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作者

César A. Hidalgo;Elisa Castañer;Andres Sevtsuk

来源

HABITAT INTERNATIONAL,Vol.106,P.102205

语言

英文

关键字

作者单位

ANITI Chair, University of Toulouse, France;Alliance Manchester Business School, University of Manchester, UK;School of Engineering and Applied Sciences, Harvard University, USA;Collective Learning Group, The MIT Media Lab, USA;Department of Urban Studies and Planning, Massachusetts Institute of Technology, USA;ANITI Chair, University of Toulouse, France;Alliance Manchester Business School, University of Manchester, UK;School of Engineering and Applied Sciences, Harvard University, USA;Collective Learning Group, The MIT Media Lab, USA;Department of Urban Studies and Planning, Massachusetts Institute of Technology, USA

摘要

Advances in computational urbanism have stimulated the rise of generative and parametric approaches to urban design. Yet, most generative and parametric approaches focus on physical characteristics, such as a neighborhoods walkability, energy efficiency, and urban form. Here, we study the colocation patterns of more than one million amenities in 47 U.S. cities to model the amenity mix of neighborhoods, and to identify the amenities that are over- or under-supplied in a neighborhood. We build this model by combining a clustering algorithm, designed to identify amenity-dense neighborhoods, and a network, connecting amenities that are likely to collocate. Our findings extend generative and parametric urban design approaches to the amenity mix of neighborhoods, by leveraging the idea of relatedness from the economic geography literature, to evaluate and optimize a neighborhood's amenity mix.