珠三角城市群生态游憩空间分异特征及关联性因素

doi:10.11821/dlyj020200376

地理研究 ›› 2020, Vol. 39 ›› Issue (9): 2148-2164.doi: 10.11821/dlyj020200376

珠三角城市群生态游憩空间分异特征及关联性因素

王甫园¹^,³(), 王开泳¹^,³(), 虞虎¹^,³, 陈田¹^,²^,³

1.中国科学院地理科学与资源研究所,北京 100101
2.粤港澳大湾区战略研究院,广州 510070
3.中国科学院区域可持续发展分析与模拟重点实验室,北京 100101

收稿日期:2020-05-06 修回日期:2020-06-08 出版日期:2020-09-20 发布日期:2020-11-20
通讯作者: 王开泳
作者简介:王甫园（1988-）,男,湖南新化人,博士后,研究方向为旅游地理与生态空间治理。E-mail: wangfy. 15b@igsnrr.ac.cn
基金资助:
国家自然科学基金青年科学基金项目(41901181);国家自然科学基金面上项目(41871151);中国博士后科学基金资助项目(2018M641457);粤港澳大湾区战略研究院建设专项(2019GDASYL-0202001);广东省科学院发展专项(2020GDASYL-20200102002)

Spatial differentiation and correlative factors of ecological recreation space distribution in the Pearl River Delta urban agglomeration

WANG Fuyuan¹^,³(), WANG Kaiyong¹^,³(), YU Hu¹^,³, CHEN Tian¹^,²^,³

1. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
2. Institute of Strategy Research for Guangdong, Hong Kong and Macao Greater Bay Area, Guangzhou 510070, China
3. Key Laboratory of Regional Sustainable Development Modeling, CAS, Beijing 100101, China

Received:2020-05-06 Revised:2020-06-08 Online:2020-09-20 Published:2020-11-20
Contact: WANG Kaiyong

摘要/Abstract

摘要：

生态游憩空间是居民放松身心、亲近自然的主要活动场所,是提升居民生活质量和幸福感的重要开放空间。随着城市群的一体化发展,以及城市群居民对居住环境和休闲品质要求的提高,生态空间游憩利用的区域组织成为了新的理论课题。本文在界定生态游憩空间并对其进行空间解译的基础上,运用GIS空间分析方法,对珠三角城市群生态游憩空间分布的集聚和分异特征进行了刻画,并分析了其与人文、自然生态要素的空间关系,揭示生态游憩空间分布存在的问题与成因。结果显示：① 各城市生态空间游憩利用率的空间分异明显,反映了生态空间游憩利用缺少有效的区域统筹。② 生态游憩空间数量、规模、等级以及生态空间游憩利用率分布具有空间集聚特征,但四者的集聚导向存在差异。③ 生态游憩空间分布与地形、交通具有空间依存关系,但与水系、旅游要素以及文化资源分布的关联性不明显。④ 生态游憩空间面积分布与人口密度分布相反,说明珠三角城市群生态空间游憩服务存在供需空间错位矛盾。

关键词: 珠三角城市群, 生态游憩空间, 空间分异, 分布, 关联性因素

Abstract:

As an open place for residents to relax and get close to nature, ecological recreation space (ERS) plays an important role in improving residents’ life quality and wellbeing. With the integrated development of urban agglomerations and the increasingly high requirements of urban residents for the quality of their habitat and leisure environment, the regional organization of recreational use of ecological space within urban agglomerations has become a new hot topic. Based on the definition and spatial interpretation of ERS, this paper analyzed the spatial agglomeration and differentiation characteristics of ERSs in the Pearl River Delta urban agglomeration (PRDUA) by using GIS spatial analysis methods. The spatial relationship between ERS and other humanities and natural ecological elements were also analyzed to reveal the problems and causes of the distribution of ERS. The results show that: (1) The spatial differentiation of recreational utilization rate of ecological space in each city is obvious, which reflects the lack of effective regional co-ordination of recreational utilization of ecological space. (2) The distribution of ERS’s number, scale, grade, and recreational utilization rate of ecological space is characterized by spatial agglomeration, but with different agglomeration orientations. (3) The distribution of ERS is spatially dependent on topography and traffic, but its link with the distribution of water systems, tourism elements, and cultural resources is not evident. (4) The area distribution of ERS is opposite to that of population density, suggesting the contradiction between the supply and demand of recreation services of ecological spaces. Compared with previous studies, this study attempted to reveal more factors that affect the spatial distribution of ERS in regional scale through the empirical study in PRDUA. It can be concluded that the factors affecting the spatial differentiation of ERS include three natural factors, i.e. topography, water system, and ecological space distribution, and three human factors, i.e. population density, transportation and regional policy and management. Interestingly, ERS distribution is not significantly correlated with the tourism elements and cultural resources, which suggests that the coordination between ERS layout and tourism and cultural system needs to be improved in the future in PRDUA.

