This paper attempts to examine the impacts of the spatial structure of landscape on housing premiums in Austin, TX through the years of 2009–2011. Dissimilar to previous studies, this paper highlighted three points. First, landscape patterns was observed—not only the composition but also the configuration in terms of shape, fragmentation, isolation, and connectivity. Second, the definition of neighborhood in this study was closely matched to the nature of a residential neighborhood, which was represented by a residential subdivision that has a name and a high level of homogeneous characteristics (i.e., development age, appraised value, lot size, and housing size). This approach specifically helps understand the impact of landscape configuration at the micro-level neighborhoods. Third, the hierarchical nature of neighborhoods and embedded parcels—nested parcels within the same neighborhood posit a certain level of identity as a whole—was given attention so that multi-level modeling could be employed. Conceptually and theoretically, multi-level modeling is a better approach to examine phenomenon that occur in multi-level units that show a clear hierarchy. The findings indicated that home buyers are willing to pay more to live in neighborhoods with the high ratio of tree cover. This is a finding consistent with previous studies. Meanwhile, the detailed spatial configuration of landscape does not play an important role at the residential neighborhood level. This result urges policy makers to be more scale-sensitive when planning landscape and indicates that micro neighborhoods are not the correct spatial level to discuss the spatial configuration of landscape, greenways, and green network.
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