特殊自然地物对城市住宅地价和房价的影响——以武汉市为例

doi:10.18402/resci.2016.04.15

摘要/Abstract

摘要：

揭示微观影响因素对城市住宅地价和房价的影响作用关系,是提高城市地价和房价预测水平,有效进行土地和房地产市场宏观调控的基础工作。本文采用地理加权回归模型（GWR）定量测度与分析特殊自然地物湖、江、山体对城市住宅地价和房价的影响及其空间分异特征,并尝试根据影响因素作用的差异解释住宅地价和房价空间分布特征形成的部分原因。结果表明:①住宅地价和房价与各自然地物之间呈现空间非平稳的影响作用关系;②湖对住宅地价和房价的平均边际价值分别为0.11元/m²、0.52元/m²,江均为0.15元/m²;在区域分布上,住宅地价和房价高值区受湖和江的影响更显著,面积较大的湖泊（如东湖）因受周边商服繁华程度、供给能力等因素影响对住宅地价和房价的作用存在各向异性;城市的山体或因坡度小、分布零散及周边特殊用地结构如黄鹤楼等保护性建筑限制了区域土地的商业开发,使其对住宅地价和房价影响作用不显著;③住宅地价与房价受湖影响的作用变化趋势并未呈现空间一致性,而是切合了区域住宅地价和房价的价格走势,且变化幅度与价格高低呈正相关;住宅地价和房价受江影响的边际作用力大小差别不大,空间上表现为梯度和圈层两种不同的变化趋势。

关键词: 空间非平稳性, 住宅地价, 房价, 特殊自然地物, 江, 湖, 山体, 地理加权回归模型, 武汉市

Abstract:

Revealing the influence of micro factors on urban land price and housing price is essential to improve the predicting precision of urban land price change and house price change and exercise effective macro-control over land market and real estate market. The aim of this study was to use the Geographically Weighted Regression model to quantitatively measure the impacts of local special natural features （lakes,rivers and mountains）on urban residential land and housing prices and their spatial differences,and to explain the cause from the aspect of impact factors. We found that the spatial distributions of Moran's I,P value,R²,adjusted R² and regression parameters of the testing models can characterize the spatially non-stationary relationship between natural features and residential land and housing prices accurately. When it comes to effect strengths,the average marginal residential land and housing price affected by lakes is 0.11 CNY/m² and 0.52 CNY/m²,respectively,while that affected by lakes is 0.15 CNY/m² on both residential land and housing prices. Lakes and rivers have more distinguished impacts on residential land and housing in areas with high prices according to the dynamic trends of their effects. Meanwhile,affected by the existence of surrounding commercial districts,anisotropic relationships between large lakes like East Lake and housing prices exist. Those mountains with a scattered distribution and low gradient,limited estate developments by the protected specific artificial amenities alike Yellow Crane Tower,show an insignificant influence. Rather than fitting with the spatial change trends of housing price,the spatial dynamics of residential land and housing prices are similar with that of regional trends and the change range is positively correlated with price. Rivers generate analogous impacts on both residential land and housing prices with similar marginal effects,but in two different spatial trends of gradients and spheres.

Key words: spatial non-stationarity, residential land price, housing price, special natural features, lake, river, mountain, GWR, Wuhan

杨剩富, 胡守庚, 徐枫, 童陆亿. 特殊自然地物对城市住宅地价和房价的影响——以武汉市为例[J]. 资源科学, 2016, 38(4): 738-749.

YANG Shengfu,HU Shougeng,XU Feng,TONG Luyi. Influence on urban residential land and housing prices by special natural features in Wuhan[J]. Resources Science, 2016, 38(4): 738-749.

