Using vegetation and chlorophyll indices to model above ground biomass over time in an urban arboretum in subtropical Queensland.

As urban forests grow, they can provide a range of ecosystem services, including by sequestering carbon in the form of above ground biomass (AGB). Data from satellites is starting to be used to estimate ecological functions of urban forests including AGB. In this study, we compare individually and in combination five vegetation index and three chlorophyll specific indices based on Sentinel-2 satellite images in spring (September to November) of a newly planted multi-species arboretum over eight years in subtropical Queensland, Australia. There was variation in the eight indices within the arboretum, but some clear patterns among indices over time reflecting the growth of the forest. Using a published simple regression model of AGB as a function of Leaf Area Index (LAI), we found Modified Soil Adjusted Vegetation Index (MSAVI) and Modified Chlorophyll Absorption Ratio Index (MCARI) best predicted AGB (r-square=0.52 and r-square=0.84, respectively), and in combination gave the best estimate (r-square=0.85). The performance of these chlorophyll-specific indices (MSAVI and MCARI) reinforces their benefits over traditional vegetation indices in characterizing vegetation patterns and could complement field-based sampling when modelling carbon sequestration potentials including in mixed species urban forests.