Assessing Forest Structure and Biomass Loss in Mount Cameroon National Park Using Remote Sensing and Machine Learning
Kato Samuel Namuene *
Department of Forestry and Wildlife, University of Buea, PMB 63 Buea, Cameroon.
Ambo Beatrice Fonge
Department of Plant Science, University of Buea, PMB 63 Buea, Cameroon, Cameroon.
Agbor James Ayamba
Department of Forestry and Wildlife, University of Buea, PMB 63 Buea, Cameroon.
*Author to whom correspondence should be addressed.
Abstract
Tropical montane forests of Cameroon represent disproportionately important per-unit-area carbon stocks and biodiversity repositories, yet remain among the least monitored protected landscapes in West and Central Africa. This study presents a comprehensive, multi-temporal remote sensing and machine learning assessment of forest structural dynamics and above-ground biomass (AGB) loss across the full extent of Mount Cameroon National Park (MCNP) between 2000 and 2023. Multi-source satellite data comprising Landsat 5/8, Sentinel-2, ALOS PALSAR-2 L-band SAR, and ICESat-2 ATL08 spaceborne LiDAR were integrated within Google Earth Engine. A Random Forest classifier achieved an overall land cover classification accuracy of 95.8% (Kappa = 0.942). AGB estimation models were calibrated against 6,842 GEDI L4A spaceborne retrievals and 4,614 ICESat-2 ATL08 segments across five altitudinal vegetation zones, yielding R² = 0.884 and RMSE = 20.31 Mg ha⁻¹, with multi-sensor fusion delivering an R² improvement of 0.150 over optical-only models. SHAP analysis identified PALSAR-2 HV backscatter as the dominant predictor (mean |SHAP| = 0.221), followed by ICESat-2 canopy height (0.179) and EVI (0.158). Dense closed-canopy forest declined from 37,309 ha (64.1%) in 2000 to 26,955 ha (46.3%) in 2023, representing a 176% increase in annual deforestation rate, from 358 ha yr⁻¹ to 987 ha yr⁻¹. Total AGB declined from 10.31 Tg to 7.04 Tg, generating cumulative carbon emissions of 5.04 Tg CO₂e. ICESat-2 ATL08 confirmed a mean canopy height reduction of 6.3 m in degraded forest zones between 2019 and 2023, with structural divergence between intact and degraded forest increasing from 8.4 m to 13.4 m. Road proximity was the dominant deforestation driver (Spearman ρ = -0.76), with the agricultural frontier migrating upslope by 350 m over the study period. These findings provide spatially explicit quantitative evidence supporting REDD+ Tier 2 carbon accounting and adaptive management in this critical Afromontane protected landscape.
Keywords: Aboveground biomass, Afromontane Forest, ALOS PALSAR-2, deforestation hotspots, google earth engine, ICESat-2, mount Cameroon national park, REDD+