FLUXCOM-X monthly net ecosystem exchange on global 0.5 degree grid for 2008

X-BASE NEE 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-JMJEX-BASE NEE 基于FLUXCOM-X框架，该框架通过对原位涡度协方差数据进行机器学习模型训练，并利用这些模型生成全球产品。X-BASE实验作为FLUXCOM-X框架的基础配置，旨在为其提供基准，并包括核心气象数据、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。涡度协方差数据中的GPP估算基于夜间分合法。

搜集汇总

背景与挑战

背景概述

该数据集是FLUXCOM-X框架下生成的全球月度净生态系统交换（NEE）产品，空间分辨率为0.5度，覆盖2008年。它基于机器学习模型（XGBoost）训练原位涡度协方差数据，并整合气象、植被和遥感等多源预测因子，作为FLUXCOM-X-BASE实验的基线配置，用于评估陆地碳和水平衡。