Kadergueli/conflict-risk-analysis-chad

# Spatial Analysis of Conflict Risk in Chad using ACLED Data ## Overview This research project analyzes the spatial and temporal distribution of conflict events in Chad using ACLED data. The goal is to identify high-risk regions and understand conflict dynamics over time. ## Research Questions - Which regions in Chad are most affected by conflict? - How do conflict events evolve over time? - Are there identifiable high-risk clusters? ## Dataset - Source: ACLED (Armed Conflict Location & Event Data Project) - Coverage: Chad - Data includes: event type, location, fatalities, actors, dates ## Methodology - Data cleaning and preprocessing - Exploratory Data Analysis (EDA) - Spatial analysis (GeoPandas, maps) - Temporal trend analysis - Basic machine learning clustering ## Tools Used - Python - Pandas - Matplotlib / Seaborn - GeoPandas - Scikit-learn ## Expected Outputs - Conflict risk maps - Temporal trend graphs - Regional risk classification ## Status Work in progress (academic research project) ## Data Source ACLED: ACLED Conflict Events Datas… ## 👤 Author Oumar Mahamat Kadergueli, Student in Computer Science – focus on Data Science & AI