Comparative analysis of urban structures in three American Rust Belt cities

Jinmo Rhee

Environment and Planning B, 2025, vol. 52, issue 9, 2066-2083

Abstract: This research presents a computational method to investigate the common urban structure of three Rust Belt cities—Cleveland, Detroit, and Pittsburgh—that share similar urban cultures. Understanding the urban structure of these cities is crucial for addressing their necessary restructuring and downsizing. However, there has been insufficient investigation of common spatial characteristics through comparative analysis of these cities. This research goes beyond conventional urban form analysis methods by employing a data scientific approach that segments cities into distinct parts and extracts spatial metrics from these segments. The approach involves the creation of a novel type of urban form data and utilizes deep neural networks for clustering to identify spatial characteristics common to the three cities, thereby deriving a shared urban structure. It reveals unseen insights into the restructuring of city spaces, offering a critical foundation for future urban development, and benefiting urban planners and researchers.

Keywords: Urban structure; urban morphology; deep learning; form classification; form data (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:sae:envirb:v:52:y:2025:i:9:p:2066-2083

DOI: 10.1177/23998083251324982

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