Modeling Urban Growth and Land-Use changes using GIS Based Cellular Automata: Case of Benslimane in Morocco

Abstract

Sustainable urban planning and management require reliable land change models, which can be used to improve decision-making. Over the years, many urban growth models have been developed and used in the developed countries for forecasting growth patterns. In the developing countries, however, there exist a very few studies showing the application of these models and their performances. The study encompasses spatio-temporal land use/land cover (LULC) monitoring (1989–2019) and urban growth modelling (1999–2039) of Benslimane, Morocco to deduce the past and future urban growth paradigm and its influence on varied LULC classes integrating geospatial techniques and Cellular Automata (CA). The study focused on scrutinizing the reliability of the CA algorithm to function independently for urban growth modelling, provided with strong model calibration. For this purpose, satellite data of four stages of time at equal intervals along with the population density, the distance to the city center, the slope and the distance to the roads are used. The satellite-based LULC during 1989-2019 reported an increase of 3.8 Sq. Km (variation of 318%) between 1989 and 2019. The spatial variation analysis using the principal component analysis (PCA) technique exhibit high similarity in classification ranging from 89% to 91%. The projected LULC exhibit that the urban area will increase to 5,044 Sq. Km in 2019, primarily in the west and southwest parts. Between 2019-2039, urban growth will replace and transform other LULC (net loss of 1,364 Sq. Km), followed by vegetation cover (net loss of 0.345 Sq. Km).