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<p>Point bars, essential geomorphic elements in meandering rivers, influence sediment dynamics and ecological processes but face escalating threats from climate variability and human activities in the Niger Delta. This study investigates the 50-year evolution (1974–2024) of point bars along the Niger River to assess their spatiotemporal changes and driving mechanisms using remote sensing and machine learning. Using Landsat and Sentinel-2 satellite imagery, digital elevation models (DEMs), and rainfall data, we applied Object-Based Image Analysis (OBIA) and Support Vector Machines (SVMs) for automated classification and mapping of river features. Temporal trends were evaluated through decadal statistical metrics, spatial autocorrelation (Moran’s Index), and correlation analyses between point bar morphology, rainfall, and elevation. Results reveal a fluctuating Niger River area, declining from 46,376.54&#xa0;km² (1974) to 44,796.47&#xa0;km² (2024), with intermittent expansion (49,601.2&#xa0;km² in 2014). Point bar area surged from 1,945.63&#xa0;km² (1974) to 8,087.89&#xa0;km² (2024), peaking at 7,026.33&#xa0;km² (2004) before contraction, linked to sediment supply shifts. Morphological analysis highlighted elongated bars (aspect ratio 54.22) indicating lateral accretion, contrasting with rounded forms (ratio ~ 20.8) in depositional zones. Spatial autocorrelation confirmed clustering with elevation (Moran’s Index = 1.06, <i>p</i> &lt; 0.001), while rainfall exhibited a dominant correlation (R² = 0.9921) with bar dynamics. These patterns mirror global systems like the Mississippi and Amazon, underscoring synergistic climatic and anthropogenic impacts. The study provides a framework for adaptive management of the Niger Delta and analogous fluvial environments, emphasizing the critical role of hydrological and sedimentological monitoring.</p>

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Assessing the evolution of point bars along the Niger river in the Niger Delta, Nigeria (1974–2024) using remote sensing and machine learning

  • 期刊论文

  • 发表日期：

    2026年1月20日

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  • Paaru Moses,
  • Emmanuel Martin Nwachukwu,
  • Omabuwa O. Mene-Ejegi,
  • Okechukwu Okpobiri,
  • Desmond Rowland Eteh

摘要

Point bars, essential geomorphic elements in meandering rivers, influence sediment dynamics and ecological processes but face escalating threats from climate variability and human activities in the Niger Delta. This study investigates the 50-year evolution (1974–2024) of point bars along the Niger River to assess their spatiotemporal changes and driving mechanisms using remote sensing and machine learning. Using Landsat and Sentinel-2 satellite imagery, digital elevation models (DEMs), and rainfall data, we applied Object-Based Image Analysis (OBIA) and Support Vector Machines (SVMs) for automated classification and mapping of river features. Temporal trends were evaluated through decadal statistical metrics, spatial autocorrelation (Moran’s Index), and correlation analyses between point bar morphology, rainfall, and elevation. Results reveal a fluctuating Niger River area, declining from 46,376.54 km² (1974) to 44,796.47 km² (2024), with intermittent expansion (49,601.2 km² in 2014). Point bar area surged from 1,945.63 km² (1974) to 8,087.89 km² (2024), peaking at 7,026.33 km² (2004) before contraction, linked to sediment supply shifts. Morphological analysis highlighted elongated bars (aspect ratio 54.22) indicating lateral accretion, contrasting with rounded forms (ratio ~ 20.8) in depositional zones. Spatial autocorrelation confirmed clustering with elevation (Moran’s Index = 1.06, p < 0.001), while rainfall exhibited a dominant correlation (R² = 0.9921) with bar dynamics. These patterns mirror global systems like the Mississippi and Amazon, underscoring synergistic climatic and anthropogenic impacts. The study provides a framework for adaptive management of the Niger Delta and analogous fluvial environments, emphasizing the critical role of hydrological and sedimentological monitoring.