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参考文献 40

[1]	王婵婵,丁和庚,吴群. 容积率对城市住宅用地交易价格影响的定量研究-以南京市为例[J]. 资源科学,2009,31(1):123-129.
	[Wang C C,Ding H G,Wu Q.Quantitative study on the influence of capacity density on land price of urban residential land:A case study of Nanjing[J]. Resources Science,2009,31(1):123-129.]
[2]	罗罡辉,吴次芳,郑娟尔. 宗地面积对住宅地价的影响[J]. 中国土地科学,2007,21(5):66-69.
	[Luo G H,Wu C F,Zheng J E.The influence of parcel land area on housing land price[J]. China Land Science,2007,21(5):66-69.]
[3]	Colwell P F,Munneke H J.Land prices and land assembly in the CBD[J]. Journal of Real Estate Finance and Economics,1999,18(2):163-180.
[4]	Jim C Y,Chen W.Consumption preferences and environmental externalities:A hedonic analysis of the housing market in Guangzhou[J]. Geoforum,2007,38(2):414-431.
[5]	Benson E D,Hansen J L.Pricing housing amenities:The value of a view[J]. The Journal of Real Estate Finance and Economics,1998,16(1):55-73.
[6]	温海珍,卜晓庆,秦中伏. 城市湖景对住宅价格的空间影响-以杭州西湖为例[J]. 经济地理,2012,32(11):58-64.
	[Wen H Z,Bu X Q,Qin Z F.The spatial effect of urban lakes on housing prices-the case of the west lake in Hangzhou[J]. Economic Geography,2012,32(11):58-64.]
[7]	钟海玥,张安录,蔡银莺. 武汉市南湖景观对周边住宅价值的影响-基于Hedonic模型的实证研究[J]. 中国土地科学,2009,32(12):63-68.
	[Zhong H Y,Zhang A L,Cai Y Y.Impacts of the Nanhu lake in Wuhan city on the price of peripheral houses:Empirical research based on hedonic model[J]. China Land Science,2009,32(12):63-68.]
[8]	石忆邵,张蕊. 大型公园绿地对住宅价格的时空影响效应-以上海市黄兴公园绿地为例[J]. 地理研究,2010,29(3):510-520.
	[Shi Y S,Zhang R.Temporal-spatial impact effects of large-scale parks on residential prices:Exemplified by the Huangxing park in Shanghai[J]. Geographical Research,2010,29(3):510-520.]
[9]	夏宾,张彪,谢高地,等. 北京建城区公园绿地的房产增值效应评估[J]. 资源科学,2012,34(7):1347-1353.
	[Xia B,Zhang B,Xie G D,et al.The value-added effect of park green space on residential property in Beijing[J]. Resources Science,2012,34(7):1347-1353.]
[10]	冯长春,李维瑄,赵蕃蕃. 轨道交通对其沿线商品住宅价格的影响分析-以北京地铁5号线为例[J]. 地理学报,2011,68(8):1055-1062.
	[Feng C C,Li W X,Zhao F F.Influence of rail transit on nearby commodity housing prices:A case study of Beijing subway line five[J]. Acta Geographica Sinica,2011,68(8):1055-1062.]
[11]	Du H,Wub B,Barryc M.The short-term land value impacts of urban rail transit quantitative evidence from Sunderland,UK[J]. Land Use Policy,2007,24(1):223-233.
[12]	温海珍,贾生华. 住宅的特征与特征的价格-基于特征价格模型的分析[J]. 浙江大学学报(工学版),2004,38(10):101-105.
	[Wen H Z,Jia S H.Housing characteristics and hedonic price:Analysis based on hedonic price model[J]. Journal of Zhejiang University (Engineering Science),2004,38(10):101-105.]
[13]	郑新奇,王家耀,阎弘文,等. 数字地价模型在城市地价时空分析中的应用[J]. 资源科学,2004,26(1):14-21.
	[Zheng X Q,Wang J Y,Yan H W,et al.Design and application of digital land price model for land price evolvement in urban area[J]. Resources Science,2004,26(1):14-21.]
