Comparative Study of Coastal Vulnerability in Morocco: In-depth Analysis of the Atlantic and Mediterranean Coasts through Machine Learning Models

The northern coast of the Sebou estuary along the Atlantic Ocean has relatively low topography, exposing the region to erosion and accretion. Machine learning models, including Random Forest, Decision Tree, and Support Vector Machine, were applied to assess coastal vulnerability. Results show that 20.1 % of the coastline is moderately vulnerable, 10.4 % is highly vulnerable, and 69.6 % is lowly vulnerable.,The Mediterranean coast, particularly the Tangier-Tetouan region, experiences higher salinity and Mediterranean climate conditions. Models such as Artificial Neural Networks, Decision Tree, Logistic Regression, Random Forest, and Support Vector Machine were employed. Approximately 19.9 % of the coastline is highly vulnerable, 20.9 % moderately vulnerable, and 59.1 % lowly vulnerable.,In summary, the low topography of the Atlantic coast increases its susceptibility to coastal changes, while the Mediterranean coast is influenced by salinity and regional climate. Model performances vary, but some algorithms provide accurate and useful results for coastal zone management and adaptation planning.