MegaCities - Global Urban Population Visualization Welcome to the MegaCities repository! This project visualizes the most populated cities in the world using geospatial and network-based analysis techniques. By leveraging Python’s powerful libraries, we provide an interactive and insightful visualization of urban population centers, highlighting their interconnectedness via a Minimum Spanning Tree (MST).

MegaCities presents an innovative way to visualize urban population centers and their spatial connections. The core feature of this project is a visualization of the top 100 most populated cities in the world, connected through an MST algorithm. This approach minimizes the distance between cities while ensuring all cities are part of a fully connected network, allowing for better geographical insights into how cities relate to one another.

This project can be used for educational purposes, urban planning, geographical research, and anyone interested in understanding the spatial dynamics of global megacities.

Key Features Global City Mapping: Visualizes the most populated cities around the world using geographic coordinates. Minimum Spanning Tree (MST): Uses MST analysis to minimize the total distance between cities and create an efficient, connected layout. Interactive Visualization: Generates a clear and interactive graph-based visualization of cities and their connections. Scalable Design: Code can be adapted to include more cities or different geographic regions. Customizable: The visualization can be modified for various geospatial data applications. Technologies Used Python: Core programming language for data manipulation and visualization. GeoPandas: Used for handling and plotting geospatial data. NetworkX: To perform graph-based operations and MST calculations. Matplotlib: For high-quality plotting and visualization of cities and their connections. AdjustText: For managing overlapping text labels to ensure clean, readable visualizations. Installation Clone the repository: bash Copy code git clone [https://github.com/radsilent/MegaCities] Install the required dependencies: Navigate into the project directory and install the required Python packages: bash Copy code pip install -r requirements.txt Usage After installation, you can run the visualization script to generate the map of the top cities connected by a minimum spanning tree:

Run the Python script: bash Copy code python megacities_visualization.py The map will be generated and displayed, showing the cities and their interconnections based on the MST algorithm. You can modify the number of cities, change city coordinates, or tweak visualization parameters as per your needs.

Future Enhancements We plan to add more features and data to the MegaCities project, such as:

Interactive maps: Add interactive functionality where users can zoom, hover, and explore cities on the map. Population Density Layers: Incorporate additional data to visualize population densities or trends over time. Transportation Networks: Integrate major transportation hubs and routes to provide more context on city connectivity. Expand to More Cities: Include more global cities or allow for dynamic selection of cities for visualization. Contributing Contributions are welcome! Feel free to submit a pull request or open an issue if you have ideas for new features or improvements.

This project is the intellectual property of Vector Stream Systems LLC and Matthew Collaro. Any usage or distribution of this code should reference the original authors. Contributions are welcome, but all modifications and derivative works should acknowledge the ownership by Vector Stream Systems LLC.