Simulating Urban Growth Using Cellular Automata Approach (SLEUTH)-A Case Study of Praia City, Cabo Verde

Abstract

In recent years, urban growth has become the center of attention and preoccupation for many researchers especially those concerned with urban planning. Some scholars only take into consideration the social dynamism and demographic data of an area of interest while analyzing the urban growth. However, those approaches fail to consider other physical conditions such as the urban extent and exclusion zones (e.g. rivers and forest reserves). This makes it difficult to correctly model the urban expansion as well as simulate for future forecast, which is vital for policymakers and city planners when making informed decisions. This study, therefore, used the Geographic Information System (GIS) to compile the data obtained from a time series of satellite images between 1984 and 2018 for the urban growth model calibration. A modified cellular automata methodology called SLEUTH was then applied to supervise and forecast the urban sprawl in Praia city, the capital of Cabo Verde from the year 1984 to 2050. The forecasted result showed that breed (100) and road (62) coefficients would influence the urban growth in Praia city. This means that there is a likelihood of newly generated detached settlements and many new buildings along the roadside.

Keywords

• Urban growth
• remote sensing
• GIS
• cellular automata -SLEUTH and Praia city