Probabilistic Cellular Automata modelling and simulation of land-use changes in Okomu National Park

Land use, land cover (LULC) change technique is essential for measuring ecological quality, environmental sustainability, and uncontrolled development at various spatiotemporal scales. To construct effective use management plans, the probable future scenario of LULC changes can be easily detected utilizing a simulation technique.This study monitors models land-use in Okomu National Park over two decades (2000 – 2020) to project forest near future. A probabilistic cellular automata (CA) model was created used simulate with aim predicting scenarios. Landsat7 ETM+ satellite images years 2000, 2005, 2010, 2015, 2020 were classified into Forest Non–Forest using maximum likelihood supervised classification algorithm. Moore’s neighborhood Von Neumann extension year 2000 as base year.The overall accuracy under 98.18%, 97.52%, 96.33%, 91.67%, 94.61%with kappa coefficients 0.97, 0.96, 0.95, 0.86, 0.91 respectively. State transition probabilities 2000–2005, 2005–2010, 2010–2015, 2015–2020 calculated from images. Simulation accuracywas 77.46%, 74.1%, 70.98%, 78.27% Projections made 2025 2030 it shows 27.41% decline by anda 29.90% 2030.The amount actual simulated gradual drop 185.15 km2 136.07 135.30 2020, respectively.Spatial models, which provide scientific basis supporting sustainable based on different scenarios alsocontribute significantly implementation framework United Nations' Reducing Emissions Deforestation Degradation (REDD/REDD+) program, well reference REDD/REDD+ incentive payments.