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The application of geographic information systems (GIS) to armed violent conflicts resolution in the Great Lakes region (GLR) of Central and East Africa.

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2020

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Abstract

Armed violent conflict is a persistent global problem, and its severity is more prominent in developing countries, including Africa. In the past decades and more recently, the GLR in east Africa has experienced various armed violent conflicts, notably the 1994 Rwandan genocide, a protracted civil war in Uganda, the Burundi ethnic conflicts, sporadic persistent cross-border ethnic conflicts in Tanzania and an unending guerrilla and civil war in the Democratic Republic of Congo (DRC). Many efforts have been made through conventional approaches, notably negotiations, peace talks, peacekeeping operations (PKO), and peace stabilization, to address these conflicts but sustainable peace remains a challenge and elusive. Most of these conventional approaches emphasize on economic and political aspects and tend to ignore the spatial component in peace talks and decisions making. GIS has been recognized as an invaluable tool in the resolution of armed violent conflicts in other parts of the world. GIS has the capability of integrating, synthesizing, and modelling spatial data, which can assist in policy and decision-making. However, GIS by itself cannot resolve any conflict, but it is a decision support system that can assist different stakeholders in sustainable peace negotiations. This study aims to explore the application of GIS to armed violent conflicts resolution in the GLR. It is built upon an array of qualitative and quantitative approaches aimed at identifying the origin and evolution of armed violent conflicts; patterns and dynamics of present conflict zones and areas that are currently not experiencing conflicts but may be prone to future armed violent conflicts in GLR in east Africa. In an attempt to trace the origin and evolution of persistent armed violent conflicts in the GLR, and the application of GIS in conflict resolution and peacebuilding, an extensive literature review was conducted. To detect past arm conflict clusters, hotspots, and areas at risk to future outbreaks of armed violent conflicts, GIS spatial analytical techniques were employed, including geocoding, autocorrelation analysis (Moran's I), Hotspot (Getis-Ord Gi*) analysis, and predictive modelling. While geocoding, cluster, and hot spot analyses were performed in ArcMap GIS software to assess the spatial distribution and patterns of armed violent conflicts in the GLR from 1998 – 2017, Microsoft Excel was used to develop a predictive Conflict Risk Model (CRM) for the probability of armed conflicts occurring from 2018 -2038. Thereafter, a conflict risk equation was developed from the CRM to predict areas at risk of future armed conflict outbreak. In response to the absence of a combined spatial data hub in the GLR, a new regional file geodatabase was created in ArcMap, ArcCatalog 10.4 using data from various referenced, survey and institutional sources. As part of a comprehensive plan to bring sustainable peace in the GLR, this study has identified the Hima –Tutsi empire ideology and the presence of mineral resources in the region as significant factors explaining the origin and evolution of persistent armed violence in the GLR. The study also highlights the application of GIS to identify and assess the spatial distribution, clusters, hot and risk spots of armed conflicts in the GLR and as a decision support tool for armed conflict resolution. From 1998-2017, armed violent conflicts were prevalent in the whole country of Burundi, eastern DRC and northern Uganda. During the same period, there was a significant clustering of armed violent conflict in the GLR at 99% confidence (p < 0.01), however eastern DRC emerged as the area with the highest armed conflicts hot spots at 99% confidence. In general, the predictive CRM analysis revealed a 66% probability of armed conflict occurring in the GLR between 2018 and 2038, with DRC predicted to be the most at risk (81%) and Tanzania the least at risk (50%). Together with the newly created regional file geodatabase, these results provide a framework for armed conflict resolution and roadmap for the possibility of sustainable peacebuilding in the GLR. Areas of future research in the GLR include the development of a geodatabase at country level, the socio-economic and environmental impact of armed conflicts in the GLR, and the development of a robust conflict risk model in the GLR and Africa as a continent. Such a robust conflict risk model including local, regional, and international stakeholders, should assist in proactively, rather than reactively identifying and managing armed violent conflicts in region.

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Doctoral Degree. University of KwaZulu-Natal, Durban.

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