Urban Mobility Index
Spring 2022
Exploring Urban Data with Machine Learning
Columbia GSAPP
By Kit Nga Chou, Kirthi Balakrishnan, Lizzie Lee, Michelle Chen
︎Interactive Site
Exploring Urban Data with Machine Learning
Columbia GSAPP
By Kit Nga Chou, Kirthi Balakrishnan, Lizzie Lee, Michelle Chen
︎Interactive Site
Project Scope:
Addressing the critical issue of urban mobility, the prevalent reliance on vehicular transportation underscores the need for improving walkability or multi-modal commute options. A valuable tool for urban planners is to be able to assess a neighborhood’s walkability score by examining its street characteristics.
Exploring the potential, our team leveraged Walkscore.com's extensive datasets of major cities to construct a training model. This model seeks to predict the efficiency of any city or neighborhood based on their street connectivity and transit density, offering a comprehensive analytical approach for urban planning.
