中国大城市公园绿地可达性的公平性研究——以武汉市中心城区为例

doi:10.18306/dlkxjz.2022.04.007

Abstract

Abstract:

Urban park green space (UPGS) is an important part of the urban ecosystem. Good accessibility of UPGS can promote urban livability and improve residents' well-being. It is important to evaluate the fairness of UPGS accessibility. Taking the central city of Wuhan as a study case and 2020 as the research time period, this study measured the accessibility from the supply and demand aspects, evaluated the spatial characteristics of the accessibility of UPGS from both the local and global perspectives, and further explored the relationship between accessibility and residents' social and economic conditions, in order to explore its social equity. Our findings include: 1) The spatial distribution of accessibility of regional, city, and comprehensive level UPGS is better than that of community level UPGS. 2) The spatial pattern of the overall accessibility of UPGS in the central city area of Wuhan gradually decreases from the core to the periphery. The communities with more UPGS and higher UPGS density show a higher level of accessibility. 3) There is a positive spatial correlation between UPGS accessibility and residents' socioeconomic conditions. The communities with higher housing prices also have higher UPGS accessibility. Thereby we identified marked social inequality in terms of the UPGS accessibility for Wuhan. It is recommended that in the future we should be further concerned with the optimization and regulation of the layout of UPGS with more nuance. While implementing the universal strategies, we should adopt targeted strategies and implement precise policies for the needs of different regions and different social groups. This study contributes to the literature in several ways. Using multi-source data and new technology to optimize indicators and data sources, the quality of parks was measured from UPGS area, ecosystem service value (ESV), recreation facilities, and safety conditions and various traffic patterns, real-time conditions, and selection preferences of different age groups, and so on were considered. At the same time, this study paid attention to the social inequality of accessibility, which enriches the empirical content and case materials and provides a scientific basis for the layout of urban infrastructure and the practice of environmental justice.

Key words: urban park green space, multi-G2SFCA, accessibility, equity, Wuhan City

WANG Zilin, LI Zhigang, CHENG Hanbei. The equity of urban park green space accessibility in large Chinese cities: A case study of Wuhan City[J].PROGRESS IN GEOGRAPHY, 2022, 41(4): 621-635.

Figures/Tables 11

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数据大类	数据子类	数据来源	软件及预处理
基础地理数据	武汉行政区划数据	地理空间数据云	ArcGIS 10.4
	土地利用变化(LUCC)数据	http://data.ess.tsinghua.edu.cn/ (2017年,精度为30 m×30 m)	ArcGIS 10.4(掩膜提取、栅格转面、地物分类提取)
	路网数据^a	OpenStreetMap开放共享数据库(www.openstreetmap.org)	ArcGIS 10.4(合并、相交)
社区数据	社区物业费标准	运用Python从安居客^b、链家网^c、搜房网^d(https://wuhan.anjuke.com/community/、 https://wh.lianjia.com/xiaoqu/、https://wh.soufun.com/ )爬取武汉社区POI数据(三者互为补充)	ArcGIS 10.4(克里金插值、分区统计、创建渔网、属性表连接和关联、标识)
	社区建成时长		ArcGIS 10.4(克里金插值、分区统计、创建渔网、属性表连接和关联、标识)
	名称	运用Python从安居客^b、链家网^c(https://wuhan.anjuke.com/community/、 https://wh.lianjia.com/xiaoqu/ )爬取武汉社区POI数据(二者互为补充)	ArcGIS 10.4(提取相应经纬度的坐标点、人工法分类、相交)、PYcharm(爬取POI)、Datamap for excel(路线规划)
	经纬度
	户数
	房价
UPGS数据	名称	运用Python从百度地图^e(http://lbsyun.baidu.com/)的web API接口爬取武汉UPGS的POI数据
	经纬度
	面积
人口数据	各出行方式的人口比例	2020武汉交通大数据分析、《2020武汉交通发展年度报告》	对全市数据与短期短途游憩锻炼目的综合分析
	各年龄层人口比例	《武汉统计年鉴2020》《武汉市2019年国民经济和社会发展统计公报》《2020年湖北省国民经济和社会发展统计公报》	用全市数据代替
	高教育水平人口比例	武汉市第六次人口普查统计数据	ArcGIS 10.4(克里金插值、分区统计、创建渔网、属性表连接和关联、标识)
	社区人口密度
	外来人口比例

出行方式	速度/(km/h)	社区型/km	区域型/km	全市型/km	综合型/km
步行	5	0.5	1.5	3	5
骑行	20	2	6	12	20
公交	30	3	9	18	30
驾车	50	5	15	30	50

公园质量特征权重		相关指标赋分及不同年龄居民需求比例
公园质量特征权重		公园类型	IF_j	SA_j	D_k₁	D_k₂	D_k₃	D_k₄
w₁	0.27	社区型	3	3	0.19	0.10	0.17	0.25
w₂	0.19	区域型	5	7	0.21	0.23	0.27	0.21
w₃	0.40	全市型	7	9	0.25	0.28	0.35	0.3
w₄	0.14	综合型	9	5	0.35	0.39	0.21	0.24

区域	社区总量/个	低可达性
区域	社区总量/个	数量/个	占比/%	数量/个	占比/%	数量/个	占比/%	数量/个	占比/%	数量/个	占比/%
江岸区	893	197	22.06	139	15.57	222	24.86	241	26.98	94	10.53
江汉区	617	150	24.31	119	19.29	142	23.01	139	22.53	67	10.86
硚口区	510	117	22.94	122	23.92	111	21.76	120	23.53	40	7.84
汉阳区	594	144	24.24	172	28.96	128	21.54	123	20.70	27	4.55
武昌区	945	183	19.37	180	19.05	252	26.67	234	24.76	96	10.16
青山区	253	57	22.53	76	30.04	59	23.32	45	17.79	16	6.32
洪山区	856	376	43.93	137	16.00	155	18.11	126	14.92	62	7.25

变量	指标	OLS结果	变量	指标	SLM结果	SEM结果
自变量	ln房价	1.325^***(0.306)	自变量	ln房价	1.234^***(0.303)	1.257^***(0.310)
控制变量	ln社区人口密度	-0.358^**(0.123)	控制变量	ln社区人口密度	-0.279^*(0.122)	-0.357^*(0.144)
	外来人口比例	-3.448^***(0.656)	控制变量	外来人口比例	-2.789^***(0.654)	-3.356^***(0.776)
	高教育水平人口比例	4.414^***(0.583)		高教育水平人口比例	3.689^***(0.584)	4.391^***(0.698)
	社区物业费标准	-0.194(0.217)		社区物业费标准	-0.150(0.215)	-0.123(0.252)
	社区建成时长	0.202^***(0.039)		社区建成时长	0.169^***(0.039)	0.209^***(0.045)
结果指标	常数	-4.734^*(3.027)	结果指标	常数	-5.334^*(2.995)	-4.312^*(3.148)
	Moran's I(error)	8.898^***	结果指标	空间滞后项	67.280^***	—
	LM(lag)	78.542^***		空间误差项	—	65.576^***
	Robust LM(lag)	3.090^*		Log Likelihood	-15067.730	-15066.9
	LM(error)	76.258^***		AIC	30149.8	30149.5
	Robust LM(error)	0.807^*		SC	30201.3	30194.6
	LM(SARMA)	79.348^***		R²	0.851	0.855
	Log Likelihood	-15100.5		N	4668	4668
	AIC	30215
	SC	30260.2
	R²	0.667
	N	4468

The equity of urban park green space accessibility in large Chinese cities: A case study of Wuhan City

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