FLUXCOM-X monthly transpiration on global 0.05 degree grid for 2010

X-BASE ET_T 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.

Published paper: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-165/
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

X-BASE ET_T 数据集基于 FLUXCOM-X 框架构建，该框架通过现场涡度协方差数据训练机器学习模型，并利用这些模型生成全球产品。X-BASE 实验作为一种基础配置，旨在为 FLUXCOM-X 框架提供一个基准，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。本实验采用了 XGBoost 作为机器学习算法。涡度协方差数据中的 GPP（总初级生产力）估计基于夜间分割法。

已发表论文：https://egusphere.copernicus.org/preprints/2024/egusphere-2024-165/
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