Geovisualization and Spatial Modelling of Armed Conflicts in the Great Lake Region of Central and East Africa

This paper explores a regional GIS-based approach to identifying, assessing, and geovisualizing the spatial distribution and patterns of armed conflicts in the Great Lakes Region (GLR) of Central and East Africa from 1998 to 2017. Geospatial analytical techniques, including geocoding, Average Nearest Neighbor (ANN) analysis, and hot spot analysis (Getis-Ord Gi*), were used to identify, map, and visualize conflict patterns, clusters, and hot spots, while kernel density estimation (KDE) analyzed conflict densities per square kilometre. The results reveal that armed conflict in the GLR was significantly clustered from 1998 to 2017, with a 99% confidence level (p < 0.01). The eastern Democratic Republic of the Congo (DRC), bordering Burundi, Rwanda, and Uganda, emerged as the most intense conflict hot spot at a 99% confidence level. These findings align with the KDE results, which also identified pockets of high conflict densities along these borders. The study further highlights the significant role of mineral resources in armed conflicts in the GLR. A chi-square test result (p < 0.005) indicates a statistically significant relationship between rebel locations and mineral resource distribution. Unlike previous geospatial studies that presented fragmented, country-specific analyses of armed conflicts in the GLR, this study adopts a holistic approach by mapping regional conflict hot spots, risk areas, densities, and related factors. This proposed methodology can assist peace-building initiatives, policymakers and stakeholders in better visualizing the spatial distribution of conflict variables, understanding their underlying causes, and developing effective strategies for mitigating and preventing further armed conflicts in the region and beyond.