Spatiotemporal Monitoring and Prediction of Land Use Integrating the Markov Chain and Cellular Automata in the Coastal Chaouia

Abstract

In the last decades, the world population rate has been gradually increasing, this population growth has faced intense urban expansion and the rapid development of the agricultural and industrial sectors. This change had an impact on the mode of land use. In the face of this problem, several strategies have been created for monitoring and predicting possible future scenarios on rhythm of land use change. The CA-Markov model used in this research allows to predict future land use trends on the basis of the classified maps of 1987, 1999, 2011 and 2019. Simulating and tracking these maps is a major challenge. The latter provides important information in terms of data, methods and models to be used to create a realistic and sustainable process of territory planning for environmentalists, planners and local authorities. The combination of the Markov chain and cellular automata has been used to qualitatively and quantitatively simulate and evaluate future land use trends in coastal Chaouia, Morocco. To achieve this purpose, two maps were developed for the two years of 2027 and 2035. By using kappa, the global success of the modelling was 89.22% and 82.12% respectively in 2011 and 2019 for the projected land use map. The results confirm that forests have been affected by intensive agricultural uses. This increase in agricultural use is due to the impact of the constant increase in the development of the agroeconomic and demographic sectors. This situation indicates the need to create new approach to management to protect the sustainability of land use in coastal Chaouia.