The impact of integrating WorldView-2 sensor and environmental variables in estimating plantation forest species aboveground biomass and carbon stocks in uMgeni Catchment, South Africa

Abstract

Reliable and accurate mapping and extraction of key forest indicators of ecosystem development and health, such as aboveground biomass (AGB) and aboveground carbon stocks (AGCS) is critical in understanding forests contribution to the local, regional and global carbon cycle. This information is critical in assessing forest contribution towards ecosystem functioning and services, as well as their conservation status. This work aimed at assessing the applicability of the high resolution 8-band WorldView-2 multispectral dataset together with environmental variables in quantifying AGB and aboveground carbon stocks for three forest plantation species i.e. Eucalyptus dunii (ED), Eucalyptus grandis (EG) and Pinus taeda (PT) in uMgeni Catchment, South Africa. Specifically, the strength of the Worldview-2 sensor in terms of its improved imaging agilities is examined as an independent dataset and in conjunction with selected environmental variables. The results have demonstrated that the integration of high resolution 8-band Worldview-2 multispectral data with environmental variables provide improved AGB and AGCS estimates, when compared to the use of spectral data as an independent dataset. The use of integrated datasets yielded a high R2 value of 0.88 and RMSEs of 10.05tha−1 and 5.03tCha−1 for E. dunii AGB and carbon stocks; whereas the use of spectral data as an independent dataset yielded slightly weaker results, producing an R2 value of 0.73 and an RMSE of 18.57tha−1 and 09.29tCha−1. Similarly, high accurate results (R2 value of 0.73 and RMSE values of 27.30tha−1 and 13.65tCha−1) were observed from the estimation of inter-species AGB and carbon stocks. Overall, the findings of this work have shown that the integration of new generation multispectral datasets with environmental variables provide a robust toolset required for the accurate and reliable retrieval of forest aboveground biomass and carbon stocks in densely forested terrestrial ecosystems.