Assessing the Driving Factors of Deforestation and Afforestation over three Decades (1990-2020) in Ngororero District, Rwanda
DOI:
https://doi.org/10.53819/81018102t2467Abstract
Deforestation is a critical environmental issue that has far-reaching impacts on biodiversity, ecosystems, and climate change. Monitoring deforestation and Afforestation processes over time is essential for understanding their drivers, patterns, and consequences, as well as informing sustainable land management strategies. This study aims to assess the driving factors of deforestation and afforestation over three decades (1990-2020) in Ngororero District, Rwanda, between 1990 and 2020, using a combination of remote sensing and geographic information system (GIS) techniques. The results indicated approximately 274.4 km2 (40.45%) of Ngororero District remained unchanged over three decades. Moreover, the findings showed that the district experienced significant deforestation, converting 43.29% of its land to cropland and 8.96% of forested areas to grasslands. This led to a loss of 53.33% of the total land use transformations. Despite this, efforts towards afforestation and reforestation were modest, with only 0.53% of total land use conversions. The study contributed to a deeper understanding of the dynamics of forest cover change in Ngororero District and provide valuable insights for policymakers, land managers, and conservation efforts in Rwanda. The findings inform sustainable land-use planning, forest management strategies, and environmental conservation initiatives aimed at mitigating deforestation and promoting afforestation in the area. By leveraging the capabilities of remote sensing and GIS technologies, this research offers a comprehensive spatiotemporal analysis of deforestation and afforestation patterns, enabling evidence-based decision-making and supporting the sustainable management of forest resources in Ngororero District and potentially other regions of Rwanda.
Keywords: Afforestation, Deforestation, Forest Cover Change, GIS, Remote Sensing
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