Mapping tree aboveground biomass and carbon in Omo Forest Reserve Nigeria using Landsat 8 OLI data
Protected areas in Nigeria are important ecosystems for carbon storage. The aim of this study was to estimate and map tree aboveground biomass (TAGB) and carbon (TAGC) within a tropical forest in Nigeria. Stepwise regression analysis was implemented to develop models for predicting TAGB in the forest stand, by integrating field TAGB data with Landsat 8 OLI data. Spectral variables used in the analysis include spectral bands, vegetation indices, tasseled cap indices and principal components. Model validation was performed using independent sample plots. The results showed that incorporating more than one category of spectral variables improved the prediction of TAGB. The best-fit model was applied to map the spatial distribution of TAGB and TAGC. The TAGC was estimated as 52.3% of TAGB, based on the average carbon content of tree species derived in this study. Average TAGB and TAGC estimates for the forest stand were 373.1 ± 165.4 t ha−1 and 194 ± 82.7 t ha−1, respectively. Reliable estimates of TAGB and TAGC for the forest reserve were obtained. This study provides important information required to manage the forest stand for optimal carbon sequestration.
Keywords: aboveground biomass, climate change mitigation, forest carbon, Landsat, remote sensing