全球植被叶片光合能力（Vcmax）数据集

最大羧化速率（Vcmax）决定了叶片光合能力，是估算陆地生态系统碳循环的关键参数。本数据集包含了3组不同卫星数据来源生成的全球0.5度分辨率生长季平均Vcmax空间分布数据：一是根据植被氮在光捕获和羧化途径之间的优化分布原理，从MERIS传感器获取的叶绿素含量 (LCC) 转换生成 Vcmax数据（LCC-Vcmax）；二是基于GOME-2卫星观测的日光诱导叶绿素荧光 (SIF)数据，通过数据同化技术生成Vcmax数据（SIF-Vcmax）；三是将第一组LCC-Vcmax数据作为限制条件，从TROPOMI SIF数据反演生成Vcmax数据（SIF+LCC-Vcmax）。三组数据均与基于生态最优性原理（EOT）通过气象参量计算的 Vcmax（EOT-Vcmax）有较好的一致性，与3672组地面测量数据相比较也获得了很好的验证。本数据集有效揭示了土地覆被、灌溉、土壤pH值等因素对叶片光合能力的影响，将会更好的支撑全球生态系统研究。

The maximum carboxylation rate (Vcmax), which determines leaf photosynthetic capacity, is a critical parameter for estimating terrestrial ecosystem carbon cycles. This dataset contains three sets of spatially distributed data of growing-season averaged Vcmax at 0.5° global resolution, generated from three different satellite data sources: 1) LCC-Vcmax: Vcmax data converted from leaf chlorophyll content (LCC) retrieved by the MERIS sensor, based on the optimal distribution principle of vegetation nitrogen between light capture and carboxylation pathways; 2) SIF-Vcmax: Vcmax data generated via data assimilation techniques using solar-induced chlorophyll fluorescence (SIF) data observed by the GOME-2 satellite; 3) SIF+LCC-Vcmax: Vcmax data retrieved from TROPOMI SIF data, with the first set of LCC-Vcmax data used as a constraint condition. All three sets of data exhibit good consistency with EOT-Vcmax, i.e., Vcmax calculated from meteorological parameters based on the ecological optimality theory (EOT), and have been well validated against 3672 ground-based measurement datasets. This dataset effectively reveals the impacts of factors such as land cover, irrigation, and soil pH on leaf photosynthetic capacity, and will better support global ecosystem research.

搜集汇总

背景与挑战

背景概述

该数据集提供了全球植被叶片光合能力（Vcmax）的关键参数，包含三组基于不同卫星数据（MERIS叶绿素含量、GOME-2和TROPOMI的日光诱导叶绿素荧光）生成的0.5度分辨率生长季平均空间分布数据，有效支持陆地生态系统碳循环研究。数据经过地面测量验证，揭示了土地覆被、灌溉和土壤pH值等因素对光合能力的影响，适用于生态学、地理学和大气科学领域的全球尺度分析。