Previous Article in Journal
A Hybrid AHP–TOPSIS–SBSC Framework for Sustainable Soil Protection in Surface Coal Mining
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Hybrid Spatial Analysis of Rurban Dynamics Using Geospatial and Socio-Economic Data: Case of Casablanca–Settat Region

1
Department of Cartography and Photogrammetry, School of Geomatics and Surveying Engineering, Agriculture and Veterinary Medicine Institute Hassan II, Rabat 10000, Morocco
2
National Agronomic Research Institute, Rabat 10000, Morocco
*
Author to whom correspondence should be addressed.
Environments 2026, 13(6), 339; https://doi.org/10.3390/environments13060339 (registering DOI)
Submission received: 19 May 2026 / Revised: 4 June 2026 / Accepted: 12 June 2026 / Published: 14 June 2026
(This article belongs to the Section Environmental Economics, Energy Systems and Policymaking)

Abstract

Rurbanization and peri-urbanization are among the most dynamic territorial processes affecting metropolitan regions in Morocco, particularly within the Casablanca–Settat region. These transformations, driven by rapid urban growth, demographic pressure, and socio-economic change, generate complex transitional spaces between rural and urban environments. In this context, the present study proposes a hybrid methodology for detecting, classifying, and analyzing the rural–urban continuum by using remote sensing data and artificial intelligence techniques. The approach integrates Sentinel-2 satellite imagery, spectral indices, Global Human Settlement Layer datasets, and socio-demographic indicators derived from the Moroccan census. Two models, Self-Organizing Maps (SOM) and Graph Neural Networks (GNN), were applied to classify territories into four categories: urban, peri-urban, rurban, and rural. Model outputs were combined with expert-based decision rules to improve classification robustness and interpretability. The SOM model achieved up to 89.3% agreement with expert classifications and a Cohen’s Kappa coefficient of 0.842, demonstrating strong interpretability and consistency, while the GNN model reached 53% agreement and effectively modeled spatial dependencies and neighborhood interactions. Diachronic analysis between 2014 and 2024 revealed a 54% increase in peri-urban municipalities, a 24% decrease in rurban territories, and a decline in rural municipalities, highlighting intensified urban sprawl and fragmentation of agricultural landscapes. Beyond its scientific contribution, this study provides a valuable decision-support framework for urban planners, environmental agencies, and policy makers involved in territorial governance and sustainable development. It can support land-use planning, monitoring of urban sprawl, protection of agricultural lands, and the implementation of adaptive territorial policies aimed at improving the resilience and sustainability of rurban environments.
Keywords: rurbanization; peri-urbanization; Self-Organizing Maps (SOM); Graph Neural Networks (GNN); rurban continuum; territorial dynamics; machine learning rurbanization; peri-urbanization; Self-Organizing Maps (SOM); Graph Neural Networks (GNN); rurban continuum; territorial dynamics; machine learning

Share and Cite

MDPI and ACS Style

Moussaoui, A.; Sifa, A.; Zerrouk, M.; Benabdelouahab, T.; Sebari, I.; Aitelkadi, K. Hybrid Spatial Analysis of Rurban Dynamics Using Geospatial and Socio-Economic Data: Case of Casablanca–Settat Region. Environments 2026, 13, 339. https://doi.org/10.3390/environments13060339

AMA Style

Moussaoui A, Sifa A, Zerrouk M, Benabdelouahab T, Sebari I, Aitelkadi K. Hybrid Spatial Analysis of Rurban Dynamics Using Geospatial and Socio-Economic Data: Case of Casablanca–Settat Region. Environments. 2026; 13(6):339. https://doi.org/10.3390/environments13060339

Chicago/Turabian Style

Moussaoui, Asmaa, Abdelghafour Sifa, Marwa Zerrouk, Tarik Benabdelouahab, Imane Sebari, and Kenza Aitelkadi. 2026. "Hybrid Spatial Analysis of Rurban Dynamics Using Geospatial and Socio-Economic Data: Case of Casablanca–Settat Region" Environments 13, no. 6: 339. https://doi.org/10.3390/environments13060339

APA Style

Moussaoui, A., Sifa, A., Zerrouk, M., Benabdelouahab, T., Sebari, I., & Aitelkadi, K. (2026). Hybrid Spatial Analysis of Rurban Dynamics Using Geospatial and Socio-Economic Data: Case of Casablanca–Settat Region. Environments, 13(6), 339. https://doi.org/10.3390/environments13060339

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop