Assessment of Forest Carbon Stock Using Remote Sensing in Edo State

Accurate estimation of forest carbon stocks is essential for Nigeria's commitments under the Paris Agreement and the REDD-plus mechanism. This study estimates above-ground biomass and carbon stock in the Okomu National Park and surrounding forest reserves in Edo State using a combination of Sentinel-2 multispectral imagery and airborne LiDAR-derived canopy height data. Allometric equations calibrated for West African tropical forests are applied to generate above-ground biomass estimates at 10-metre spatial resolution. Sentinel-2 spectral bands and vegetation indices are used to extrapolate LiDAR-calibrated biomass estimates across the full study area extent. A stepwise regression model relating spectral predictors to field-measured biomass achieves a cross-validated R-squared of 0.78. Results indicate total carbon stocks of approximately 4.2 million tonnes of carbon dioxide equivalent across the 120,000-hectare study area. Spatial distribution maps reveal the highest carbon density in interior primary forest, with significantly reduced values in degraded secondary forest along reserve margins. Keywords: forest carbon, remote sensing, biomass estimation, Edo State, REDD-plus