Modeling Urban Growth and Future Scenario Projections forChinhoyi, Zimbabwe using Cellular Automata

Abstract

Land use land cover (LULC) change processes in less developed countries are typically rapid and extensive, and they often include a considerable proportion of unplanned or informal development. Land use land cover change models can help to understand, analyse and simulate the outcomes of such processes, providing information that can inform policy development. Rapid urbanisation presents a land planning conundrum for town planners and policymakers besides disenfranchising urban green spaces and encroaching into peri urban areas in the developing town of Chinhoyi in Zimbabwe. This necessitates for predicting future urban growth using modern and accurate techniques. This study aims to i) model the urban growth and ii) project future scenarios of a developing town, Chinhoyi in Zimbabwe using Cellular Automata. Landsat satellite images for the interval years 2000, 2013 and 2021 were used for data analysis. Spatial variables comprising rivers, Digital Elevation Model (DEM), slope, Central Business District (CBD) and Euclidean distances of the city roads in tandem with Land Use Land Cover images were analysed using Cellular-Automata model. LULC were significantly different (p<0.05) for 2000–2013 with non significant changes between 2013 2021. Cellular Automata prediction model shows marginal growth in Chinhoyi by 2050. This is attributed to
fewer land categories which can be converted in the CA model. For broader use the current CA model need more and new parameters (driving factors) to improve its urban growth prediction accuracy. Simulation of future land use can provide decision support for urban planners and decision makers, which is important for sustainable urban expansion in developing countries.