Estimating LAI and mapping canopy storage capacity for hydrological applications in wattle infested ecosystems using Sentinel-2 MSI derived red edge bands

This study assessed the strength of Sentinel-2 multispectral instrument (MSI) derived Red Edge (RE) bands in estimating Leaf Area Index (LAI) and mapping canopy storage capacity (CSC) for hydrological applications in wattle infested ecosystems. To accomplish this objective, this study compared the estimation strength of models derived, using standard bands (all bands excluding the RE band) with those including RE bands, as well as different vegetation indices. Sparse Partial Least Squares (SPLSR) and Partial Least Squares Regression (PLSR) ensembles were used in this study. Results showed that the RE spectrum covered by the Sentinel-2 MSI satellite reduced the estimation error by a magnitude of 0.125 based on simple ratio (RE SR) vegetation indices from 0.157m(2)m(-2) based on standard bands, and by 0.078m(2)m(-2) based on red edge normalised difference vegetation (NDVI-RE). The optimal models for estimating LAI to map CSC were obtained based on the RE bands centered at 705nm (Band 5), 740nm (Band 6), 783nm (Band 7) as well as 865nm (Band 8a). A root mean square error of prediction (RMSEP) of 0.507m(2)m(-2) a relative root mean square error of prediction (RRMSEP) of 11.3% and R-2 of 0.91 for LAI and a RMSEP of 0.246m(2)/m(2) (RRMSEP=7.9%) and R-2 of 0.91 for CSC were obtained. Overall, the findings of this study underscore the relevance of the new copernicus satellite product in rapid monitoring of ecosystems that are invaded by alien invasive species.