Key words: the Pearl River Delta urban agglomeration, ecological recreation space, spatial differentiation, distribution, correlation factors

王甫园, 王开泳, 虞虎, 陈田. 珠三角城市群生态游憩空间分异特征及关联性因素[J]. 地理研究, 2020, 39(9): 2148-2164.

WANG Fuyuan, WANG Kaiyong, YU Hu, CHEN Tian. Spatial differentiation and correlative factors of ecological recreation space distribution in the Pearl River Delta urban agglomeration[J]. GEOGRAPHICAL RESEARCH, 2020, 39(9): 2148-2164.

图/表 10

表1

主要数据来源"

大类	具体类型	属性信息来源	获取信息的等级属性
生态游憩空间	森林公园	包含县级至国家级4个等级,名录、面积和等级信息从原广东省林业厅官方网站获得	国家级、省级、市级和县级
	湿地公园	包含县级至国家级4个等级,名称、面积和等级信息通过申请原广东省林业厅政府信息公开获得	国家级、省级、市级和县级
	风景名胜区	有国家级、省级两个等级,名称和等级从《广东省风景名胜区体系规划（2015—2030）》获得	国家级、省级
	水利风景区	包含国家级、省级两个等级,缺乏省级数据,仅从水利部官方网站获得国家级水利风景区名录,其面积经由网络搜索获得	国家级
	地质公园	包含国家级和省级两级,名录、面积和等级信息通过向原广东省国土资源厅申请信息公开获得	国家级、省级
	生态型景区	名录和等级信息来自广东省旅游局官方网站^[34],面积同样通过网络搜索整理	5A、4A、3A、2A
	城市公园	名录、面积和等级信息通过网络和谷歌地图综合整理	城市综合公园和专类公园
其他地理数据	公路网	根据15级的谷歌影像图,对区域内公路进行数字化处理,建立城乡道路网Shapefile图层	高速公路、国道、省道、县道
	水系、高程和坡度	水系根据城市群自然地理地图数字化得来。90 m空间分辨率的珠三角城市群的高程和坡度栅格图下载自地理空间数据云	—
	人口	人口数据方面,从最近的一次人口普查中获取乡镇街道人口数据的做法,被国内外研究所采用^{[18, 35]},因而本文的乡镇街道（含少数开发区、林场和管委会管辖区）人口数据来自广东省2010年人口普查分乡、镇、街道资料^[36],共计611个人口统计单元。借助广东省乡镇街道地图,对乡镇街道边界进行数字化,然后将人口属性赋予每个乡镇街道,得到乡镇街道人口分布矢量图	乡镇级
	旅游要素 POI	旅游要素分为住宿、购物、餐饮和休闲娱乐四类,数据为BIGEMAP地图下载器提取的POI（Point of Interest）,其中购物点414404个,休闲娱乐点77938个,住宿点21088个,餐饮点113773个	—
	文化资源	根据数据可得性,选取省级以上文物保护单位作为文化资源,考察其与生态游憩空间的空间关系。省级文物保护单位名称与地理位置信息来源于网络公开发布的广东省第1-8批省级文物保护单位名录,总计299项。全国重点文物保护单位来源于国家文物局网站公布的第1~7批全国重点文物保护单位名录,总计62项^[37]。通过查询361个文化资源点的经纬度信息,对其进行空间定位,建立点状矢量数据集	国家级、省级

