Predictive Land Use Change under Business-As-Usual and Afforestation Scenarios in the Vea Catchment, West Africa

Isaac Larbi, Gerald Forkuor, Fabien C.C. Hountondji, Wilson Agyei Agyare, Daouda Mama, (doi: 10.23953/cloud.ijarsg.416)


This study aimed to assess the historical Land use/land cover (LULC) changes and project the future (2025) LULC pattern in the Vea catchment based on Business as Usual (BAU) and afforestation scenarios of land use. Landsat Imagery of 1990, 2001, 2011 and 2016 were classified at overall accuracy assessment of 82%, 86%, 85% and 88% respectively. Major transitions were modeled using the Multi-layer Perceptron Neural Network algorithm, and the future scenarios maps of LULC were projected based on the Markov chain after validation of the Land Change Modeler. The results indicate the conversion of forest/mixed vegetation (23.1%) and grassland (76.9%) to cropland as the dominant LULC conversion from 1990 to 2016. An increase in cropland, built-up areas, and water bodies were observed while grassland and forest/ mixed vegetation decreased over the last 27 years. The 2025 LULC simulation indicates continuous expansion of cropland at the expense of forest/mixed vegetation which is projected to decrease by 4.5% in 2025 for the BAU scenario. Under afforestation scenario, where forest/mixed vegetation and grassland are expected to increase, cropland is projected to decrease by 20% in 2025. These findings set a reference ground for sustainable land use governance through responsible planning and management of land and water resources by considering trade-offs between cropland expansion and ecosystems’ preservation in the Vea catchment.


Cropland; Land change modeler; land use/land cover change; Vea catchment

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