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Urbanity: automated modelling and analysis of multidimensional networks in cities

Computer Science

Urbanity: automated modelling and analysis of multidimensional networks in cities

W. Yap, R. Stouffs, et al.

This paper introduces Urbanity, a Python package that revolutionizes urban network construction by integrating open data for enhanced location context. Conducted by Winston Yap, Rudi Stouffs, and Filip Biljecki, the research presents compelling evidence that adding contextual features significantly boosts the accuracy of urban machine-learning models.

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Playback language: English
Abstract
This paper introduces Urbanity, a Python package for automated construction of feature-rich urban networks. It leverages open data to supplement urban networks with location information, enabling more expressive urban machine-learning models. The paper discusses data sources, software features, and presents network data from five global cities. Experiments show that adding contextual features significantly improves the accuracy of classifying different connection types within a network.
Publisher
npj Urban Sustainability
Published On
Jul 25, 2023
Authors
Winston Yap, Rudi Stouffs, Filip Biljecki
Tags
Urbanity
Python package
urban networks
open data
machine learning
contextual features
network data
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