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Dynamics of Hierarchical Urban Green Space Patches and Implications for Management Policy

Accurately quantifying the variation of urban green space is the prerequisite for fully understanding its ecosystem services. However, knowledge about the spatiotemporal dynamics of urban green space is still insufficient due to multiple challenges that remain in mapping green spaces within heteroge...

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Autores principales: Yu, Zhoulu, Wang, Yaohui, Deng, Jinsong, Shen, Zhangquan, Wang, Ke, Zhu, Jinxia, Gan, Muye
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5492285/
https://www.ncbi.nlm.nih.gov/pubmed/28587309
http://dx.doi.org/10.3390/s17061304
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author Yu, Zhoulu
Wang, Yaohui
Deng, Jinsong
Shen, Zhangquan
Wang, Ke
Zhu, Jinxia
Gan, Muye
author_facet Yu, Zhoulu
Wang, Yaohui
Deng, Jinsong
Shen, Zhangquan
Wang, Ke
Zhu, Jinxia
Gan, Muye
author_sort Yu, Zhoulu
collection PubMed
description Accurately quantifying the variation of urban green space is the prerequisite for fully understanding its ecosystem services. However, knowledge about the spatiotemporal dynamics of urban green space is still insufficient due to multiple challenges that remain in mapping green spaces within heterogeneous urban environments. This paper uses the city of Hangzhou to demonstrate an analysis methodology that integrates sub-pixel mapping technology and landscape analysis to fully investigate the spatiotemporal pattern and variation of hierarchical urban green space patches. Firstly, multiple endmember spectral mixture analysis was applied to time series Landsat data to derive green space coverage at the sub-pixel level. Landscape metric analysis was then employed to characterize the variation pattern of urban green space patches. Results indicate that Hangzhou has experienced a significant loss of urban greenness, producing a more fragmented and isolated vegetation landscape. Additionally, a remarkable amelioration of urban greenness occurred in the city core from 2002 to 2013, characterized by the significant increase of small-sized green space patches. The green space network has been formed as a consequence of new urban greening strategies in Hangzhou. These strategies have greatly fragmented the built-up areas and enriched the diversity of the urban landscape. Gradient analysis further revealed a distinct pattern of urban green space landscape variation in the process of urbanization. By integrating both sub-pixel mapping technology and landscape analysis, our approach revealed the subtle variation of urban green space patches which are otherwise easy to overlook. Findings from this study will help us to refine our understanding of the evolution of heterogeneous urban environments.
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spelling pubmed-54922852017-07-03 Dynamics of Hierarchical Urban Green Space Patches and Implications for Management Policy Yu, Zhoulu Wang, Yaohui Deng, Jinsong Shen, Zhangquan Wang, Ke Zhu, Jinxia Gan, Muye Sensors (Basel) Article Accurately quantifying the variation of urban green space is the prerequisite for fully understanding its ecosystem services. However, knowledge about the spatiotemporal dynamics of urban green space is still insufficient due to multiple challenges that remain in mapping green spaces within heterogeneous urban environments. This paper uses the city of Hangzhou to demonstrate an analysis methodology that integrates sub-pixel mapping technology and landscape analysis to fully investigate the spatiotemporal pattern and variation of hierarchical urban green space patches. Firstly, multiple endmember spectral mixture analysis was applied to time series Landsat data to derive green space coverage at the sub-pixel level. Landscape metric analysis was then employed to characterize the variation pattern of urban green space patches. Results indicate that Hangzhou has experienced a significant loss of urban greenness, producing a more fragmented and isolated vegetation landscape. Additionally, a remarkable amelioration of urban greenness occurred in the city core from 2002 to 2013, characterized by the significant increase of small-sized green space patches. The green space network has been formed as a consequence of new urban greening strategies in Hangzhou. These strategies have greatly fragmented the built-up areas and enriched the diversity of the urban landscape. Gradient analysis further revealed a distinct pattern of urban green space landscape variation in the process of urbanization. By integrating both sub-pixel mapping technology and landscape analysis, our approach revealed the subtle variation of urban green space patches which are otherwise easy to overlook. Findings from this study will help us to refine our understanding of the evolution of heterogeneous urban environments. MDPI 2017-06-06 /pmc/articles/PMC5492285/ /pubmed/28587309 http://dx.doi.org/10.3390/s17061304 Text en © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Yu, Zhoulu
Wang, Yaohui
Deng, Jinsong
Shen, Zhangquan
Wang, Ke
Zhu, Jinxia
Gan, Muye
Dynamics of Hierarchical Urban Green Space Patches and Implications for Management Policy
title Dynamics of Hierarchical Urban Green Space Patches and Implications for Management Policy
title_full Dynamics of Hierarchical Urban Green Space Patches and Implications for Management Policy
title_fullStr Dynamics of Hierarchical Urban Green Space Patches and Implications for Management Policy
title_full_unstemmed Dynamics of Hierarchical Urban Green Space Patches and Implications for Management Policy
title_short Dynamics of Hierarchical Urban Green Space Patches and Implications for Management Policy
title_sort dynamics of hierarchical urban green space patches and implications for management policy
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5492285/
https://www.ncbi.nlm.nih.gov/pubmed/28587309
http://dx.doi.org/10.3390/s17061304
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