表1

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参考文献 41

[1]	Wolch J R, Byrne J, Newell J P. Urban green space, public health, and environmental justice: The challenge of making cities ‘just green enough’. Landscape and Urban Planning, 2014, 125:234-244.
[2]	Serret H, Raymond R, Foltêtec J-C, et al. Potential contributions of green spaces at business sites to the ecological network in an urban agglomeration: The case of the Ile-de-France region, France. Landscape and Urban Planning, 2014, 131:27-35.
[3]	Su Y, Chen X, Liao J, et al. Modeling the optimal ecological security pattern for guiding the urban constructed land expansions. Urban Forestry & Urban Greening, 2016, 19:35-46.
[4]	Peng J, Zhao M, Guo X, et al. Spatial-temporal dynamics and associated driving forces of urban ecological land: A case study in shenzhen city, China. Habitat International, 2017, 60:81-90.
[5]	Wang J, He T, Lin Y. Changes in ecological, agricultural, and urban land space in 1984-2012 in China: Land policies and regional social-economical drivers. Habitat International, 2018, 71:1-13.
[6]	Xie H, He Y, Xie X. Exploring the factors influencing ecological land change for China's Beijing-Tianjin-Hebei region using big data. Journal of Cleaner Production, 2017, 142:677-687.
[7]	Jiang W, Wang W, Chen Y, et al. Quantifying driving forces of urban wetlands change in Beijing City. Journal of Geographical Sciences, 2012, 22:301-314.
[8]	姚娜, 马履一, 杨军, 等. 北京市平原地区1992-2013年生态空间演变. 生态学杂志. 2015, 34(5): 1427-1434.
	[ Yao Na, Ma Lvyi, Yang Jun, et al. Changes of ecological spaces in Beijing's plain areas between 1992 and 2013. Chinese Journal of Ecology, 2015, 34(5): 1427-1434.]
[9]	Xie H, Liu Z, Wang P, et al. Exploring the mechanisms of ecological land change based on the spatial autoregressive model: A case study of the poyang lake eco-economic zone, China. International Journal of Environmental Research and Public Health, 2014, 11(1): 583-599. doi: 10.3390/ijerph110100583 pmid: 24384778
[10]	魏冶, 修春亮, 高瑞, 等. 基于高斯两步移动搜索法的沈阳市绿地可达性评价. 地理科学进展, 2014, 33(4): 479-487.
	[ Wei Ye, Xiu Chunliang, Gao Rui, et al. Evaluation of green space accessibility of Shenyang using Gaussian based 2-step floating catchment area method. Progress in Geography, 2014, 33(4): 479-487.]
[11]	Chen J, Chang Z. Rethinking urban green space accessibility: Evaluating and optimizing public transportation system through social network analysis in megacities. Landscape and Urban Planning, 2015, 143:150-159.
[12]	Camps-Calvet M, Langemeyer J, Calvet-Mir L, et al. Ecosystem services provided by urban gardens in Barcelona, Spain: Insights for policy and planning. Environmental Science & Policy, 2016, 62:14-23.
[13]	Wu J G. Urban ecology and sustainability: The state-of-the-science and future directions. Landscape and Urban Planning, 2014, 125:209-221.
[14]	Triguero-Mas M, Dadvand P, Cirach M, et al. Natural outdoor environments and mental and physical health: Relationships and mechanisms. Environment International, 2015, 77:35-41. doi: 10.1016/j.envint.2015.01.012 pmid: 25638643
[15]	Nieuwenhuijsen M J, Khreis H, Triguero-Mas M, et al. Fifty shades of green pathway to healthy urban living. Epidemiology, 2017, 28(1): 63-71. pmid: 27525811
[16]	吴健生, 司梦林, 李卫锋. 供需平衡视角下的城市公园绿地空间公平性分析: 以深圳市福田区为例. 应用生态学报, 2016, 27(9): 2831-2838.
	[ Wu Jiansheng, Si Menglin, Li Weifeng. Spatial equity analysis of urban green space from the perspective of balance between supply and demand: A case study of Futian District, Shenzhen, China. Chinese Journal of Applied Ecology, 2016, 27(9): 2831-2838.]
[17]	Fan P, Xu L, Yue W, et al. Accessibility of public urban green space in an urban periphery: The case of Shanghai. Landscape and Urban Planning, 2017, 165:177-192.
[18]	Dai D. Racial/ethnic and socioeconomic disparities in urban green space accessibility: Where to intervene? Landscape and Urban Planning, 2011, 102(4): 234-244.
[19]	Wei F. Greener urbanization? Changing accessibility to parks in China. Landscape and Urban Planning, 2017, 157:542-552.
[20]	李孟桐, 杨令宾, 魏冶. 高斯两步移动搜索法的模型研究: 以上海市绿地可达性为例. 地理科学进展, 2016, 35(8): 990-996.
	[ Li Mengtong, Yang Lingbin, Wei Ye. Improved Gaussian based 2-step floating catchment area method: A case study of green space accessibility in Shanghai. Progress in Geography, 2016, 35(8): 990-996.]
[21]	张鹏飞, 蔡忠亮, 张成, 等. 基于E2SFCA的城市旅游景点的潜在空间可达性分析. 测绘地理信息, 2015, 40(1): 76-79.
	[ Zhang Pengfei, Cai Zhongliang, Zhang Cheng. Potential spatial accessibility to urban scenic spots based on E2SFCA. Journal of Geomatics, 2015, 40(1): 76-79.]
[22]	Matthew Mcconnachie M, Shackleton C M. Public green space inequality in small towns in South Africa. Habitat International, 2010, 34(2): 244-248.
[23]	Jones K R. ' The Lungs of the City ': Green space, public health and bodily metaphor in the landscape of urban park history. Environment and History, 2018, 24(1): 39-58.
