Data from: Estimation of woody and herbaceous leaf area index in Sub-Saharan Africa using MODIS data

Savannas are widespread global biomes covering ~20% of terrestrial ecosystems on all continents except Antarctica. These ecosystems play a critical role in regulating terrestrial carbon cycle, ecosystem productivity, and the hydrological cycle and contribute to human livelihoods and biodiversity conservation. Despite the importance of savannas in ecosystem processes and human well-being, the presence of mixed woody and herbaceous components at scales much fin-er than most medium and coarse resolution satellite imagery poses significant challenges to their effective representation in remote sensing and modeling of vegetation dynamics. Although pre-vious studies have attempted to separate woody and herbaceous components, the focus on greenness indices and fractional cover provides little insight into spatio-temporal variability in woody and herbaceous vegetation structure, in particular, leaf area index (LAI). This paper pre-sents a method to partition 1km spatial resolution Moderate Resolution Imaging Spectroradiome-ter (MODIS) aggregate green leaf area index (LAIA) from 2003-2015, into separate woody (LAIW) and herbaceous (LAIH) constituents in both drought seasonal savannas and moist tropical forests of Sub-Saharan Africa (SSA). In our analysis, we use an allometric relationship describing the variation in peak within-canopy woody LAI of dominant tree species (LAIWpinc) across gradi-ents in mean annual precipitation (MAP), coupled with independent estimates of woody canopy cover (τw), to constrain seasonally changing LAIW. We present the LAI partitioning approach and highlight the broad spatial and temporal patterns of woody and herbaceous LAI across SSA. The long-term average 8-day phenologies of woody and herbaceous LAI (averaged across 2003-2015) are available for evaluation, research and application purposes.

热带稀树草原（Savannas）是分布广泛的全球生物群系，覆盖了除南极洲以外所有大陆约20%的陆地生态系统。该类生态系统在调控陆地碳循环、生态系统生产力与水文循环中发挥关键作用，同时对人类生计保障与生物多样性保护具有重要意义。尽管热带稀树草原在生态系统过程与人类福祉中至关重要，但其木本与草本混合组分的空间尺度远小于多数中、粗分辨率卫星影像的像元分辨率，这给遥感表征与植被动态建模中的有效呈现带来了极大挑战。尽管此前已有研究尝试分离木本与草本组分，但现有研究多聚焦于绿度指数与覆盖占比，难以揭示木本与草本植被结构的时空变异规律，尤其是叶面积指数（LAI）。本文提出一种拆分方法，可将2003-2015年空间分辨率为1km的中分辨率成像光谱仪（Moderate Resolution Imaging Spectroradiometer，简称MODIS）总绿叶面积指数（LAIA），拆分为撒哈拉以南非洲（Sub-Saharan Africa，简称SSA）季节性干旱热带稀树草原与湿润热带森林的木本绿叶面积指数（LAIW）与草本绿叶面积指数（LAIH）两个独立组分。本研究利用异速生长关系描述优势树种冠层内木本叶面积指数峰值（LAIWpinc）随年平均降水量（MAP）梯度的变化，并结合木本冠层覆盖度（τw）的独立估算值，约束随季节动态变化的木本叶面积指数（LAIW）。本文详细阐述了该叶面积指数拆分方法，并揭示了撒哈拉以南非洲区域木本与草本叶面积指数的整体时空分布格局。本数据集提供2003-2015年木本与草本叶面积指数的长期平均8天物候数据，可用于评估、研究与实际应用。