NYC Sidewalk Time Machine

Overview

NYC Sidewalk Time Machine is an interactive visualization tool built for CS-GY 9223 (Visualization for Machine Learning) that explores 20 years of Manhattan pedestrian infrastructure data. The project started as a simple single-region visualization and grew into a more comprehensive system with multi-tile selection capabilities.

Key Features

• Multi-Tile Selection: Select and analyze multiple geographic regions at once
• Coordinate Transformation: Convert between different geospatial coordinate systems
• Dark Mode: Clean dark theme for better viewing
• Historical Analysis: Explore 20 years of pedestrian infrastructure changes across Manhattan

Technical Implementation

Built with:

• Frontend: React for the UI
• Visualization: D3.js for interactive, data-driven graphics
• Geospatial Processing: tile2net for handling geospatial data transformations
• Data Pipeline: Custom pipeline for processing historical infrastructure data

Impact

This tool gives urban planners, researchers, and anyone interested in NYC an easy way to see how Manhattan’s pedestrian infrastructure has changed over the past two decades.

Links

• Live Demo: https://shyamksateesh.github.io/pedestrian-viz/
• GitHub Repository: https://github.com/shyamksateesh/pedestrian-viz

Technologies Used

React • D3.js • tile2net • Geospatial Data Processing • JavaScript • HTML/CSS