Modeling Dynamic Urban Growth Using Cellular Automata and Geospatial Technique: Case of Casablanca in Morocco

Abstract

The rapid urbanisation contribute to the spatial expansion in cities.However, the rapid and unmanaged urban growth, degraded the urban environment. In casablanca the economic engine of Morocco, the rapid urbanization was a result of demographic explosion, rural exodus, and the introduction of new urban projects. Understanding the interdependencies between urban growth patterns, infrastructure, and socioeconomic indicators is a critical step in achieving a sustainable urban development. In order to help Casablanca's sustainable growth, this study used remote sensing data to evaluate past urban land use changes. This study was conducted to examine past urban land cover change on the basis of remote sensing data collected between 1989 and 2019. To forecast the city's expansion for the years 2019e2029, an integrated Cellular Automata urban growth model was used. The research looked into the CA algorithm's capacity to work independently for urban development modeling satellite data from four time periods at equal intervals, as well as population density, distance to the city center, slope, and distance to roadways, are used for this purpose. Between 1989 and 2019, the satellite-based LULC reported an increase of 61.77Km2 (an 88 percent increase). The principle component analysis (PCA) technique was used to analyze geographic variation and found good classification similarity ranging from 87 to 90%. Based on the anticipated LULC, the built-up area will grow to 131.88 km2 in 2019, mostly in the west and southwest. Urbanization will replace and transform other LULC (net loss of 15.348Km2) between 2019 and 2029, followed by plant cover (net loss of 1.608Km2).