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Hierarchical Analysis of Miombo Woodland Spatial Dynamics in Lualaba Province (DR Congo), 1990-2024: Integrating Remote Sensing and Landscape Ecology Techniques
Useni Sikuzani, Y.; Mpanda Mukenza, M.; Kikuni Tchowa, J.; Kabamb Kanyimb, D.; Malaisse, F.; Bogaert, J. Hierarchical Analysis of Miombo Woodland Spatial Dynamics in Lualaba Province (DR Congo), 1990-2024: Integrating Remote Sensing and Landscape Ecology Techniques. Preprints2024, 2024090072. https://doi.org/10.20944/preprints202409.0072.v1
APA Style
Useni Sikuzani, Y., Mpanda Mukenza, M., Kikuni Tchowa, J., Kabamb Kanyimb, D., Malaisse, F., & Bogaert, J. (2024). Hierarchical Analysis of Miombo Woodland Spatial Dynamics in Lualaba Province (DR Congo), 1990-2024: Integrating Remote Sensing and Landscape Ecology Techniques. Preprints. https://doi.org/10.20944/preprints202409.0072.v1
Chicago/Turabian Style
Useni Sikuzani, Y., François Malaisse and Jan Bogaert. 2024 "Hierarchical Analysis of Miombo Woodland Spatial Dynamics in Lualaba Province (DR Congo), 1990-2024: Integrating Remote Sensing and Landscape Ecology Techniques" Preprints. https://doi.org/10.20944/preprints202409.0072.v1
Abstract
Lualaba Province, located in the southeastern Democratic Republic of the Congo, consists of five territories with varied dominant land uses: agriculture (Dilolo, Kapanga, and Musumba in the west) and mining (Mutshatsha and Lubudi in the east). The province also includes protected areas with significant governance challenges. The unique miombo woodlands of Lualaba are threatened by deforestation, posing risks to biodiversity and local livelihoods that depend on these woodlands for agriculture and forestry. To quantify the spatio-temporal dynamics of Lualaba's landscape, we utilized Landsat images from 1990 to 2024, supported by a Random Forest Classifier. Landscape metrics were calculated at multiple hierarchical levels: province, territory, and protected areas. Our provincial-level analysis revealed a pronounced deforestation trend, with miombo woodland cover declining from 62,90 % to less than 25 % over the 34-year period. This trend was characterized by the fragmentation and dissection of woodland patches and a decline in remaining woodland fragments, due to their ongoing replacement by savannas, agriculture, and urbanization. The average distance between miombo woodland patches increased significantly, indicating heightened fragmentation and spatial isolation. Agricultural areas such as Sandoa and Kapanga were particularly vulnerable to deforestation. On the other hand, the miombo forest cover in the mining areas is still representative, with over 30% of the landscape covered. Notably, the reduction in woodland cover within protected areas was substantial, with significant losses observed across both agricultural and mining territories. The loss of miombo woodland cover in Lualaba and its territories was accompanied by an increase in landscape patch diversity, as indicated by the Shannon diversity index, suggesting a shift to more heterogeneous landscapes. These findings underscore a complex deforestation pattern, highlighting the intense local impact on miombo woodland cover loss. Urgent action is needed to implement land conservation policies, promote sustainable agricultural practices, strengthen miombo woodland regulation enforcement, and actively support protected areas. Involvement from both local and international stakeholders is imperative to preserve the ecological richness and functionality of Lualaba Province's miombo woodland ecosystems.
Copyright:
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