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.