Impacts Of The Urban Landscape On The Housing Price

Beautiful landscapes give people sense of pleasure and freshness which is beneficial to people’s health. With continuous development of the socio-economic and increasing improvement in people’s living standards, residents are paying more attention to the quality of the living environment. As public properties, urban landscapes have the features of scarcity and location particularity. The closer the residents live to these properties, the more public welfare they benefit. It’s directly reflected in higher housing prices. On the other hand, the value of urban landscape is recessive and except the land using, maintenance is also necessary from the government for the landscape. Compared to real estate development, plant construction, and other land using patterns, it’s difficult to measure the economic benefit directly in currency. So the importance of the urban landscape is often neglected and lead to a Public financial loss. This paper attempts to explore the impact of urban landscape on housing price from levels of housing and residential community. What’s more, the spatial autocorrelation effect of housing price in Hangzhou is also analyzed in this paper. The main work and conclusions of this paper are as follows:(1)In this paper, the Hedonic price method and related improvements are introduced and summarized, and its applications in the field of environmental evaluation are thoroughly discussed. Based on the previous studies, the variables are set and selected. This paper takes Hangzhou as example, districts of Xihu, Gongshu, Shangcheng, Xiacheng, Jianggan and Binjiang are selected as study cases. Residential data including3400housing and660communities is collected. Then four methods are used to code and quantify the sample data.(2)There are several patterns of landscape in Hangzhou, such as lake, mountain, river and park etc. A detailed description and analysis of Hangzhou’s landscape and pattern distribution is presented and a contour map of housing price in Hangzhou is drawn in this paper.(3) Then Hedonic price model is built based on the samples and analysis of landscapes’impact on housing prices is conducted. The empirical result shows that there is an inverse relationship between the housing price and its distance from West Lake and the park while the park size is positively correlated to the house price, and there will be a premium of the house price when it has beautiful landscape views. We also get a result that the distance of impacts of the West Lake on housing price is about4.59kilometers and the distance of impacts of the Qiantang River on housing price is about0.8kilometers.(4)The spatial autocorrelation effect of housing price in Hangzhou is explored in this paper. The result indicates that there is certain spatial correlation in the spatial distribution of Hangzhou housing price, so it’s necessary to consider the impact of spatial autocorrelation effect when conduct hedonic price model. And the empirical result shows that spatial hedonic model is more effective and robust compared to the traditional hedonic price model. In addition, the impact of landscape on housing values is overestimated due to the factor of missing variables and space-dependent. To avoid this circumstance and improve the empirical effect, the spatial econometrics model is required.