[24]	Ngom R, Gosselin P, Blais C. Reduction of disparities in access to green spaces: Their geographic insertion and recreational functions matter. Applied Geography, 2016, 66:35-51.
[25]	李玏, 刘家明, 宋涛, 等. 北京市绿带游憩空间分布特征及其成因. 地理研究, 2015, 34(8): 1507-1521.
	[ Li Le, Liu Jiaming, Song Tao, et al. Spatial characteristics and causes of recreational space in the urban green belt of Beijing, China. Geographical Research, 2015, 34(8): 1507-1521. ]
[26]	杨丽婷, 刘大均, 赵越, 等. 长江中游城市群森林公园空间分布格局及可达性评价. 长江流域资源与环境, 2016, 25(8): 1228-1237.
	[ Yang Liting, Liu Dajun, Zhao Yue, et al. Spatial pattern and accessibility of the forest parks in urban agglomeration in the middle reaches of the Yangtze River. Resources and Environment in the Yangtze Basin, 2016, 25(8): 1228-1237.]
[27]	王甫园, 王开泳, 刘汉初. 珠三角城市群生态空间游憩服务供需匹配性评价与成因分析: 基于改进的两步移动搜寻法. 生态学报, 2020, 40(11): 3622-3633.
	[ Wang Fuyuan, Wang Kaiyong, Liu Hanchu. The evaluation and influencing factors of spatial accessibility of ecological space recreation service in the Pearl River Delta urban agglomeration: A modified two-step floating catchment area method. Acta Ecologica Sinica, 2020, 40(11): 3622-3633.]
[28]	广东省统计局, 国家统计局广东调查总队. 2019年广东统计年鉴. 北京: 中国统计出版社, 2019.
	[ Guangdong Bureau of Statistics, Guangdong Survey Corps of the National Bureau of Statistics. Guangdong Statistical Yearbook 2019. Beijing: China Statistics Press, 2019.]
[29]	广东省委, 省人民政府. 广东省委省政府新一轮绿化广东大行动的决定. http://www.forestry.gov.cn/portal/slgy/s/2445/content-730481.html, 2020-4-20.
	[ Guangdong Provincial Party Committee, Guangdong Provincial Government. Guangdong Provincial Party Committee and Provincial Government's decision on a new round of greening Guangdong. http://www.forestry.gov.cn/portal/slgy/s/2445/content-730481.html, 2020-4-20.]
[30]	中共中央办公厅, 国务院办公厅. 关于划定并严守生态保护红线的若干意见. http://www.gov.cn/zhengce/2017-02/07/content_5166291.htm, 2020-7-3.
	[ General Office of the CPC Central Committee, General Office of the State Council. Several opinions on delineating and strictly observing the red line of ecological protection. http://www.gov.cn/zhengce/2017-02/07/content_5166291.htm, 2020-7-3.]
[31]	中国科学院资源环境科学数据中心. 2015年中国土地利用现状遥感监测数据. http://www.resdc.cn/data.aspx?DATAID=184, 2020-4-20.
	[ Data Center for Resources and Environmental Sciences, Chinese Academy of Sciences. emote sensing monitoring data of China's land use status in 2015. http://www.resdc.cn/data.aspx?DATAID=184, 2020-4-20.]
[32]	建设部. 《城市绿地分类标准》(CJJ/T 85—2002). http://www.linxiang.gov.cn/24733/24760/24821/24859/36947/content_1115834.html, 2020-4-20.
	[ Ministry of Construction. City Greenland Classification Standards (CJJ/T 85-2002). http://www.linxiang.gov.cn/24733/24760/24821/24859/36947/content_1115834.html, 2020-4-20.]
[33]	王甫园, 王开泳. 珠江三角洲城市群区域绿道与生态游憩空间的连接度与分布模式. 地理科学进展, 2019, 38(3): 428-440.
	[ Wang Fuyuan, Wang Kaiyong. Connectivity and distribution pattern of regional greenways and ecological recreation spaces in the Pearl River Delta urban agglomeration. Progress in Geography, 2019, 38(3): 428-440. ]
[34]	广东省旅游局. 广东省A级旅游景区名录(截至2017年9月8日). http://zwgk.gd.gov.cn/006940247/201710/t20171024_727479.html, 2020-4-20.
	[ Tourism Bureau of Guangdong Province. Directory of A-level tourist attractions in Guangdong Province (before September 8, 2017). http://zwgk.gd.gov.cn/006940247/201710/t20171024_727479.html, 2020-4-20.]
[35]	Cheng G, Zeng X, Duan L, et al. Spatial difference analysis for accessibility to high level hospitals based on travel time in Shenzhen, China. Habitat International, 2016, 53:485-494.
[36]	国务院人口普查办公室, 国家统计局. H中国2010年人口普查分乡、镇、街道资料. 北京: 中国统计出版社, 2012.
	[ Census Office of the State Council, National Bureau of Statistics. China Census by Township, Town, and Street in 2010. Beijing: China Statistics Press, 2012.]
[37]	国家文物局. 全国重点文物保护单位. http://www.sach.gov.cn/col/col1645/index.html, 2020-4-23.
	[ State Administration of Cultural Heritage. National key cultural relics protection unit. http://www.sach.gov.cn/col/col1645/index.html, 2020-4-23.]
[38]	广东省林业局. 提升市民“享绿”空间为美丽广东建设增速: 广东城郊森林公园建设发展纪实. http://zwgk.gd.gov.cn/006939916/201412/t20141224_561271.html, 2019-4-25.
	[ Guangdong Provincial Forestry Bureau. Promote the growth of citizens' “green space” for the construction of beautiful Guangdong - Documentary of Guangdong suburban forest park construction and development. http://zwgk.gd.gov.cn/006939916/201412/t20141224_561271 html, 2019-4-25.]
[39]	Zhou X, Wang Y C. Spatial-temporal dynamics of urban green space in response to rapid urbanization and greening policies. Landscape and Urban Planning, 2011, 100(3): 268-277.
[40]	Zhao J, Chen S, Jiang B, et al. Temporal trend of green space coverage in China and its relationship with urbanization over the last two decades. Science of the Total Environment, 2013, 442:455-65.
[41]	Tan P Y, Wang J, Sia A. Perspectives on five decades of the urban greening of Singapore. Cities, 2013, 32:24-32.

