Modeling the geospatial dynamics of residential segregation in three Canadian cities: An agent‐based approach. Issue 2 (2nd December 2020) - Anderson, Taylor; Leung, Aaron; Dragicevic, Suzana; Perez, Liliana
Abstract: Long‐term residential segregation can exacerbate social inequality and exclusion in urban populations. Existing models of segregation aim to represent and better understand drivers of segregation and assess possible segregation effects in response to incoming immigrant populations. However, these studies are not typically implemented on real geospatial data to represent the urban environment, and even less frequently compare patterns of segregation between cities. Therefore, the objective of this study is to implement an agent‐based model that simulates the decision‐making process of immigrants as they arrive and settle in three Canadian gateways for immigration, including the City of Toronto, the City of Calgary, and Metro Vancouver. The resulting simulated spatial patterns of segregation are visually compared to real data representing the location of hotspots of immigrants of various ethnic origins. The degree of segregation is measured and compared, with measures of segregation obtained from actual census data. The spatial patterns and degree of segregation are compared across the three study areas. The developed model has the potential to be used as a tool for knowledge discovery and decision‐making in the processes of city planning.