Full Citation
Title: Improving the understanding of the US urban racial geography and its temporal change using the Racial Landscape method
Citation Type: Miscellaneous
Publication Year: 2023
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Abstract: Racial Landscape (RL) is an innovative methodology for studying racial geography that offers several advantages over current approaches. This paper aims to highlight two key features of RL that have the potential to significantly impact the discipline. Firstly, the RL approach introduces a fundamentally different method for assessing segregation compared to existing methods. We delve into this distinction and emphasize its benefits, such as the ability to calculate segregation for any arbitrary area without the need for subdivisions, diversity measures, reference regions, or reliance on census geography. Importantly, by utilizing data from 51 Metropolitan Statistical Areas (MSAs) across the US, we demonstrate that the RL's segregation metric produces comparable rankings of segregation among MSAs when compared to existing segregation indices. Thus, while the RL expands the scope of problems where segregation can be quantified, it remains compatible with current segregation assessment practices. Secondly, we utilize data from the core parts of four selected MSAs in 1990 and 2020 to showcase how high-resolution RL-based racial maps can be employed for spatially explicit visual analyses of racial change. We discuss the potential impact of RL on the field, particularly in relation to segregation assessment and the evaluation of spatially explicit models of racial dynamics. While initially developed for analyzing racial geography in the United States, the RL framework can be extended to other countries as well.
Url: https://osf.io/preprints/socarxiv/46hfa/
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Authors: Dmowska, Anna; Stepinski, Tomasz
Publisher: SocArXiv
Data Collections: IPUMS NHGIS
Topics: Land Use/Urban Organization, Population Mobility and Spatial Demography, Race and Ethnicity
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