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imbukwa1/Pastoralist-Pastoralist-Conflict-Prevention-System-Turkana-County

Domaine:

peace and securityenvironment and energy

Type de record:

project
Créateur:
imb
Hôte:
Pastoralist Conflict Prevention System — Turkana County Overview The Pastoralist Conflict Prevention System is a machine learning–based early warning platform designed to detect environmental conditions that may contribute to resource-driven conflicts among pastoralist communities in Turkana County, Kenya. In arid and semi-arid regions such as Turkana, pastoralist livelihoods depend heavily on access to water and grazing land. During periods of drought or environmental stress, competition over these scarce resources often intensifies, increasing the likelihood of inter-community conflict. This project addresses that challenge by integrating satellite remote sensing data, machine learning techniques, and geospatial visualization tools to detect environmental scarcity hotspots. By analysing long-term patterns in rainfall and vegetation conditions, the system identifies areas where environmental stress may increase the risk of conflict. The results are presented through an interactive dashboard that allows users to visualize high-risk areas spatially. The system is intended to support decision-makers, humanitarian organizations, and peacebuilding institutions by providing early warnings that enable proactive interventions before resource competition escalates into violence. Project Objectives The primary objective of this project is to develop a data-driven system capable of monitoring environmental conditions that influence pastoralist livelihoods in Turkana County. Specifically, the system seeks to identify environmental scarcity hotspots by analysing satellite-derived rainfall and vegetation datasets. Through the use of machine learning techniques, the project aims to detect patterns associated with resource stress and translate them into actionable insights. Another important objective is to provide a visual interface that allows non-technical stakeholders to interpret the model outputs easily. Ultimately, the system contributes to conflict prevention efforts b …

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