Predicting land use/land cover changes in the Santchou Wildlife Reserve (Santchou, West-Cameroon) using a CA-Markov model

Over the last three decades, the Santchou Wildlife Reserve (SWR) located in the West region of Cameroon has experienced rapid degradation. Land reclamation and population growth have significantly contributed to meeting the increasing demands for foods and urban development. In this study, Landsat 4–5 Thematic Mapper (TM) images of 1988 and 2005, and Landsat 8 Operational Land Imager and Thermal Infrared Sensor (OLI-TIRS) image of 2022 are firstly used for calculating and analysing area changes and then spatial distribution of land use/land cover changes (LULCC) in the SWR for a time span 1988–2005–2022. Secondly, the spatial distribution of LULCC from 2022 to 2027 and from 2027 to 2032 was simulated using a Cellular Automata (CA)-Markov model that allows to predict future changes and identify the possible patterns of evolution. Results exhibit six major LULC classes including Mountain Forest, Degraded Lowland Forest, Lowland Forest, Degraded Mountain Forest, Built-up Area and Cultivated Land. The overall accuracies of LULC classification reached 89.71‒92.24 %, with Kappa coefficients of 0.87‒0.92. However, the prediction model was validated with an overall good agreement of 90.51 %. In general, two significant patterns of change were evidenced and characterized by the rapid expansion of Cultivated Land from 158.6 to 736.4 ha between 1988 and 2022, and could reach 809.0 ha in 2032, while Built-up Area displays a surface change from 12.4 to 29.3 ha, which is expected to attend 67.3 ha in 2032. Change patterns from the past to the future are also marked by a decline of Mountain Forest (2107.4 to 1594.4 ha), Degraded Lowland Forest (1450.1 to 1024.5 ha) and Degraded Mountain Forest (954.6 to 860.6 ha) at the expense of Lowland Forest (2332.5 to 2659.8 ha). Human activities influenced by socio-economic issues remain the main factor of changes in the SWR. Despite the limitations of the CA-Markov model due to the non-consideration of socio-economic factors, this study appears as a new opportunity to develop effective strategies for managing LULCC and protecting ecological biodiversity in the SWR.