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Remote sensing and GIS-based modelling of land use dynamics and urban flood risk in Lagos megacity for future flood mitigation

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Abstract

This study investigates changes in land use and land cover (LULC) and their impact on flood risk in Lagos Megacity using an integrated geospatial approach. Multi-temporal Landsat TM1984, ETM + 2002, OLI 2023, and Sentinel-2 images were used for LULC classification. Flood depth mapping was conducted using terrain models and hydro-climatic datasets to assess surface inundation dynamics. Rainfall-runoff modelling and flood hydrograph simulations were performed using HEC-HMS 4.12, while Markov Chain Model predicted future LULC dynamics and flood receptors by 2050 within the megacity. Results revealed significant urbanization, with light vegetation (18.87%) and built-up areas (37.68%) expanded between 1984 and 2023. Meanwhile, forests (− 31.55%) and waterbodies (− 11.26%) declined rapidly, reducing the natural flood buffering capacity of Lagos Megacity. Flood impact analysis revealed that 46, 018.18 ha were affected within 12–24 h; 125, 218.43 ha over 5–7 days; and 211, 230.22 ha were severely affected for up to 30 days. By the year 2050, extreme flooding will significantly impact built-up area, totaling 236,810.7 ha (66.20%), while natural flood buffers including forest (1.35%), light vegetation (7.64%), and waterbodies (10.86%) will decline drastically over the predicted year, indicating noticeable environmental changes and high flood vulnerability in the future. The spatial modelling highlighted the need for robust disaster reduction framework, emphasizing the interaction between land use dynamics and hydro-climatic responses in flood-prone areas of Lagos. The study is timely and crucial for informing sustainable land use frameworks and the implementation of future flood mitigations in fast-growing African cities such as Lagos.

Data availability

Raw data were generated at the United States Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center ( [https://earthexplorer.usgs.gov] (https://earthexplorer.usgs.gov) ). Derived data supporting the findings of this study are available from the corresponding author based on request.

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Acknowledgements

The study acknowledges the late Pastor Nathaniel Feso Aniramu for his suggestions and guidance in undertaking this research. Similar appreciation is extended to the Ekiti State Scholarship Board for their fellowship award on the doctoral dissertation, from which the manuscript is carve-out.

Funding

The study was not funded by government or non-governmental organization.

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Authors and Affiliations

  1. Institute of Ecology and Environmental Studies, Obafemi Awolowo University, Ile-Ife, Nigeria

    Opeyemi Aniramu & Olamide Iyanda

  2. Department of Geography, Obafemi Awolowo University, Ile-Ife, Nigeria

    Oluwagbenga Orimoogunje

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  1. Opeyemi Aniramu
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  2. Olamide Iyanda
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Conceptualization, O.A., O.I. and O.O; methodology, O.A., and O.O; software and validation, O.A., O.I. and O.O; formal analysis, O.A.; investigation, O.A., and O.O; manuscript writing, O.A. and O.I.; supervision, O.O.; editing and review, O. A., O. I. and O.O; All authors have read and agreed to the published version of the manuscript.

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Opeyemi Aniramu.

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Aniramu, O., Iyanda, O. & Orimoogunje, O. Remote sensing and GIS-based modelling of land use dynamics and urban flood risk in Lagos megacity for future flood mitigation.
Sci Rep (2026). https://doi.org/10.1038/s41598-026-38544-1

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  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s41598-026-38544-1

Keywords

  • Land use and land cover
  • Urban flood risk
  • Markov chain model
  • Urban growth dynamics
  • Flood mitigation
  • Lagos megacity

Source: Resources - nature.com

Microbial communities and plasmids mediate biodegradation of polycyclic aromatic hydrocarbons (PAHs) in coastal sediments

Riparian vegetation reduces coastal turbidity

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