Investigating Durban’s Morphological Dynamics and Spatial Prediction Techniques for Urban Geography Pedagogy
This study highlighted the transformative potential of geospatial analysis and spatial prediction techniques in using the dynamic morphology of Durban Metropolis as a model for fostering innovative, data-driven learning experiences. The methodology integrated quantitative and geospatial data analysi...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Noyam Journals
2025-07-01
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| Series: | E-Journal of Humanities, Arts and Social Sciences |
| Subjects: | |
| Online Access: | https://noyam.org/wp-content/uploads/2025/07/JELT2025676.pdf |
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| Summary: | This study highlighted the transformative potential of geospatial analysis and spatial prediction techniques in using the dynamic morphology of Durban Metropolis as a model for fostering innovative, data-driven learning experiences. The methodology integrated quantitative and geospatial data analysis of Land Use and Land Cover (LULC) changes from 2004 to 2024 using Geographic Information Systems (GIS)-based change detection tools to identify and predict LULC change patterns in 2034. The research findings revealed that built-up areas expanded significantly from 123.21 km² (5.38%) in 2004 to 442.92 km² (19.32%) in 2024, while agricultural lands, dense vegetation, and water bodies steadily declined, signalling ongoing environmental changes and urban pressures that are predicted to intensify to 520.3 km2 (22.7%) by 2034. The study concluded that Durban Metropolis is rapidly expanding with a concomitant decline in vegetation LULC, thus highlighting the urgent need for sustainable urban planning and environmental conservation strategies. These findings have profound implications for urban geography pedagogy, providing data-driven insights that enhance curriculum development, equip students with spatial analysis skills, and promote informed decision-making on urban sustainability challenges. This study is original in integrating historical LULC analysis, GIS-based spatial modelling, and urban geography pedagogy, thereby offering a novel approach to linking urban studies with educational applications. This study recommends the integration of GIS-based predictive modelling into urban geography education, contributing to research knowledge by offering an innovative, data-driven approach that enhances spatial literacy, informs sustainable urban planning, and empowers students with real-world analytical skills for addressing future urban challenges. |
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| ISSN: | 2720-7722 |