Applying machine learning to decode built environment thresholds for public and active transport distances in the global south

Applying machine learning to decode built environment thresholds for public and active transport distances in the global south

Urban mobility in rapidly growing megacities, particularly in the Global South, presents unique challenges due to population densities, fragmented transit networks, and informal urban growth. While extensive research has examined how the built environment (BE) influences transport mode choice, the i...

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Bibliographic Details
Main Authors: Ali Shkera, Domokos Esztergár-Kiss
Format: Article
Language:English
Published: Elsevier 2025-12-01
Series:Journal of Urban Mobility
Subjects:
Global south
Non-linear relationships
Machine learning
Built environment
Urban mobility
Online Access:http://www.sciencedirect.com/science/article/pii/S2667091725000457
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