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<p>Large estuarine lakes such as Lake Nokoué are increasingly exposed to intense demographic pressure, resulting in persistent environmental disturbances, particularly in areas adjacent to watercourses and wetland systems. This study aims to assess the temporal dynamics of land use around Lake Nokoué, focusing on the Sô-Ava district. The methodological approach combines documentary review, field verification, and remote sensing techniques. Landsat 7 ETM + (2005) and Landsat 8 OLI-TIRS (2022) satellite images both with a spatial resolution of 30&#xa0;m were processed using a supervised classification method based on the Maximum Likelihood algorithm. A 1.5&#xa0;km buffer zone from the centroid of the lake portion in Sô-Ava was used to define the study area. Predictive modeling using the CA–Markov model in the IDRISI Selva environment was applied to project land use changes by 2050. Analysis of land use maps from 2005 and 2022 revealed a sharp decline in forests and marshy savannas from 956.13&#xa0;ha to 453.80&#xa0;ha indicating a net loss of 502.33&#xa0;ha. Meanwhile, water bodies and wooded savannas remained relatively stable. Projections for 2050 indicate a significant expansion of the lake area (from 714.43&#xa0;ha in 2022 to 827.03&#xa0;ha), along with a decline in agricultural lands, especially oil palm fields and fallows, in favor of expanding residential zones.</p>

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Diachronic analysis of land vegetation around the mouth of the Sô River

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年10月7日

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  • Nofodo Innocent Gbaï,
  • Ghislain Comlan Akabassi,
  • Abdoulaye Djafarou,
  • P. Foumilayo Dagou,
  • Clément Adjire

摘要

Large estuarine lakes such as Lake Nokoué are increasingly exposed to intense demographic pressure, resulting in persistent environmental disturbances, particularly in areas adjacent to watercourses and wetland systems. This study aims to assess the temporal dynamics of land use around Lake Nokoué, focusing on the Sô-Ava district. The methodological approach combines documentary review, field verification, and remote sensing techniques. Landsat 7 ETM + (2005) and Landsat 8 OLI-TIRS (2022) satellite images both with a spatial resolution of 30 m were processed using a supervised classification method based on the Maximum Likelihood algorithm. A 1.5 km buffer zone from the centroid of the lake portion in Sô-Ava was used to define the study area. Predictive modeling using the CA–Markov model in the IDRISI Selva environment was applied to project land use changes by 2050. Analysis of land use maps from 2005 and 2022 revealed a sharp decline in forests and marshy savannas from 956.13 ha to 453.80 ha indicating a net loss of 502.33 ha. Meanwhile, water bodies and wooded savannas remained relatively stable. Projections for 2050 indicate a significant expansion of the lake area (from 714.43 ha in 2022 to 827.03 ha), along with a decline in agricultural lands, especially oil palm fields and fallows, in favor of expanding residential zones.