I am excited to share my latest project, developed as part of the Microsoft Fabric Data Days Notebooks Contest.
As urbanisation accelerates, a critical question arises: Does high population density doom a city to low livability? In this project, I explored the "Density Myth" and uncovered actionable insights to guide urban planning and sustainability efforts.
Key Highlights:
- Objective: Decode the drivers of urban sustainability and challenge common misconceptions.
- Dataset: 3,400+ cities with features like green cover, renewable energy usage, and urban density.
- Tech Stack: Python (pandas, scikit-learn, seaborn), Microsoft Fabric Notebooks.
Key Findings:
1. Density is Not Destiny: Population density has minimal impact on sustainability.
2. The Green Imperative: Green cover percentage is the most critical predictor of urban livability (~47% importance).
3. City Archetypes: Using K-Means clustering, cities were grouped into actionable clusters:
- Cluster 0: High disaster risk, low sustainability.
- Cluster 1: Moderate sustainability, low green cover.
- Cluster 2: High sustainability, leveraging green spaces and renewable energy.
Recommendations:
- Increase Green Cover: Urban forestry, green roofs, and parks.
- Promote Renewable Energy: Subsidies for solar and wind energy projects.
- Improve Public Transport: Expand transit systems to reduce carbon emissions.
This project showcases the transformative power of data-driven urban planning in creating greener, safer, and more sustainable cities.
GitHub Repository: https://github.com/pythonist4444/cities-of-tomorrow
I would love to hear your thoughts. Let’s connect and discuss how data science can shape the future of urban sustainability.
https%3A%2F%2Fgithub.com%2Fpythonist4444%2Fcities-of-tomorrow
