Using High-Resolution Population Data to Identify Neighborhoods and Establish Their Boundaries

Neighborhoods are about local territory, but what territory? This paper offers one approach to this question through a novel application of "local" spatial statistics. We conceptualize a neighborhood in terms of both space and social composition; it is a contiguous territory defined by a bundle of social attributes that distinguish it from surrounding areas. Our method does not impose either a specific social characteristic or a predetermined spatial scale to define a neighborhood. Rather we infer neighborhoods from detailed information about individual residents and their locations. The analysis is based on geocoded complete-count census data from the late 19(th) Century in four cities: Albany, NY, Buffalo, NY, Cincinnati, OH, and Newark, NJ. We find striking regularities (and some anomalies) in the spatial structure of the cities studied. Our approach illustrates the "spatialization" of an important social scientific concept.