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Take a Look Around: Using Street View and Satellite Images to Estimate House Prices

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  • Stephen Law
  • Brooks Paige
  • Chris Russell

Abstract

When an individual purchases a home, they simultaneously purchase its structural features, its accessibility to work, and the neighborhood amenities. Some amenities, such as air quality, are measurable whilst others, such as the prestige or the visual impression of a neighborhood, are difficult to quantify. Despite the well-known impacts intangible housing features have on house prices, limited attention has been given to systematically quantifying these difficult to measure amenities. Two issues have lead to this neglect. Not only do few quantitative methods exist that can measure the urban environment, but that the collection of such data is both costly and subjective. We show that street image and satellite image data can capture these urban qualities and improve the estimation of house prices. We propose a pipeline that uses a deep neural network model to automatically extract visual features from images to estimate house prices in London, UK. We make use of traditional housing features such as age, size and accessibility as well as visual features from Google Street View images and Bing aerial images in estimating the house price model. We find encouraging results where learning to characterize the urban quality of a neighborhood improves house price prediction, even when generalizing to previously unseen London boroughs. We explore the use of non-linear vs. linear methods to fuse these cues with conventional models of house pricing, and show how the interpretability of linear models allows us to directly extract the visual desirability of neighborhoods as proxy variables that are both of interest in their own right, and could be used as inputs to other econometric methods. This is particularly valuable as once the network has been trained with the training data, it can be applied elsewhere, allowing us to generate vivid dense maps of the desirability of London streets.

Suggested Citation

  • Stephen Law & Brooks Paige & Chris Russell, 2018. "Take a Look Around: Using Street View and Satellite Images to Estimate House Prices," Papers 1807.07155, arXiv.org.
  • Handle: RePEc:arx:papers:1807.07155
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    References listed on IDEAS

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    1. Gibbons, Steve & Machin, Stephen, 2003. "Valuing English primary schools," Journal of Urban Economics, Elsevier, vol. 53(2), pages 197-219, March.
    2. Rosen, Sherwin, 1974. "Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition," Journal of Political Economy, University of Chicago Press, vol. 82(1), pages 34-55, Jan.-Feb..
    3. Cheshire, Paul & Sheppard, Stephen, 1995. "On the Price of Land and the Value of Amenities," Economica, London School of Economics and Political Science, vol. 62(246), pages 247-267, May.
    4. Palmquist, Raymond B, 1984. "Estimating the Demand for the Characteristics of Housing," The Review of Economics and Statistics, MIT Press, vol. 66(3), pages 394-404, August.
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