Deep Learning Analysis of Urban Growth Boundaries: An Evaluation of Effectiveness in Mitigating Urban Sprawl in China-Reference-Cited by-同舟云学术

Deep Learning Analysis of Urban Growth Boundaries: An Evaluation of Effectiveness in Mitigating Urban Sprawl in China

Published:2024-03 Issue:1 Volume:150 Page:
ISSN:0733-9488
Container-title:Journal of Urban Planning and Development
language:en
Short-container-title:J. Urban Plann. Dev.

Author:

Liu Yong¹^ORCID,He Lulu²,Wang Jinzhu³^ORCID,Zhang Yihao²,Yang Qiaoran²

Affiliation:

1. School of Management Science and Real Estate, Chongqing Univ., Chongqing 400045, P.R. China (corresponding author). ORCID: .

2. School of Management Science and Real Estate, Chongqing Univ., Chongqing 400045, P.R. China.

3. Centre for Integrative Ecology, School of Life and Environmental Sciences, Deakin Univ., Melbourne, VIC 3125, Australia; Deakin-SWU Joint Research Centre on Big Data, Faculty of Science, Engineering, and Built Environment, Deakin Univ., Melbourne, VIC 3125, Australia. ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Subject

Urban Studies,Development,Geography, Planning and Development,Civil and Structural Engineering

Link

https://ascelibrary.org/doi/pdf/10.1061/JUPDDM.UPENG-4701

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