邻避设施空间分布特征及其与周边住宅价格的关系——广州案例

doi:10.18306/dlkxjz.2023.01.004

地理科学进展 ›› 2023, Vol. 42 ›› Issue (1): 42-52.doi: 10.18306/dlkxjz.2023.01.004

邻避设施空间分布特征及其与周边住宅价格的关系——广州案例

谢涤湘¹(), 吴淑琪¹, 常江²^,^*()

1.广东工业大学建筑与城市规划学院，广州 510090
2.上海大学上海美术学院建筑系，上海 200444

收稿日期:2022-05-25 修回日期:2022-08-29 出版日期:2023-01-28 发布日期:2023-02-06
通讯作者: *常江(1989— )，男，河北邯郸人，主要从事城市社会文化地理、城市更新研究。E-mail: jc@msu.edu
作者简介:谢涤湘(1974— )，男，湖南攸县人，教授，博士，主要从事城市社会文化地理、城市更新研究。E-mail: xiedixiang@126.com
基金资助:
国家自然科学基金项目(42071176);广东省科技计划项目(2020A1010020037);广东省社科规划项目(GD20SQ16)

The spatial distribution of NIMBY facilities and housing prices in surrounding areas: A case study of Guangzhou

XIE Dixiang¹(), WU Shuqi¹, CHANG Jiang²^,^*()

1. School of Architecture and Urban Planning, Guangdong University of Technology, Guangzhou 510090, China
2. Department of Architecture, Shanghai Academy of Fine Arts, Shanghai University, Shanghai 200444, China

Received:2022-05-25 Revised:2022-08-29 Online:2023-01-28 Published:2023-02-06
Supported by:
National Natural Science Foundation of China(42071176);Science and Technology Plan of Guangdong Province(2020A1010020037);Guangdong Planning Office of Philosophy and Social Science(GD20SQ16)

摘要/Abstract

摘要：

随着中国城镇的快速发展以及市民环境意识的提高，由邻避设施引发的矛盾日益增多。合理规划邻避设施，是促进环境正义、推动社会和谐的重要课题。论文从“规划云平台”获取广州主城区邻避设施的地理信息数据，通过Python语句编码收集广州主城区小区平均房价数据，运用克里金插值法分析邻避设施的空间分布特征，构建多元线性回归模型和地理加权回归模型研究邻避设施与周边住宅价格的关系。研究发现，广州主城区邻避设施的布局与低收入住宅区的分布在空间上具有一致性，邻避设施主要分布在房价较低的住宅区周边；邻避设施对周边小区房价的影响与邻避设施的类型和所在区位相关，城市边缘区的邻避设施对房价造成了显著的负面影响，而城市中心良好的区位条件、基础设施与公共服务配套一定程度上抵消了邻避设施的负外部性；污名化类的邻避设施对房价的影响程度明显小于污染类、风险聚集类和心理不悦类邻避设施。本研究对有关城市邻避设施的科学规划布点具有一定的借鉴和指导意义。

关键词: 邻避设施, 环境正义, 地理加权回归模型, 房价, 广州

Abstract:

With the rapid development of cities and the improvement of citizens' environmental awareness in China, tensions and conflicts caused by "Not In My Backyard" (NIMBY) facilities have increased. How to plan NIMBY facilities properly has become an essential issue for promoting environmental justice and social harmony. We obtained the geographic data of the NIMBY facilities in the main urban area of Guangzhou City from the Planning Cloud Platform. Using Python coding, we also collected housing price data from major real-estate brokerage companies. Kriging interpolation was used to analyze the spatial distribution characteristics of the NIMBY facilities. We used both ordinary least squares regression and geographically weighted regression to investigate the relationship between the locations of NIMBY facilities and housing prices in their surrounding areas. Results show that the distribution of NIMBY facilities in the main urban area of Guangzhou is spatially consistent with the distribution of low-income neighborhoods. The NIMBY facilities are mainly distributed around neighborhoods with lower housing prices. The impact of NIMBY facilities on the housing prices of surrounding neighborhoods is related to the type and location of NIMBY facilities. The feature of NIMBY facilities in the urban peripheries negatively impact housing prices. In the core urban area, however, good location, infrastructure, and public services have, to some extent, canceled out the negative impacts of NIMBY facilities on housing prices. The impact of stigma related NIMBY facilities on housing prices is significantly lower than that of pollution, high safety risk, and psychological distress related NIMBY facilities. This study provides scientific guidelines for urban NIMBY planning.

Key words: NIMBY facilities, environmental justice, geographically weighted regression, housing price, Guangzhou

谢涤湘, 吴淑琪, 常江. 邻避设施空间分布特征及其与周边住宅价格的关系——广州案例[J]. 地理科学进展, 2023, 42(1): 42-52.

XIE Dixiang, WU Shuqi, CHANG Jiang. The spatial distribution of NIMBY facilities and housing prices in surrounding areas: A case study of Guangzhou[J]. PROGRESS IN GEOGRAPHY, 2023, 42(1): 42-52.

图/表 9

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分类	内容	数量
污染类邻避设施 (81个)	火车、高铁站	4
	污水处理设施	4
	垃圾处理设施	38
	废品站	30
	屠宰场	5
风险聚集类邻避设施 (93个)	发电厂	1
	化工厂	8
	加气站	33
	加油站	51
心理不悦类邻避设施 (35个)	殡仪馆	1
	骨灰楼	18
	火葬场	1
	墓地	15
污名化类邻避设施 (8个)	传染病医院	2
	监狱	1
	戒毒中心	3
	精神病院	2

变量类型	变量名	量化方法
主解释变量	DisNIMBY	到最近邻避设施的距离
控制变量	RoomAge	房龄
	DisCBD	到CBD的距离
	DisSchool	到最近学校(小学或中学)的距离
	DisSubway	到最近地铁站的距离
	DisPark	到最近公园绿地的距离
	DisHospital	到最近医院的距离

价格区间 /(元/m²)	房价较低小区(即“低收入小区”)			房价中等小区(即“中等收入小区”)			房价较高小区(即“中高收入小区”)
价格区间 /(元/m²)	13822~23997	23998~29084	29085~34171	34172~39259	39260~45129	45130~53347	53348~63914	63915~78393	78394~113614
数量/个	46	53	60	29	17	9	2	1	0
百分比/%	21.20	24.42	27.65	13.36	7.84	4.15	0.92	0.46	0

变量类型	变量名	Moran's I
主解释变量	DisNIMBY	0.437^*
控制变量	RoomAge	0.114^*
	DisCBD	0.753^*
	DisSchool	0.366^*
	DisSubway	0.340^*
	DisPark	0.385^*
	DisHospital	0.379^*

模型	AICc	R²	调整R²
多元线性回归模型	91048.640	0.329	0.328
地理加权回归模型	90204.103	0.464	0.456

邻避设施空间分布特征及其与周边住宅价格的关系——广州案例

The spatial distribution of NIMBY facilities and housing prices in surrounding areas: A case study of Guangzhou

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