Urban green spaces, their spatial pattern, and ecosystem service value: The case of Beijing

2016 ◽  
Vol 56 ◽  
pp. 84-95 ◽  
Author(s):  
Liyan Xu ◽  
Hong You ◽  
Dihua Li ◽  
Kongjian Yu
Author(s):  
Minghui Yang ◽  
Yu Xie

Ecological conservation red line (ECRL) is gaining increasing academic attention as delimiting the minimum space scope of ecological protection and the bottom line of ecological security. Taking Nanjing as a case study, we divided the territory into ecological and non-ecological redline areas (ERAs and NERAs, respectively). This paper highlights two key research issues based on the 2005, 2010, 2015 and 2018 annual remote sensing data: (i) quantitative analysis of the Ecological Redline Policy (ERP) validity by conducting a horizontal comparison of the ERAs and NERAs; and (ii) exploration of the land-use transitions and spatial pattern changes affecting ecosystem service value (ESV). Results showed that delineating ECRL could effectively slow down the decline rate of ESV. The trend of eco-quality deterioration was greater than eco-quality improvement in Nanjing, presenting an ESV that declined slightly in the whole. According to our findings, we suggest that reasonably increasing eco-lands (woodland and water area) and decreasing construction land will enhance the regional ESV. Meanwhile, promoting the transition from production space to ecological space and depressing the encroachment of living space on other space types, will be instrumental in mitigating the ESV decline. The results of this study are expected to provide valuable implications for spatial planning and sustainable development in Nanjing.


2021 ◽  
Vol 9 ◽  
Author(s):  
Shunqi Cheng ◽  
Zhiqiang Liao ◽  
Yu Zhu

Urban green spaces (UGSs) improve the quality of life of urban inhabitants. With the acceleration of urbanization and changes in traffic networks, it remains unclear whether changes in the distribution of UGSs can satisfy the needs of all inhabitants and offer equal services to inhabitants from different socioeconomic backgrounds. This study addresses this issue by analyzing dynamic changes in UGS accessibility in 2012, 2016, and 2020 for inhabitants of the central urban area of Fuzhou in China at the community level. The study introduces multiple transportation modes for an accessibility estimation based on a framework using the two-step floating catchment area method and examines the dynamic changes in community deprivation of UGS accessibility using Kernel regularized least squares, a machine learning algorithm. The results demonstrate that spatial disparities of UGS accessibility exist among the multi-transport modes and vary with time. Communities with high accessibility to UGSs by walking are scattered around the urban area; for accessibility by cycling, the high accessibility regions expand and surround the regions with low accessibility in the core urban areas, forming a semi-enclosed spatial pattern. However, the core urban spatial orientation of UGS accessibility by public transit demonstrates a reverse trend to the above two modes. The spatial pattern of UGS accessibility also varies over time, and the growth rate of accessibility slightly declined during the study period. Furthermore, the increase in UGS accessibility tended to slow from 2016–2020 compared with 2012–2016, and the trend toward equality was also erratic. The degree of deprivation for communities first weakened and was then aggravated, corresponding to the slowdown in the growth rate of accessibility, leading to the persistence existence of social inequality. Moreover, significant deprivation mainly exists among less educated people or those using the cycling and integrated travel modes. Although public transport is developing, deprived communities, such as communities with large proportion of older people, have experienced a decline in access to UGSs by public transport. Based on these findings, the study proposes a policy framework for the balanced distribution of UGSs as part of urbanization.


2020 ◽  
Vol 431 ◽  
pp. 109178 ◽  
Author(s):  
Zhen Guo ◽  
Zhiwei Zhang ◽  
Xiaogang Wu ◽  
Jing Wang ◽  
Peidong Zhang ◽  
...  

2019 ◽  
Vol 96 ◽  
pp. 111-119 ◽  
Author(s):  
Caige Sun ◽  
Tao Lin ◽  
Qianjun Zhao ◽  
Xinhu Li ◽  
Hong Ye ◽  
...  

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