The applicability of empirical vegetation indices for determining leaf chlorophyll content over different leaf and canopy structures

Retrieving leaf chlorophyll content at a range of spatio-temporal scales is central to monitoring vegetation productivity, identifying physiological stress and managing biological resources. However, estimating leaf chlorophyll over broad spatial extents using ground-based traditional methods is time and resource heavy. Satellite-derived spectral vegetation indices (VIs) are commonly used to estimate leaf chlorophyll content, however they are often developed and tested on broadleaf species. Relatively little research has assessed VIs for different leaf structures, particularly needle leaves which represent a large component of boreal forest and significant global ecosystems. This study tested the performance of 47 published VIs for estimating foliar chlorophyll content from different leaf and canopy structures (broadleaf and needle). Coniferous and deciduous sites were selected in Ontario, Canada, representing different dominant vegetation species (Picea mariana and Acer saccharum) and a variety of canopy structures. Leaf reflectance data was collected using an ASD Fieldspec Pro spectroradiometer (400–2500 nm) for over 300 leaf samples. Canopy reflectance data was acquired from the medium resolution imaging spectrometer (MERIS). At the canopy level, with both leaf types combined, the DD-index showed the strongest relationship with leaf chlorophyll (R² = 0.78; RMSE = 3.56 μg/cm²), despite differences in leaf structure. For needleleaf trees alone the relationship with the top VI was weaker (D_[red], R² = 0.71; RMSE = 2.32 μg/cm²). A sensitivity study using simulated VIs from physically-modelled leaf (PROSPECT) and canopy (4-Scale) reflectance was performed in order to further investigate these results and assess the impacts of different background types and leaf area index on the VIs’ performance. At the leaf level, the MNDVI8 index showed a strong linearity to changing chlorophyll and negligible difference to leaf structure/type. At canopy level, the best performing VIs were relatively consistent where LAI ≥ 4, but responded strongly to differences in background at low canopy coverage (LAI = 2). This research provides comprehensive assessments for the use of spectral indices in retrieval of spatially-continuous leaf chlorophyll content at the leaf (MTCI: R² = 0.72; p < 0.001) and canopy (DD: R² = 0.78; p < 0.001) level for resource management over different spatial and temporal scales.