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Urban Growth Monitoring and Prediction Using Remote Sensing Urban Monitoring Indices Approach and Integrating CA-Markov Model: A Case Study of Lagos City, Nigeria

Author

Listed:
  • Katabarwa Murenzi Gilbert

    (College of Surveying and Geo-Informatics, Tongji University, Shanghai 200092, China)

  • Yishao Shi

    (College of Surveying and Geo-Informatics, Tongji University, Shanghai 200092, China)

Abstract

As one of the swiftly advancing megacities globally, Lagos faces significant challenges in managing its urban expansion. Mainly, this study focuses on monitoring and predicting urban growth using a comprehensive approach incorporating Global Land 30 (GL30), satellite-based nighttime light observations, and built-up and population density data. The application of remote sensing techniques, combined with utilizing the GL30 dataset, provides an effective means to monitor and predict urban growth trends and patterns. The major patterns occurred from 2000 to 2020, including increased cultivated land; reductions in grasslands, shrublands, and wetlands; and major urbanization. Predictive models indicate that urbanization will continue. Furthermore, employing the Cellular Automata (CA) Markov model in land-use and land-cover (LULC) change prediction. The findings revealed significant changes in LULC over the two decades. Particularly, the percentage of artificial terrain increased from 17.016% to 25.208%, and the area under cultivation increased significantly, rising from 46,771 km 2 (1.238%) in 2000 to 75,283 km 2 (1.993%) in 2020. Grasslands fell from 7.839% to 1.875%, while forest cover somewhat increased, climbing from 39.319% to 43.081%. Additionally, marshes fell from 9.788% to 5.646%, while shrublands decreased from 4.421% to 2.640%. Surprisingly, bare ground decreased sharply from 0.677% to 0.003%. To forecast future LULC changes, the study also used a Markov Chain Transition Matrix. According to the data, there is a 3.54% chance that agricultural land will become urban, converting it from being used for agriculture to urban development. On the other hand, just 1.05% of forested regions were likely to become municipal areas. This study offers foundations for the upcoming research to enhance urban growth models and sustainability strategies in the face of rising urbanization and environmental concerns in the region, as well as laying the groundwork for informed decision-making in the region.

Suggested Citation

  • Katabarwa Murenzi Gilbert & Yishao Shi, 2023. "Urban Growth Monitoring and Prediction Using Remote Sensing Urban Monitoring Indices Approach and Integrating CA-Markov Model: A Case Study of Lagos City, Nigeria," Sustainability, MDPI, vol. 16(1), pages 1-20, December.
    • Handle: RePEc:gam:jsusta:v:16:y:2023:i:1:p:30-:d:1303287
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    References listed on IDEAS

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    1. Jing Ma & Dan Liu & Zhengwen Wang, 2023. "Sponge City Construction and Urban Economic Sustainable Development: An Ecological Philosophical Perspective," IJERPH, MDPI, vol. 20(3), pages 1-17, January.
    2. Yang, Xin & Zheng, Xin-Qi & Chen, Rui, 2014. "A land use change model: Integrating landscape pattern indexes and Markov-CA," Ecological Modelling, Elsevier, vol. 283(C), pages 1-7.
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    1. repec:bcp:journl:v:9:y:2025:i:10:p:5860-5873 is not listed on IDEAS
    2. Mohammed J. Alshayeb, 2025. "Evaluating Ecosystem Service Trade-Offs and Recovery Dynamics in Response to Urban Expansion: Implications for Sustainable Management Strategies," Sustainability, MDPI, vol. 17(5), pages 1-30, March.

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