GIS analysis of Quickmart supermarket coverage and population density in Nairobi, Kenya
# 🗺️ Nairobi Quickmart Coverage Analysis
> **GIS project identifying underserved high-density zones in Nairobi for strategic Quickmart supermarket expansion.**
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## 📌 Project Overview
This geospatial analysis examines the spatial distribution of Quickmart supermarkets across Nairobi County relative to population density. By overlaying 1 km walkability buffers against high-density residential zones, the project highlights coverage gaps — areas with large populations but no nearby Quickmart store — to support data-driven retail expansion decisions.
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## 🗂️ Repository Structure
```
Nairobi_Quickmart_Coverage/
│
├── workflow/
│ ├── population_density.jpeg # Population density raster
│ ├── Quickmat_distribution.jpeg # Geocoded store locations
│ └── Catchment_areas.jpeg # 1 km catchment buffers
│
├── Quickmart map.jpeg # Final composite map
└── README.md
```
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## 🔢 Data Sources
| Dataset | Source |
|---|---|
| Quickmart store locations | Geocoding |
| Population density | Worldpop |
| Nairobi administrative boundary | HDX |
| Basemap | OpenStreetMap Standard |
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## ⚙️ Methodology
### Step 1 — Population Density
Population density data for Nairobi County was acquired and visualised as a raster layer, providing a spatial baseline of where residents are concentrated.
*Figure 1: Population density raster for Nairobi County*
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### Step 2 — Store Distribution
All Quickmart branch locations in Nairobi were geocoded and imported as a point layer in QGIS.
*Figure 2: Geocoded Quickmart store locations across Nairobi*
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### Step 3 — 1 km Catchment Buffers
A 1 km Euclidean buffer was generated around each store, representing an approximate walking-distance catchment area for each branch.
*Figure 3: 1 km walking-distance catchment buffers*
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### Step 4 — Overlay Analysis/Final map
The population density raster, store point layer, and catchment buffers were overlaid to identify:
- Areas **within** catchment c …