Knowledge Agora



Scientific Article details

Title Modelling past and future land use and land cover dynamics in the Nakambe River Basin, West Africa
ID_Doc 67070
Authors Yangouliba, GI; Zoungrana, BJB; Hackman, KO; Koch, H; Liersch, S; Sintondji, LO; Dipama, JM; Kwawuvi, D; Ouedraogo, V; Yabré, S; Bonkoungou, B; Sougué, M; Gadiaga, A; Koffi, B
Title Modelling past and future land use and land cover dynamics in the Nakambe River Basin, West Africa
Year 2023
Published Modeling Earth Systems And Environment, 9, 2
DOI 10.1007/s40808-022-01569-2
Abstract Understanding land use and cover (LULC) dynamic is of great importance to sustainable development in Africa where deforestation is a common problem. This study aimed to assess the historical and future dynamics of LULC in the Nakambe River Basin. Landsat images were used to determine LULC dynamics for the years 1990, 2005 and 2020 using Random Forest classification system in Google Earth Engine while the predicted LULC of 2050 was simulated using the Markov Chain and Multi-Layer-Perceptron neural network in Land Change Modeler. The findings showed significant changes in LULC patterns. From 1990 to 2020, woodland and shrubland decreased by - 45% and - 68%, respectively, while water body, cropland and bare land/built-up increased by 233%, 51%, and 75%, correspondingly. From 2020 to 2050, the results revealed that under the Business-as-usual scenario, bare land/built-up and water bodies could continue to increase by 99% and 1%, respectively. However, cropland, shrubland, and woodland could decrease by - 32.61%, - 33.91%, and - 46.86%, respectively. Under the afforestation scenario, the contrary of Business-as-usual could occur. While woodland, shrubland, and cropland would increase by 22.24%, 51.57%, and 18.13%, correspondingly, between 2020 and 2050, the area covered by water bodies and bare land/built-up will decrease by - 6.16% and - 39.04%, respectively. The results of this research give an insight into past and future LULC dynamics in the Nakambe River Basin and suggest the need to strengthen the policies and actions for better land management in the region.
Author Keywords Land use; land cover; Random forest; Markov chain; Multi-layer-perceptron neural network; Land change modeler; Nakambe River Basin
Index Keywords Index Keywords
Document Type Other
Open Access Open Access
Source Emerging Sources Citation Index (ESCI)
EID WOS:000876220700002
WoS Category Environmental Sciences
Research Area Environmental Sciences & Ecology
PDF
Similar atricles
Scroll