2 posts about urban planning by 1 contributor.
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Unlock urban insights by animating foot traffic heatmaps using Python! This guide simulates realistic GPS data around Shibuya Station, Tokyo, and visualizes pedestrian movement over time. Learn to build interactive heatmaps with Folium and Matplotlib, revealing temporal density changes for city planning, retail analysis, and emergency response.
Unlock economic insights in smart cities! This guide teaches you how to calculate the GINI coefficient using Python, a crucial metric for measuring income inequality. Learn to analyze real-world data, like ride-hailing earnings in Austin, and implement ethical considerations for fair urban planning. Detect inequality, trigger alerts, and build equitable cities with this practical, code-driven approach. Start measuring and balancing your city's social fabric today!
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