Spatiotemporal analysis of urban expansion and environmental impacts in five Saudi Arabian cities by utilizing geospatial and remote sensing approach

Rapid urbanization in Saudi Arabia has fundamentally reshaped metropolitan landscapes, creating unprecedented challenges for environmental sustainability in arid regions. This study presents a spatiotemporal analysis of urban expansion patterns and associated environmental impacts across five major Saudi cities (Riyadh, Makkah, Jeddah, Madinah, and Dammam) over a 30-year period (1993-2023) using remote sensing and geographic information systems (GIS). We employed supervised classification of multi-temporal Landsat imagery, integrating spectral indices such as NDVI, SAVI, and NDWI to enhance land-cover discrimination. Classification accuracies ranged from 92% to 95.2% and were validated through stratified sampling and error matrix analysis. Post-classification change detection algorithms quantified urban growth dynamics, while binary logistic regression models assessed topographic influences on spatial development patterns. Results reveal dramatic urban transformation across all study cities. Madinah experienced the largest absolute expansion (759.2 km²), followed by Riyadh (648.08 km²) and Jeddah (640.12 km²). Growth rates varied significantly: Riyadh exhibited the highest proportional increase (236.8%), while Makkah showed more constrained expansion (48.92 km²) due to topographic limitations. Spatial analysis identified distinct urbanization patterns, with centralized growth in Makkah and Madinah versus dispersed, sprawling development in Riyadh, Jeddah, and Dammam. Topographic analysis showed that slope significantly influenced urban development in Jeddah (p = 0.003) and Makkah (p = 0.030), while elevation significantly shaped expansion patterns in Riyadh, Jeddah, Makkah, and Madinah (p < 0.05). Model fit statistics (Nagelkerke R² = 0.06-0.24; ROC AUC = 0.56-0.72) indicate that topographic variables provide modest but meaningful explanatory power, with additional socioeconomic variables needed for comprehensive modeling. These findings reveal complex relationships among urban growth, topographic constraints, and environmental pressures in arid metropolitan areas. The observed urban expansion patterns are consistent with documented effects of government policies, oil-driven economic growth, and population migration on Saudi urban landscapes, with potential implications for habitat continuity, local environmental quality, and resource pressures. This research provides baseline data for evidence-based urban planning and offers a replicable methodological approach for monitoring rapid urbanization in similar arid environments.

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Publication Details

Journal
PLoS ONE
Published
2026-09-01
DOI
https://doi.org/10.1371/journal.pone.0354154
Primary Topic
Land Use and Ecosystem Services
Type
article
Field-Weighted Citation Impact
0.00

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article

Spatiotemporal analysis of urban expansion and environmental impacts in five Saudi Arabian cities by utilizing geospatial and remote sensing approach

Jannatun Nahar Fariha, Abdulla ‐ Al Kafy, Ahmed Ali A. Shohan, Saleh Alsulamy et al.
PLoS ONE
Land Use and Ecosystem Services
article

Spatiotemporal analysis of urban expansion and environmental impacts in five Saudi Arabian cities by utilizing geospatial and remote sensing approach

Jannatun Nahar Fariha, Abdulla ‐ Al Kafy, Ahmed Ali A. Shohan, Saleh Alsulamy, Abdullah Al Baky, Md Tanvir Miah, Md Hojaifa Al Hossain Khan
article en

Abstract

Rapid urbanization in Saudi Arabia has fundamentally reshaped metropolitan landscapes, creating unprecedented challenges for environmental sustainability in arid regions. This study presents a spatiotemporal analysis of urban expansion patterns and associated environmental impacts across five major Saudi cities (Riyadh, Makkah, Jeddah, Madinah, and Dammam) over a 30-year period (1993-2023) using remote sensing and geographic information systems (GIS). We employed supervised classification of multi-temporal Landsat imagery, integrating spectral indices such as NDVI, SAVI, and NDWI to enhance land-cover discrimination. Classification accuracies ranged from 92% to 95.2% and were validated through stratified sampling and error matrix analysis. Post-classification change detection algorithms quantified urban growth dynamics, while binary logistic regression models assessed topographic influences on spatial development patterns. Results reveal dramatic urban transformation across all study cities. Madinah experienced the largest absolute expansion (759.2 km²), followed by Riyadh (648.08 km²) and Jeddah (640.12 km²). Growth rates varied significantly: Riyadh exhibited the highest proportional increase (236.8%), while Makkah showed more constrained expansion (48.92 km²) due to topographic limitations. Spatial analysis identified distinct urbanization patterns, with centralized growth in Makkah and Madinah versus dispersed, sprawling development in Riyadh, Jeddah, and Dammam. Topographic analysis showed that slope significantly influenced urban development in Jeddah (p = 0.003) and Makkah (p = 0.030), while elevation significantly shaped expansion patterns in Riyadh, Jeddah, Makkah, and Madinah (p < 0.05). Model fit statistics (Nagelkerke R² = 0.06-0.24; ROC AUC = 0.56-0.72) indicate that topographic variables provide modest but meaningful explanatory power, with additional socioeconomic variables needed for comprehensive modeling. These findings reveal complex relationships among urban growth, topographic constraints, and environmental pressures in arid metropolitan areas. The observed urban expansion patterns are consistent with documented effects of government policies, oil-driven economic growth, and population migration on Saudi urban landscapes, with potential implications for habitat continuity, local environmental quality, and resource pressures. This research provides baseline data for evidence-based urban planning and offers a replicable methodological approach for monitoring rapid urbanization in similar arid environments.

PLoS ONEVol. 21(9)
Texas Tech University (US), Khulna University (BD), United International University (BD), King Khalid University (SA), The University of Texas at Austin (US)
Deanship of Scientific Research, King Khalid University, King Khalid University
Sustainable cities and communities
Openalex Percentile: Top 13%
Land Use and Ecosystem Services
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