[14]	Hu S,Cheng Q,Wang L,et al.Multifractal characterization of urban residential land price in space and time[J]. Applied Geography,2012,34:161-170.
[15]	Brunsdont C,Fotheringham S,Chariton M.Geographically weighted regression-modelling spatial non-stationarity[J]. The Statistician,1998,47(2):431-443.
[16]	Zhang L,Gove J H,Heath L S.Spatial residual analysis of six modeling techniques[J]. Ecological Modelling,2005,186(2):154-177.
[17]	玄海燕,王静. 地理加权回归模型的平稳性检验[J]. 甘肃联合大学学报(自然科学版),2006,20(5):10-12.
	[Xuan H Y,Mei C L,Wang J.Stationary tests of geographically weighted regression model[J]. Journal of Gansu Lianhe University (Natural Sciences),2006,20(5):10-12.]
[18]	覃文忠,王建梅,刘妙龙. 混合地理加权回归模型算法研究[J]. 武汉大学学报(信息科学版),2007,32(2):115-119.
	[Qin W Z,Wang J M,Liu M L.An elevation model of InSAR and its accuracy analysis[J]. Geomatics and Information Science of Wuhan University,2007,32(2):115-119.]
[19]	罗罡辉. 基于GWR模型的城市住宅地价空间结构研究[D]. 杭州:浙江大学,2007.
	[Luo G H.Spatial Structure of Urban Housing Land Prices Based on GWR Model [D]. Hangzhou:Zhejiang University,2007.]
[20]	曾晖. 城市住宅价格时空分布规律研究[D]. 南京:南京林业大学,2012.
	[Zeng H.Research on the Spatial and Temporal Distri-bution Rule of Urban Residence Price-Taking Nanjing City and Jiangmen City as Example[D]. Nanjing:Nanjing Forestry University,2012.]
[21]	吕萍,甄辉. 基于GWR模型的北京市住宅用地价格影响因素及其空间规律研究[J]. 经济地理,2010,30(3):472-478.
	[Lv P,Zheng H.Affecting factors research of Beijing residential land price based on GWR model[J]. Economic Geography,2010,30(3):472-478.]
[22]	曹天邦,黄克龙,李剑波,等. 基于GWR的南京市住宅地价空间分异及演变[J]. 地理研究,2013,32(12):2324-2333.
	[Cao T B,Huang K L,Li J B,et al.Research on spatial variation and evolution of residential land price in Nanjing based on GWR model[J]. Geographical Research,2013,32(12):2324-2333.]
[23]	李志,周生路,张红富,等. 基于GWR模型的南京市住宅地价影响因素及其边际价格作用研究[J]. 中国土地科学,2009,23(10):20-25.
	[Li Z,Zhou S L,Zhang H F,et al.Exploring the factors impacting on the residential land price and measuring their marginal effects based on geographically weighted regression model:A case study of Nanjing[J]. China Land Science,2009,23(10):20-25.]
[24]	汤庆园,徐伟,艾福利. 基于地理加权回归的上海市房价空间分异及其影响因子研究[J]. 经济地理,2012,32(2):52-58.
	[Tang Q Y,Xu W,Ai F L.A GWR-based study on spatial pattern and structural determinants of Shanghai's housing price[J]. Economic Geography,2012,32(2):52-58.]
[25]	Wang K,Zhang C,Li W.Predictive mapping of soil total nitrogen at a regional scale:A comparison between geographically weighted regression and cokriging[J]. Applied Geography,2013,42(8):73-85.
[26]	崔长彬,姜石良,张正河. 河北县域经济影响因素的空间差异分析-基于贝叶斯地理加权回归方法[J]. 经济地理,2012,32(2):39-45.
	[Cui C B,Jiang S L,Zhang Z H. The analysis of spatial variability of influencing factors to county economy in Hebei-based on BGWR[J]. Economic Geography,32(2):39-45.]
[27]	Huang B,Wu B,Barry M.Geographically and temporally weighted regression for modeling spatio-temporal variation in house prices[J]. International Journal of Geographical Information Science,2010,24(3):383-401.
