Using Zillow Data To Value Green Space Amenities At The Neighborhood Scale

URBAN FORESTRY & URBAN GREENING(2020)

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摘要
It is important to quantify the value of green space amenities in order to justify the cost of their creation and maintenance; furthermore, advances in available data and methods have produced exciting ways to measure the economic values of green infrastructure. In this study, we use publicly available data from Zillow, Inc. to implement the hedonic pricing method at a novel scope and scale. We analyze over 5000 Zillow neighborhoods located in metropolitan areas across 44 states to identify the marginal value of urban green spaces with respect to median neighborhood home prices. By incorporating a vast, heterogeneous study area, we are able to gain a national-scale perspective on the effects of green spaces on home values. Furthermore, Zillow neighborhoods permit reproducible, extensible, and policy-relevant insight into the effects of green spaces on neighborhoods holistically. Our results suggest that for Zillow neighborhoods on average the normalized difference vegetation index (NDVI) and open space are dis-amenities; however, parks and tree cover add premiums to Zillow neighborhood value. By interacting tree cover with land surface temperature, we find the amenity value of trees is realized in part through shading; furthermore, we find that tree-shading has a greater amenity value in higher income areas.
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关键词
Environmental justice, Green space, Hedonic pricing method, Remote sensing, Urban green infrastructure, Zillow
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