Regional Development

Coupling coordination relationship between park green spaces and urban functional spaces and its influencing factors: A case of Urumqi City

  • ZHAO Xuechun ,
  • JU Chunyan
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  • Faculty of Public Administration (Faculty of Law), Xinjiang Agricultural University, Urumqi 830052, Xinjiang, China

Received date: 2023-08-28

  Revised date: 2023-10-23

  Online published: 2024-05-30

Abstract

The study of the coupled coordination relationship between park green spaces and urban functional spaces, along with its influencing factors, is crucial for optimizing the layout of park green spaces and enhancing the synergistic development of urban functional spaces. This research focuses on the central urban area of Urumqi City, Xinjiang, China, employing kernel density analysis, standard deviation ellipse, coupling coordination degree model, and Geodetector. It aims to analyze the distribution patterns of park green spaces and urban functional spaces and investigate their coupling and coordination relationship and influencing factors. The findings reveal that: (1) Parks and urban functional spaces exhibit a spatial aggregation characteristic that is dense at the center and sparse at the edges, diminishing in concentric circles and expanding toward the northwest. (2) The distribution centers of parks and urban functional spaces have shifted away from the city center, with parks, residential, transportation, and public service spaces aligning in the northwest-southeast direction, while leisure and commercial spaces align in the northeast-southwest direction. (3) The predominant coupling and coordination type between park green spaces and various urban functional spaces is moderate dissonance, with the degree of coupling and coordination displaying spatial differentiation characterized by higher levels in the center and lower levels in the eastern, western side, and extremities of the north-south axis. Demographic factors and transportation conditions are identified as primary influences on the degree of coupling and coordination between parks and urban functional spaces, with socio-economic factors playing a secondary role.

Cite this article

ZHAO Xuechun , JU Chunyan . Coupling coordination relationship between park green spaces and urban functional spaces and its influencing factors: A case of Urumqi City[J]. Arid Land Geography, 2024 , 47(5) : 898 -908 . DOI: 10.12118/j.issn.1000-6060.2023.452

