Comparative study on stochastic and deterministic approaches in urban growth model

Urban growth always relates to the combination of natural increase in urban population and immigration of people to urban areas. Urbanization is very closely linked to industrialization, commercialization or overall economic growth and development. The process of urbanization exhibits a pattern in which the rate rises steeply in the early stages of industrialization, and tapers off gradually when the proportion reaches a saturation point. Finally, as most of populations become urbanized, urbanization falls to keep pace continuously with the economic development. In this study, “model” means how the data are manipulated by regression technique based on deterministic or stochastic technique. This study aims to compare these two different regression techniques for their spatial structure models on urban growth at the same specific study area. Moreover, both techniques will use the same datasets and their results will be analyzed to determine any similarity or difference between them. The work starts by producing an urban growth model by using the stochastic technique through geographical weighted regression (GWR). Later, the deterministic technique will be used based on radial basis functions (RBF). In general, the urban growth changes for both models are very similar. Thus, the deterministic technique can be considered as an alternative when details information are lacking.