珠三角城市群生态游憩空间分异特征及关联性因素

Spatial differentiation and correlative factors of ecological recreation space distribution in the Pearl River Delta urban agglomeration

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[10]	王辉, 栾维新, 康敏捷. 渤海氮污染的来源结构与污染压力空间分布[J]. 地理研究, 2020, 39(1): 186-199.
[11]	邓粒子, 保继刚. 中国避暑型与避寒型宜人气候的分布特征及差异[J]. 地理研究, 2020, 39(1): 41-52.
[12]	陈万旭,李江风,曾杰,冉端,杨斌. 中国土地利用变化生态环境效应的空间分异性与形成机理[J]. 地理研究, 2019, 38(9): 2173-2187.
[13]	余国良,李建华,孙嘉欣,沈培培,杨春白雪. 基于地理探测器的中国城市男性青少年BMI影响因子探究[J]. 地理研究, 2019, 38(9): 2288-2301.
[14]	古恒宇,覃小玲,沈体雁. 中国城市流动人口回流意愿的空间分异及影响因素[J]. 地理研究, 2019, 38(8): 1877-1890.
[15]	刘晔,王若宇,薛德升,曾经元. 中国高技能劳动力与一般劳动力的空间分布格局及其影响因素[J]. 地理研究, 2019, 38(8): 1949-1964.