Predictive modelling on Spatial–temporal Land Use and Land Cover changes at the Casablanca-Settat Region in Morocco

• Published in: Modeling earth systems and environment 2024-09, Vol.10 (6), p.6691-6714
• Main Authors: Sabri, Anas, Bahi, Hicham, Bounoua, Lahouari, Tahiri, Mounia, Tweed, Sarah, LeBlanc, Marc, Bouramtane, Tarik, Malah, Anass, Kacimi, Ilias
• Format: Article
• Language: English
• Subjects: Agricultural land; Barren lands; Biodiversity; Chemistry and Earth Sciences; Computer Science; Decision making; Earth and Environmental Science; Earth Sciences; Earth System Sciences; Economics; Ecosystems; Environment; Environmental Sciences; Global Changes; Human influences; Hydrology; Land cover; Land use; Markov chains; Math. Appl. in Environmental Science; Mathematical Applications in the Physical Sciences; Modelling; Multilayers; Original Article; Physics; Population (statistical); Population growth; Prediction models; Predictions; Public health; Satellite observation; Sciences of the Universe; Statistical analysis; Statistical methods; Statistical models; Statistics for Engineering; Urban areas; Urban development; Urban populations; Urbanization
• ISSN: 2363-6203; 2363-6211
• DOI: 10.1007/s40808-024-02107-y

  Urban Population growth coupled with human activities are the main drivers inducing land use and land cover changes (LU/LCC), which impact earth’s landscapes dynamics. In the era of global challenges, a comprehensive modelling of past and future prediction of LU/LCC is therefore essential. In this regard, the current study aims to model LU/LCC and predict its changes by 2030, 2050 and 2100. Moreover, determine the main driver of these changes, and assess the impact of urbanization on natural ecosystems. For doing so, a three-decade times series (1992–2020) data have been used, including LU/LC, environmental, societal, and auxiliary data to conduct a statistical analysis and modelling using hybrid Multi-Layer-Perceptron Markov-Chain model (MLP-MC). The analyses results showed that urbanization has significantly increased between 1992 and 2020, mainly in the outskirts of the Casablanca metropolis, where economic dynamic, population growth, and territorial infrastructure takes place. This increase was at the expense of barren and agricultural land. Concerning the future projection, the MLP-MC model showed satisfactory results with an overall accuracy (OA) and Cohen’s Kappa greater than 0.98 Revealing that the model has batter reliability to predict LU/LC maps that are identical to observed ones. Consequently, the Future projection indicates that urban areas will persistently sprawl, especially in satellite cities of the economic capital which adversely affect biodiversity, local climate, water, and public health. These findings remain so promising that can guide decision-making and stakeholders to improve sustainable territorial and urban development.