Tracking Urban Expansion Using Random Forests for the Classification of Landsat Imagery (1986–2015) and Predicting Urban/Built-Up Areas for 2025: A Study of the Kumasi Metropolis, Ghana

Kumasi is a nodal city and functions as the administrative economic capital of Ashanti region in Ghana. Rapid urbanization has been experienced inducing transformation various Land Use Cover (LULC) types into urban/built-up areas Kumasi. This paper aims at tracking spatio-temporal LULC changes utilizing Landsat imagery from 1986, 2013 2015 The unique contribution this research its focus on urban expansion analysis utilization Random Forest (RF) Classifier for satellite image classification. Change detection, land modelling sub-metropolitan zones, buffers, density decay curve correlation were methodologies adopted our study. classifier yielded better accuracy compared to earlier works evaluation indicated that are continually increasing expense agricultural forestlands. occupied 4622.49 hectares (ha) (23.78%), 13,447.50 ha (69.18%) 14,004.60 (72.05%) 2015, respectively 19,438 area Projection will occupy 15,490 (79.70%) 2025. was statistically significant. results revealed importance spatial modeling environmental management planning.