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Measuring the pace and spatial distribution of gentrification is important to developing policies to mitigate its negative consequences. Typically, this is done through an analysis of census data on demographic, socioeconomic or housing change. However, this approach has numerous shortcomings, including the homogenizing effect on differences within neighbourhoods and the infrequency of census data collection. Visual analysis, particularly when examining multiple temporal views of the same location, has the potential to render visible fine-grained detail about spatial, economic and cultural changes within the urban landscape. Google Street View (GSV) is emerging as a source of repeat photography data. In this article, we employ a GSV analysis within a number of neighbourhoods in Hamilton, Ontario. Coding and analysing GSV images between 2009 and 2021 reveals an array of specific home upgrades, as well as aesthetic changes that reflect middle-class tastes, values and lifestyles that suggest more upgrading than found within conventional statistics or dominant narratives about the city. Mapping these changes paints a complex, and fine-grained, block-by-block picture of gentrification that reveals why some areas are more conducive to gentrification than others. Our analysis is important for critical visual methodologies, theoretical discussions about gentrification and neighbourhood change theories and debates within planning and policymaking.
Babin et al. (Mon,) studied this question.