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<p>Understanding spatiotemporal land-use and vegetation dynamics is vital for sustainable management; however, translating this knowledge into effective planning remains challenging. This study addresses the gap by assessing Land Use and Land Cover (LULC) dynamics in the Belabo-Diang Communal Forest (BDCF) in eastern Cameroon, employing remote sensing and Geographic Information System (GIS) techniques. Landsat images from December 1984, December 2002, and November 2020 were utilised for supervised classification using the maximum likelihood algorithm, resulting in thematic maps of land use/land cover (LULC). Post-classification analysis, conducted at the pixel scale and LULC process insights, assessed forest loss and change trajectories in the BDCF. Results show the BDCF covers 53,213.80 hectares, with seven LULC types: Mature Secondary Forest (MSF), Young Secondary Forest (YSF), Savannah (SA), Cropland and Fallow (CF), Bare Soil (BS), permanently flooded swamp (PFS), and periodically flooded swamp (TFS). MSF declined 37.78% (1984–2002) but increased 36.10% (2002–2020). The annual change per hectare shows that MSF decreased by 319.42&#xa0;ha/year, while SA, CF, and BS increased by 401.12, 351.7, and 1281.4&#xa0;ha/year, respectively, resulting in a loss of 19,625.93&#xa0;ha in forest formations. These findings support BDCF managers in landscape restoration and the Reducing Emissions from Deforestation and Forest Degradation (REDD +) initiative, providing insights for sustainable land management, effective conservation strategies, and mitigating climate impact.</p>

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Spatio-temporal dynamics of land use and land cover types within the Belabo-Diang communal forest in East Cameroon

  • 期刊论文

  • 发表日期：

    2025年4月28日

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  • Guylene Ngoukwa,
  • Jules Christian Zekeng,
  • Bienvenu Léonnel Djoumbi Tchonang,
  • Cédric Djomo Chimi,
  • Louis-Paul-Roger Banoho Kabelong,
  • Amandine Yonkeu Ntonmen,
  • Louis Zapfack

摘要

Understanding spatiotemporal land-use and vegetation dynamics is vital for sustainable management; however, translating this knowledge into effective planning remains challenging. This study addresses the gap by assessing Land Use and Land Cover (LULC) dynamics in the Belabo-Diang Communal Forest (BDCF) in eastern Cameroon, employing remote sensing and Geographic Information System (GIS) techniques. Landsat images from December 1984, December 2002, and November 2020 were utilised for supervised classification using the maximum likelihood algorithm, resulting in thematic maps of land use/land cover (LULC). Post-classification analysis, conducted at the pixel scale and LULC process insights, assessed forest loss and change trajectories in the BDCF. Results show the BDCF covers 53,213.80 hectares, with seven LULC types: Mature Secondary Forest (MSF), Young Secondary Forest (YSF), Savannah (SA), Cropland and Fallow (CF), Bare Soil (BS), permanently flooded swamp (PFS), and periodically flooded swamp (TFS). MSF declined 37.78% (1984–2002) but increased 36.10% (2002–2020). The annual change per hectare shows that MSF decreased by 319.42 ha/year, while SA, CF, and BS increased by 401.12, 351.7, and 1281.4 ha/year, respectively, resulting in a loss of 19,625.93 ha in forest formations. These findings support BDCF managers in landscape restoration and the Reducing Emissions from Deforestation and Forest Degradation (REDD +) initiative, providing insights for sustainable land management, effective conservation strategies, and mitigating climate impact.