYtAKh1ZN521xiBJAhN

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。X-BASE实验是一种基本配置，旨在作为FLUXCOM-X框架的基准，其中包含核心气象数据、植被功能型分类以及基于MODIS的植被指数和地表温度作为预测因子。XGBoost被用作机器学习算法。涡度协方差数据的GPP估算基于夜间分割方法。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度网格上的每日总初级生产力，杂项，https://hdl.handle.net/11676/abBFUTYtAKh1ZN521xiBJAhN