References

[1] 陈阳, 张琳琳, 马仁锋, 等. 城市绿色空间可达性与居民分布的空间匹配与影响因素[J]. 生态学报, 2022, 42(24): 9971-9980.
  [Chen Yang, Zhang Linlin, Ma Renfeng, et al. Spatial match between urban residents’ distribution and green space accessibility and its driving force[J]. Acta Ecologica Sinica, 2022, 42(24): 9971-9980. ]
[2] 张彪, 徐洁, 谢高地, 等. 2000—2010年北京城市绿色空间格局动态分析[J]. 生态科学, 2016, 35(6): 24-33.
  [Zhang Biao, Xu Jie, Xie Gaodi, et al. Analysis on the pattern changes of urban green space in Beijing from 2000 to 2010[J]. Ecological Science, 2016, 35(6): 24-33. ]
[3] 成超男, 胡杨, 赵鸣. 城市绿色空间格局时空演变及其生态系统服务评价的研究进展与展望[J]. 地理科学进展, 2020, 39(10): 1770-1782.
  [Cheng Chaonan, Hu Yang, Zhao Ming. Progress and prospect of the spatiotemporal change and ecosystem services evaluation of urban green space pattern[J]. Progress in Geography, 2020, 39(10): 1770-1782. ]
[4] James P, Tzoulas K, Adams M D, et al. Towards an integrated understanding of green space in the European built environment[J]. Urban Forestry and Urban Greening, 2009, 8(2): 65-75.
[5] 李锋, 王如松. 城市绿色空间生态服务功能研究进展[J]. 应用生态学报, 2004, 15(3): 527-531.
  [Li Feng, Wang Rusong. Research advance in ecosystem service of urban green space[J]. Chinese Journal of Applied Ecology, 2004, 15(3): 527-531. ]
[6] Garcia D A. Green areas management and bioengineering techniques for improving urban ecological sustainability[J]. Sustainable Cities and Society, 2017, 30: 108-117.
[7] 木皓可, 高宇, 王子尧, 等. 供需平衡视角下城市公园绿地服务水平与公平性评价研究——基于大数据的实证分析[J]. 城市发展研究, 2019, 26(11): 10-15.
  [Mu Haoke, Gao Yu, Wang Ziyao, et al. Equity evaluation of park green space service level from the perspective of supply and demand balance: An empirical analysis based on big data[J]. Urban Development Studies, 2019, 26(11): 10-15. ]
[8] 赵志远, 丁逸尘, 杨喜平, 等. 基于手机定位数据的西宁市老年人公园绿地可达性预测[J]. 干旱区地理, 2023, 46(10): 1744-1756.
  [Zhao Zhiyuan, Ding Yichen, Yang Xiping, et al. Prediction of the accessibility of park and green space for the elderly in Xining City based on mobile phone location data[J]. Arid Land Geography, 2023, 46(10): 1744-1756. ]
[9] 隋洪鑫, 杨秀, 徐姗, 等. 城市功能空间更新研究进展与新时期重点方向[J]. 热带地理, 2020, 40(6): 1150-1160.
  [Sui Hongxin, Yang Xiu, Xu Shan, et al. Progress and hot research on urban functional space renewal in the new era[J]. Tropical Geography, 2020, 40(6): 1150-1160. ]
[10] 马燕坤. 城市群功能空间分工形成的演化模型与实证分析[J]. 经济管理, 2016, 38(12): 31-46.
  [Ma Yankun. The evolvement model and empirical analysis of the functional spatial division of urban agglomeration[J]. Business and Management Journal, 2016, 38(12): 31-46. ]
[11] Duranton G, Puga D. From sectoral to functional urban specialisation[J]. Journal of Urban Economics, 2005, 57(2): 343-370.
[12] 金贵, 邓祥征, 张倩, 等. 武汉城市圈国土空间综合功能分区[J]. 地理研究, 2017, 36(3): 541-552.
  [Jin Gui, Deng Xiangzheng, Zhang Qian, et al. Comprehensive function zoning of national land space for Wuhan Metropolitan Region[J]. Geographical Research, 2017, 36(3): 541-552. ]
[13] 康雨豪, 王玥瑶, 夏竹君, 等. 利用POI数据的武汉城市功能区划分与识别[J]. 测绘地理信息, 2018, 43(1): 81-85.
  [Kang Yuhao, Wang Yueyao, Xia Zhujun, et al. Identification and classification of Wuhan urban districts based on POI[J]. Journal of Geomatics, 2018, 43(1): 81-85. ]
[14] 王勇, 李广斌. 苏南乡村聚落功能三次转型及其空间形态重构——以苏州为例[J]. 城市规划, 2011, 35(7): 54-60.
  [Wang Yong, Li Guangbin. Functional transformation and spatial restructuring of rural settlements in southern Jiangsu: A case study of Suzhou[J]. City Planning Review, 2011, 35(7): 54-60. ]
[15] 刘滨谊, 贺炜, 刘颂. 基于绿地与城市空间耦合理论的城市绿地空间评价与规划研究[J]. 中国园林, 2012, 28(5): 42-46.
  [Liu Binyi, He Wei, Liu Song. Study of the evaluation and planning of urban green space based on the coupling theory of green space and city space[J]. Chinese Landscape Architecture, 2012, 28(5): 42-46. ]
[16] 黄槟铭, 李方正, 李雄. 耦合空间规划体系的区域绿地规划思路[J]. 规划师, 2020, 36(2): 5-11.
  [Huang Bingming, Li Fangzheng, Li Xiong. Regional green space planning that fits national land use and spatial plan system[J]. Planners, 2020, 36(2): 5-11. ]
[17] 伍萱, 邵大伟, 吴殿鸣. 南京公园绿地与城市功能空间的时空关联特征——基于Ripley’s K函数与POI数据[J]. 中国园林, 2023, 39(5): 92-97.
  [Wu Xuan, Shao Dawei, Wu Dianming. Spatiotemporal correlation characteristics between park green space and urban functional space in Nanjing: Based on Ripley’s K function and POI data[J]. Chinese Landscape Architecture, 2023, 39(5): 92-97. ]
[18] 邵大伟, 吴殿鸣. 城市功能空间对绿地格局作用效应的地理探测——以南京为例[J]. 中国园林, 2021, 37(9): 31-35.
  [Shao Dawei, Wu Dianming. Geographical detection of the effect of urban functional space on green space pattern: A case study of Nanjing[J]. Chinese Landscape Architecture, 2021, 37(9): 31-35. ]
[19] 姜佳怡, 戴菲, 章俊华. 基于POI数据的上海城市功能区识别与绿地空间评价[J]. 中国园林, 2019, 35(10): 113-118.
