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

Abstract

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

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.

Figures/Tables 9

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References 37

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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

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

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