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Land use/land cover (LULC) changes modeling and susceptibility mapping using the binary logistic regression at the territorial level in eastern DR Congo Nteranya, Jean Nacishali; Kiplagat, Andrew; Ucakuwun, Elias K.; Nzabandora , Chantal Kabonyi
Journal of Degraded and Mining Lands Management Vol. 11 No. 4 (2024)
Publisher : Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15243/jdmlm.2024.114.6399

Abstract

The Land Use and Land Cover (LULC) changes are commonly used to determine the landscape conditions and have significant impacts on the earth's surface processes. During the last three decades, there has been an acceleration of LULC changes in Eastern DR Congo. However, there is no comprehensive overview of the drivers of these changes at the territorial level in this region, even though the knowledge of these drivers is important for land use planning and spatial modeling of environmental changes. Using the Kalehe Territory as a case study, this work sought to fill this gap by analyzing the drivers of LULC changes during the 1987-2020 period. A mixed approach combining remote sensing, Geographic Information System, and logistic regression modeling was used. The results indicated that the prominent LULC changes in the study area are deforestation, built-up area expansion, cropland expansion, and shrubland expansion. These changes are significantly influenced by biophysical factors (slope, altitude, and soil type), conservation zoning, population dynamics, and accessibility factors at different levels. The occurrence of conservation zones decreases the susceptibility to deforestation, built-up land, and cropland expansions. In contrast, the proximity factors (distance to road, artisanal mining, and locality) increase the susceptibility to LULC changes. These factors can be integrated into spatial models to forecast LULC changes susceptibility in this region. Furthermore, the establishment of future land use management policy at the territorial level in eastern DR Congo should be space-specific as the susceptibility of LULC changes shows a spatial trend.
Extent and drivers of land productivity degradation at the territorial level in Eastern DR Congo Nteranya, Jean Nacishali; Kiplagat, Andrew; Ucakuwun, Elias K; Nzabandora, Chantal Kabonyi
Journal of Degraded and Mining Lands Management Vol. 12 No. 1 (2024)
Publisher : Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15243/jdmlm.2024.121.6737

Abstract

Land degradation is a global environmental problem that affects the livelihoods of communities. Understanding the extent and causative factors of this phenomenon is important to design the cause-targeted strategies to cope with this problem. This study aimed to assess the effects of biophysical and socio-economic factors on the occurrence of land productivity degradation at the territorial level in Eastern DR Congo, using the Kalehe territory as a case study. The land productivity dynamics were determined based on the trend analysis of Landsat-based NDVI annual composites over the 1987-2020 period. Additionally, a binary logistic regression model was developed to identify the determinant factors and to map the susceptibility of this degradation at the territorial level. The results revealed that 31.25% (1303.175 km2) of the territory had experienced a decrease in land productivity, with 10.8% (453.83 km2) characterized by a significant decrease at the confidence level of 90%, representing the hotspots area of land productivity degradation where conservation actions should be prioritized. This decrease in land productivity is location-specific as it depends on the land cover types and health zones. It is likely to occur at high altitudes, in areas close to artisanal mining sites, rivers, and administrative centers. These results imply that policy interventions to cope with the problem of land productivity degradation should be developed following the heterogeneity of the landscape, and sustainable land management practices that take into account both the biophysical and socio-economic drivers of land degradation should be implemented in this region to achieve the land degradation neutrality by 2030.