There is an emerging consensus that improvements in the planning and design of the urban environment, such as the increase in urban green space provision, have capitalised into the intrinsic value of housing. Understanding how green space intervention increase the value of housing is essential both economically (since housing is usually the largest financial asset of resident owners and affects local businesses, consumption and activity vibrancy) and socially (since this can help deprived neighbourhoods improve public health, the living environment and quality of life). However, existing studies have largely failed to distinguish the effects of different types of urban green space on housing value.

This dissertation aims to understand and quantify the associations between different urban greenery metrics on the one hand and the levels and changes in housing prices on the other, using the mid-ring area in Shanghai, China. A unique feature of this dissertation is that it studies four types of urban green space metrics: they are the extent of visible urban green space as measured by the area percentages of street view pictures around each residential estate, the rate of green space coverage within each residential estate, the average percentage of land area in and around each residential estate in terms of the Normalised Difference Vegetation Index (NDVI), a standard measurement of land cover for satellite pictures, and the distance from each estate to the nearest park.

As hypothesised, different aspects of urban green space appear to play important and distinctive roles in influencing housing price, and the specific influence on price levels is different from those on price changes over time. In terms of the housing price levels of 2018 and 2021, street view greenery level, green space coverage within estate, and distance to nearest parks are all shown to be significant positive influences, with the street view greenery being the most significant. By comparison, NDVI is shown to be a relatively poor predictor for the price levels of a specific year, given it was not significant in 2018. For price changes over time, results show that NDVI and green space coverage within the estate positively affect housing prices.

The analyses confirm that different aspects of green space tend to have significant but distinctive influences on housing prices. The findings of this dissertation also suggest that it would be necessary for future studies to include all the metrics above, rather than the convention to use only one indicator.

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How to cite:

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Dongsheng He, (2021) The influence of different types of urban green space on housing price: A study of the mid-ring area in Shanghai. MPhil in Architecture and Urban Studies Dissertation, University of Cambridge