Urban Inequality in Vadodara

A Spatial Analysis of Opportunity, Risk, and Accessibility

This project presents a thesis-grade spatial analysis of urban inequality in Vadodara, India. It combines accessibility modelling, flood exposure, public transport networks, and spatial statistics to construct and analyze a Urban Opportunity Index (UOI) at the ward level.

The repository is designed for:

• 📊 Academic research & thesis evaluation
• 🗺️ Policy analysis & planning support
• 🌐 Public-facing interactive exploration

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📌 Key Contributions

• Urban Opportunity Index (UOI) Composite index capturing access to:

  • Healthcare
  • Education
  • Road & highway connectivity
  • Public bus transit (integrated from Smart City Bus data)

• Flood & Environmental Risk Assessment

• Spatial Inequality Metrics

  • Gini coefficient
  • Lorenz curve
  • Kolm–Pollak EDE (inequality-adjusted opportunity)

• Spatial Autocorrelation

  • Global Moran’s I
  • LISA cluster maps

• Interactive & Presentation-Ready Maps

  • Satellite + physical basemaps
  • Road network overlays
  • Bus stop networks
  • Toggleable analytical layers

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🗂 Repository Structure

URBAN-INEQUALITY-IN-BARODA/
│
├── data/
│   ├── raw/                # Raw inputs (OSM, bus stops JSON)
│   ├── interim/            # Cleaned spatial layers
│   └── processed/          # Final analytical datasets (GPKG / CSV)
│
├── scripts/
│   └── Python/
│       ├── 03_accessibility_engine.py
│       ├── 03b_transit_accessibility.py
│       ├── 04_risk_assessment.py
│       ├── 05_calculate_uoi.py
│       ├── 06_dashboard_generator.py
│       ├── 07_*_presentation_maps.py
│       ├── 08_*_network_maps.py
│       └── 09_interactive_road_bus_network.py
│
├── results/
│   ├── thesis_figures_clean/        # Publication-ready figures
│   ├── interactive_network_maps/    # Interactive HTML maps
│   ├── interactive_physical_maps/
│   └── reports & CSV outputs
│
├── docs/
│   ├── maps/               # GitHub Pages assets
│   └── images/
│
└── README.md

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🧠 Methodology Overview

1️⃣ Accessibility Modelling

• Road-network based travel times using OSMnx

• Separate treatment for:

  • Hospitals (drive)
  • Schools (walk)
  • Bus stops (walk)
  • Highway access (network proximity)

2️⃣ Transit Integration (NEW)

• Bus stop & route data from:

  • Open Vadodara – Smart City Bus

• Metrics derived:

  • Stop density
  • Route coverage
  • Ward-level transit accessibility

3️⃣ Risk & Exposure

• Flood exposure (% ward area)
• Building density (proxy for exposure intensity)

4️⃣ Urban Opportunity Index (UOI)

• Normalized components
• Balanced weighting
• Final scale: 0–100 (higher = better)

5️⃣ Inequality & Spatial Analysis

• Gini & Lorenz
• Kolm–Pollak EDE (κ sensitivity)
• Moran’s I & LISA clustering

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🗺️ Maps & Visual Outputs

Static (Thesis / PDF)

• UOI choropleth
• Flood exposure map
• LISA cluster map
• Ward typology (Opportunity × Risk)

Interactive (HTML)

• Satellite & physical basemaps
• Road network overlay
• Bus stops & transit layers
• Hover tooltips with all indicators
• Layer toggles for presentations

👉 Located in: results/interactive_network_maps/

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🚀 How to Run (Quick Start)

# Create environment
python -m venv venv
source venv/bin/activate

# Install core dependencies
pip install geopandas osmnx folium libpysal esda splot shapely pandas numpy matplotlib

Run scripts in order:

03_accessibility_engine.py
03b_transit_accessibility.py
04_risk_assessment.py
05_calculate_uoi.py
07_*_presentation_maps.py
09_interactive_road_bus_network.py

and others in order

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🎓 Intended Use

• Thesis defense & academic review
• Urban policy & planning insights
• Public visualization & storytelling
• Template for other Indian cities

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⚠️ Notes & Design Choices

• Wards are synthetic analytical units
• Transit data is real but simplified
• Interactive maps prioritized over heavy 3D tools for stability
• Kepler.gl intentionally excluded due to build constraints on Arch Linux

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📬 Acknowledgements

• OpenStreetMap contributors
• Open Vadodara – Smart City Bus initiative
• Urban spatial analysis literature (Moran, Kolm–Pollak, etc.)

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✨ Next Extensions (Optional)

• Time-of-day accessibility
• Scenario simulations (new bus routes)
• Policy-driven optimization

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🔗 Related & Inspiring Repositories

The following repositories influenced tools, data handling, or visual design choices used in this work:

1. Map Posters & Visual Design 🎨 https://github.com/originalankur/maptoposter High-quality cartographic posters and map aesthetics.

2. JSON Processing Utilities 🧩 https://github.com/jhsu98/json-splitter Helpful for handling large and nested JSON datasets.

3. Open Vadodara Ecosystem 🌆 https://github.com/open-vadodara Community-driven open data and civic tech projects for Vadodara, including transit-related datasets.