Large-Scale and Refined Green Space Identification-Based Sustainable Urban Renewal Mode Assessment

Large-Scale and Refined Green Space Identification-Based Sustainable Urban Renewal Mode Assessment

Urban sustainable renewal has received extensive attention in a wide range of fields, including urban planning, urban management, energy management, and transportation. Given that environmental resource conservation is critical to urban sustainability renewal, this study highlighted the imbalance am...

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Main Authors: Rong Guo, Xiaoya Song, Peiran Li, Guangming Wu, Zhiling Guo
Format: Article
Language:English
Published: Hindawi Limited 2020-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2020/2043019
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spelling doaj-604af0ef5a4542d0bb7b7ff4169cc7172020-11-25T01:59:27ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472020-01-01202010.1155/2020/20430192043019Large-Scale and Refined Green Space Identification-Based Sustainable Urban Renewal Mode AssessmentRong Guo0Xiaoya Song1Peiran Li2Guangming Wu3Zhiling Guo4Key Laboratory of Cold Region Urban and Rural Human Settlement Environment Science and Technology, Ministry of Industry and Information Technology, School of Architecture, Harbin Institute of Technology, Harbin 150006, ChinaKey Laboratory of Cold Region Urban and Rural Human Settlement Environment Science and Technology, Ministry of Industry and Information Technology, School of Architecture, Harbin Institute of Technology, Harbin 150006, ChinaCenter for Spatial Information Science, The University of Tokyo, Kashiwa 277-8568, JapanCenter for Spatial Information Science, The University of Tokyo, Kashiwa 277-8568, JapanCenter for Spatial Information Science, The University of Tokyo, Kashiwa 277-8568, JapanUrban sustainable renewal has received extensive attention in a wide range of fields, including urban planning, urban management, energy management, and transportation. Given that environmental resource conservation is critical to urban sustainability renewal, this study highlighted the imbalance among green space, urban development, and transportation accessibility. Here, a novel node-place-green model is presented to measure sustainable urban development; meanwhile, deep learning is utilized to identify and extract the green space to measure the environmental index. Based on the generated node, place, and green value, urban developing status could be classified into nine modes for further analysis of transportation, urban function, and ecological construction. The experimental results of Harbin reveal the feasibility of the proposed method in providing specific guidelines for urban planning and policies on sustainable development.http://dx.doi.org/10.1155/2020/2043019
collection DOAJ
language English
format Article
sources DOAJ
author Rong Guo
Xiaoya Song
Peiran Li
Guangming Wu
Zhiling Guo
spellingShingle Rong Guo
Xiaoya Song
Peiran Li
Guangming Wu
Zhiling Guo
Large-Scale and Refined Green Space Identification-Based Sustainable Urban Renewal Mode Assessment
Mathematical Problems in Engineering
author_facet Rong Guo
Xiaoya Song
Peiran Li
Guangming Wu
Zhiling Guo
author_sort Rong Guo
title Large-Scale and Refined Green Space Identification-Based Sustainable Urban Renewal Mode Assessment
title_short Large-Scale and Refined Green Space Identification-Based Sustainable Urban Renewal Mode Assessment
title_full Large-Scale and Refined Green Space Identification-Based Sustainable Urban Renewal Mode Assessment
title_fullStr Large-Scale and Refined Green Space Identification-Based Sustainable Urban Renewal Mode Assessment
title_full_unstemmed Large-Scale and Refined Green Space Identification-Based Sustainable Urban Renewal Mode Assessment
title_sort large-scale and refined green space identification-based sustainable urban renewal mode assessment
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2020-01-01
description Urban sustainable renewal has received extensive attention in a wide range of fields, including urban planning, urban management, energy management, and transportation. Given that environmental resource conservation is critical to urban sustainability renewal, this study highlighted the imbalance among green space, urban development, and transportation accessibility. Here, a novel node-place-green model is presented to measure sustainable urban development; meanwhile, deep learning is utilized to identify and extract the green space to measure the environmental index. Based on the generated node, place, and green value, urban developing status could be classified into nine modes for further analysis of transportation, urban function, and ecological construction. The experimental results of Harbin reveal the feasibility of the proposed method in providing specific guidelines for urban planning and policies on sustainable development.
url http://dx.doi.org/10.1155/2020/2043019
work_keys_str_mv AT rongguo largescaleandrefinedgreenspaceidentificationbasedsustainableurbanrenewalmodeassessment
AT xiaoyasong largescaleandrefinedgreenspaceidentificationbasedsustainableurbanrenewalmodeassessment
AT peiranli largescaleandrefinedgreenspaceidentificationbasedsustainableurbanrenewalmodeassessment
AT guangmingwu largescaleandrefinedgreenspaceidentificationbasedsustainableurbanrenewalmodeassessment
AT zhilingguo largescaleandrefinedgreenspaceidentificationbasedsustainableurbanrenewalmodeassessment
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