Mapping and Predicting Land Use Land Cover Dynamics in the Sefwi Wiawso District, Ghana

Abstract

Land use land cover changes can cause environmental problems; however, few studies have analysed land use land cover changes in Ghana's Sefwi Wiawso District. This study assessed land use land cover changes in Sefwi Wiawso District from 2010 to 2020 and predicted land use land cover changes for 2025 to highlight key shifts and opportunities for sustainable development and spatial planning. The study used Landsat satellite images for three years (2010, 2015, and 2020). The images were classified into four land use land cover classes, namely: closed forest, farmlands, barelands/settlement, and water bodies, using the maximum likelihood classification algorithm. The results obtained revealed closed forest declining from 37.9% in 2010 to 20.5% in 2020. Farmlands however, increased in 2015 but decreased in 2020. Barelands/Settlement showed a rapid increase from 5.7% in 2010 to 25.1% in 2020. To simulate future changes in LULC classes, an Artificial Neural Network - Cellular Automata was used. The simulation showed that barelands/settlement and closed forest may increase in 2025, but farmlands could decrease.