[28]	Propastina P.Modifying geographically weighted regression for estimating aboveground biomass in tropical rainforests by multispectral remote sensing data[J]. International Journal of App-lied Earth Observation and Geoinformation,2012,18(1):82-90.
[29]	Mei C,Wang N,Zhang W.Testing the importance of the explanatory variables in a mixed geographically weighted regression model[J]. Environment and Planning A,2006,38:587-598.
[30]	张静,张丽芳,濮励杰,等. 基于GWR模型的城市住宅地价的时空演变研究-以江苏省为例[J]. 地理科学,2012,32(7):828-834.
	[Zhang J,Zhang L F,Pu L J,Research on spatio-temporal variation of urban residential land price based on GWR model:A case study of Jiangsu province[J]. Scientia Geographica Sinica,2012,32(7):828-834.]
[31]	宁秀红,郭龙,张海涛. 基于空间自回归和地理加权回归模型的不同尺度下土地利用程度研究[J]. 华中农业大学学报,2013,32(4):48-54.
	[Ning X H,Guo L,Zhang H T.Compre-hensive degree of land-use at different scales based on spatial autocorrelation regression and geographically weighted regression models[J]. Journal of Huazhong Agricultural University,2013,32(4):48-54.]
[32]	毕宝德,柴强,李铃. 土地经济学[M]. 北京:中国人民大学出版社,2011.
	[Bi B D,Cai Q,Li L.Land Economic[M]. Beijing:China Renmin University Press,2011.]
[33]	卢新海,王玥. 地价与房价的关系及稳定地价的对策[J]. 统计与决策,2006,(1):50-52.
	[Lv X H,Wang Y.The relationship between land price and house price and the countermeasures of stabilizing land price[J]. Statistics and Decision,2006,(1):50-52.]
[34]	邹晓云. 地价房价谁抬升谁[J]. 瞭望新闻周刊,2004,(51):46-47.
	[Zhou X Y.The relationship between land value and house price[J]. News Weekend,2004,(51):46-47.]
[35]	周京奎. 城市土地价格波动对房地产业的影响-1999~2005年中国20城市的实证分析[J]. 当代经济科学,2006,28(4):1-7.
	[Zhou J K.The effect of urban land price fluctuation on real estate industry-empirical analysis with data of 20 cities 1999- 2005 in China[J]. Modern Economic Science,2006,28(4):1-7.]
[36]	严金海. 中国的房价与地价:理论、实证和政策分析[J]. 数量经济技术经济研究,2006,23(1):17-26.
	[Yan J H.Land price and housing price in China:A theoretical & empirical study[J]. The Journal of Quantitative & Technical Economics,2006,23(1):17-26.]
[37]	中共武汉市委,武汉人民政府. 武汉市2049[R]. 武汉:2014.
	[CPC Wuhan Municipal Committee,Wuhan People's Govern-ments.Wuhan 2049[R].Wuhan:2014.]
[38]	武汉市水务局,武汉市国土资源和规划局,武汉市园林局. 武汉市中心城区湖泊“三线一路”保护规划[R]. 武汉:2012年.
	[Wuhan Municipal Water Affairs Authority,Wuhan Land Resources and Planning Bureau,Wuhan Gardens Bureau. Pro-tection plan of three lines one road directive about lake in the Wuhan's central urban area[R]. Wuhan:2012.]
[39]	Anderson S T,West S T.Open space,housing property values,and spatial context[J]. Regional Science Urban Economics,2006,36(6):773-789.
[40]	武汉市水务局. 2013年武汉市水资源公报[R]. 武汉:2013.
	[Wuhan Municipal Water Affairs Authority,Wuhan city water resources bulletin[R].Wuhan city water resources bulletin[R]. Wuhan:2013.]

	残差 Moran's I	p	AIC	R²	调整R²
GWR1	-0.02	<0.01	6 827.69	0.81	0.61
OLS1			6 982.25	0.39	0.37
GWR2	-0.07	<0.01	3 358.86	0.78	0.60
OLS2			3 423.49	0.45	0.40