Quantification, Valuation and Mapping of Carbon Stocks in Relation to Land Cover Dynamics in Ghana

Abstract

Land use and land cover (LULC) change is a major driver of carbon emissions and ecosystem transformation, with significant implications for climate change mitigation and sustainable development. This study provides a comprehensive assessment of LULC dynamics from 2018 to 2024, with projections to 2030 under a Business-as-Usual scenario, and quantifies their impacts on carbon storage, sequestration, and the economic value of carbon in Ghana. Environmental Systems Research Institute global land cover data at 10 m resolution was reclassified for Ghana; future LULC was projected using the MOLUSCE plugin in QGIS, and the InVEST carbon model was used to estimate carbon stocks and their monetary value. Results show Trees Outside Forests (TOF) declined by 14% (11981 km²) between 2018 and 2024 and is projected to decline a further 6% (5113 km²) by 2030, while forest reserves remained stable. This decline contributed to a reduction in total carbon storage to 7227 million t C (301.7 t C ha⁻¹) in 2024. Projections show a partial recovery to 7563 million t C (315.7 t C ha⁻¹) by 2030, driven by a projected expansion of the forest reserves; however, no net sequestration was observed relative to the 2017 primary baseline (8055 Mt C). This persistent carbon deficit is primarily driven by the decline in TOF, which acted as the main catalyst for the national carbon loss signal, whereas protected forest reserves remained relatively stable. Economic losses are profound, totaling US$12,032 million (US$662/ha) in 2024 and a projected US$5,398 million (US$347/ha) in 2030. Although losses slowed by 55%, this deceleration does not signify recovery. The national carbon Net Present Value remains consistently negative through 2030, yielding no net economic gains relative to the baseline. The findings underscore the urgent need for targeted land management policies, especially for TOF, to enhance carbon sequestration and support Nationally Determined Contribution targets.