  [Jiang Jiayi, Dai Fei, Zhang Junhua. Urban functional zone recognition and green space evaluation of Shanghai based on POI data[J]. Chinese Landscape Architecture, 2019, 35(10): 113-118. ]
[20] 邵大伟, 殷文彧, 吴殿鸣. 基于街区空间的公园绿地-道路-居住用地分布关系研究——以南京为例[J]. 现代城市研究, 2021(12): 116-124.
  [Shao Dawei, Yin Wenyu, Wu Dianming. Research on the distribution relationship of park green space-road-residential land in the block space: A case study of Nanjing[J]. Modern Urban Research, 2021(12): 116-124. ]
[21] 邵大伟, 吴殿鸣, 刘志强. 绿地与居住用地演进的空间相关性研究——以南京主城区为例[J]. 中国园林, 2017, 33(12): 64-69.
  [Shao Dawei, Wu Dianming, Liu Zhiqiang. Spatial correlation of green space and residential land evolution in the central city of Nanjing[J]. Chinese Landscape Architecture, 2017, 33(12): 64-69. ]
[22] 刘雅轩, 陈彤. 基于POI数据的乌鲁木齐市城市公园绿地对周边住宅价格的影响研究[J]. 干旱区资源与环境, 2020, 34(11): 36-43.
  [Liu Yaxuan, Chen Tong. Impact of urban park green space on the price of peripheral housing in Urumqi[J]. Journal of Arid Land Resources and Environment, 2020, 34(11): 36-43. ]
[23] 雷一鸣, 陈曦, 杨辽, 等. 基于Worldview-2的乌鲁木齐城区绿地空间格局分析[J]. 干旱区研究, 2015, 32(6): 1233-1239.
  [Lei Yiming, Chen Xi, Yang Liao, et al. Analysis of green space landscape pattern in Urumqi based on Worldview-2[J]. Arid Zone Research, 2015, 32(6): 1233-1239. ]
[24] 蒲智, 刘萍, 杨辽, 等. 面向对象技术在城市绿地信息提取中的应用[J]. 福建林业科技, 2006, 33(1): 40-44.
  [Pu Zhi, Liu Ping, Yang Liao, et al. Study on extraction of urban green space using object-oriented classification method[J]. Journal of Fujian Forestry Science and Technology, 2006, 33(1): 40-44. ]
[25] 刘韬, 杨德刚, 张豫芳, 等. 城市公园绿地可达性时空变化及影响因素——以乌鲁木齐市为例[J]. 中国科学院大学学报, 2021, 38(3): 350-359.
  [Liu Tao, Yang Degang, Zhang Yufang, et al. Spatial-temporal change and influence factors of park green space accessibility in arid area: Taking Urumqi as an example[J]. Journal of University of Chinese Academy of Sciences, 2021, 38(3): 350-359. ]
[26] 王庆, 王承武. 大数据视角下的城市“三生”空间识别及分布特征研究——以乌鲁木齐市中心城区为例[J]. 资源开发与市场, 2022, 38(2): 142-147.
  [Wang Qing, Wang Chengwu. Research on spatial identification and distribution characteristics of “production-living-ecological” in cities from the perspective of big data: A case study of Urumqi City[J]. Resource Development Market, 2022, 38(2): 142-147. ]
[27] 陈洪星, 杨德刚, 徐红涛, 等. 基于POI的住宿业时空格局演化及与旅游景点的空间关联研究[J]. 干旱区地理, 2020, 43(5): 1382-1390.
  [Chen Hongxing, Yang Degang, Xu Hongtao, et al. Spatial and temporal evolution of the accommodation industry and spatial association with tourist spots based on POI[J]. Arid Land Geography, 2020, 43(5): 1382-1390. ]
[28] 李吉玫, 张毓涛. 乌鲁木齐不同功能区林带土壤重金属污染特征分析[J]. 生态环境学报, 2019, 28(9): 1859-1866.
  [Li Jimei, Zhang Yutao. Characteristics of heavy-metal pollution in forest belt soil of different functional zones in Urumqi, Xinjiang[J]. Ecology and Environmental Sciences, 2019, 28(9): 1859-1866. ]
[29] 谷岩岩, 焦利民, 董婷, 等. 基于多源数据的城市功能区识别及相互作用分析[J]. 武汉大学学报(信息科学版), 2018, 43(7): 1113-1121.
  [Gu Yanyan, Jiao Limin, Dong Ting, et al. Spatial distribution and interaction analysis of urban functional areas based on multi-source data[J]. Geomatics and Information Science of Wuhan University, 2018, 43(7): 1113-1121. ]
[30] Zhao N Z, Liu Y, Cao G F, et al. Forecasting China's GDP at the pixel level using nighttime lights time series and population images[J]. GIScience and Remote Sensing, 2017, 54(3): 407-425.
[31] 张珣, 钟耳顺, 张小虎, 等. 2004—2008年北京城区商业网点空间分布与集聚特征[J]. 地理科学进展, 2013, 32(8): 1207-1215.
  [Zhang Xun, Zhong Ershun, Zhang Xiaohu, et al. Spatial distribution and clustering of commercial network in Beijing during 2004—2008[J]. Progress in Geography, 2013, 32(8): 1207-1215. ]
[32] 张烈琴, 陆亦农, 龙震, 等. 新疆文化旅游空间分布格局[J]. 干旱区地理, 2023, 46(5): 823-833.
  [Zhang Lieqin, Lu Yi’nong, Long Zhen, et al. Spatial distribution pattern of cultural tourism in Xinjiang[J]. Arid Land Geography, 2023, 46(5): 823-833. ]
[33] 王淑佳, 孔伟, 任亮, 等. 国内耦合协调度模型的误区及修正[J]. 自然资源学报, 2021, 36(3): 793-810.
  [Wang Shujia, Kong Wei, Ren Liang, et al. Research on misuses and modification of coupling coordination degree model in China[J]. Journal of Natural Resources, 2021, 36(3): 793-810. ]
[34] 王劲峰, 徐成东. 地理探测器: 原理与展望[J]. 地理学报, 2017, 72(1): 116-134.
  [Wang Jinfeng, Xu Chengdong. Geodetector: Principle and prospective[J]. Acta Geographica Sinica, 2017, 72(1): 116-134. ]
[35] 邢忠, 朱嘉伊. 基于耦合协调发展理论的绿地公平绩效评估[J]. 城市规划, 2017, 41(11): 89-96.
  [Xing Zhong, Zhu Jiayi. Evaluation on fair performance of urban green space based on coupling model of coordinated development theory[J]. City Planning Review, 2017, 41(11): 89-96. ]
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