lewis1024-debug/Kaduana-State-IRT-REPORT-security-Hotspot-analysis
GitHub: lewis1024-debug/Kaduana-State-IRT-REPORT-security-Hotspot-analysis
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# Kaduana-State-IRT-REPORT-security-Hotspot-analysis
# Kaduna State IRT Security Hotspot Analysis
**Project:** Spatial analysis of kidnapping incidents and security response mapping for Kaduna State, Nigeria
**Data Source:** IRT 2024 Incident Records
**Objective:** Visualize threat concentration, assess IRT operational impact, and support data-driven deployment decisions.
## **1. Project Overview**
The Intelligence Response Team (IRT) is a specialized tactical unit of the Nigeria Police Force deployed to combat banditry, kidnapping-for-ransom, and terrorism in Kaduna State. This project translates IRT 2024 incident data into actionable spatial intelligence.
**Key outputs:**
1. `Kaduna_Hotspots_2024` — Kernel density heatmap of kidnapping incidents by LGA
2. `Kaduna_Major_Roads` — Filtered highway network showing ambush corridors
3. Integrated threat map for identifying high-risk LGAs: Birnin Gwari, Igabi, Chikun, Kaduna North, Kaduna South
This analysis supports the findings in: *Report: Impact of the Intelligence Response Team (IRT) on Security Issues in Kaduna State*
## **2. Tools & Dependencies**
| **Tool** | **Version** | **Purpose** |
| --- | --- | --- |
| QGIS | 3.34+ LTR | Core GIS, spatial analysis, map layout |
| QuickOSM Plugin | 2.2+ | Download OSM road/administrative data |
| LibreOffice Calc / Excel | Any | Data cleaning, CSV prep |
| OpenStreetMap | Live API | Highway network data |
| Natural Earth / GADM | v4.1 | LGA administrative boundaries |
## **3. Data Sources**
1. **IRT 2024 Incident Records** — CSV with fields: `incident_id`, `date`, `lga`, `latitude`, `longitude`, `incident_type`, `victims_rescued`
2. **Kaduna LGA Boundaries** — Shapefile from GADM Nigeria Level 2 Admin
3. **OSM Highway Data** — `highway=trunk, primary, secondary, tertiary` via Overpass API
## **4. Workflow: Reproducing the IRT Map**
### **Step 1: Data Preparation**
1. Clean IRT CSV: Remove duplicates, validate lat/long, standardize LGA names
2. Import to QGIS: `Layer > Add Layer > Add Delimited Text Layer` → Set Geometry CRS to `EPSG:4326`
### **Step 2: Generate Incident Heatmap**
1. `Processing Toolbox > Heatmap (Kernel Density Estimation)`
2. **Input**: IRT points layer
3. **Radius**: `15000` meters — reflects rural mobility patterns
4. **Pixel size**: `300` meters
5. **Output**: `Kaduna_Hotspots_2024.tif`
6. **Symbology**: Singleband pseudocolor, `Inferno` ramp, 70% opacity