The neighborhood is the central analytical entry point into a wide range of research topics, but it is an open question as to what defines a neighborhood. Most quantitative neighborhood classification methods are based on the assumption that neighborhoods are composed of places with similar spatial and socioeconomic characteristics. While this assumption is both convenient and valuable in neighborhood classification, it tends to overlook critical features of lived experience, particularly human activities such as migration. This paper examines neighborhood classification through the lens of migration patterns in the Twin Cities Metropolitan Area of Minnesota. This study uses a parcel dataset to derive a near complete depiction of intraurban migration, which is then coupled to a new combination of methods informed by migration concepts to construct and analyze neighborhood structure. The results of this approach illustrate the value of combining data, method, and theory of human migration in neighborhood classification.

Neighborhood intraurban migration urban segmentation parcel data

metropolitan area segmentation quantitative analysis Minnesota neighborhood urban geography United States socioeconomic conditions migration spatial analysis