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Visualizing demographic evolution using geographically inconsistent census data

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  • Dias, Fabio
  • Silver, Daniel

Abstract

Video Abstract: https://youtu.be/bKeV08Os0uA Census measurements provide reliable demographic data going back centuries. However, their analysis is often hampered by the lack of geographical consistency across time. We propose a visual analytics system that enables the exploration of geographically inconsistent data. Our method also includes incremental developments in the representation, clustering, and visual exploration of census data, allowing an easier understanding of the demographic groups present in a city and their evolution over time. We present the feedback of experts in urban sciences and sociology, along with illustrative scenarios in the USA and Canada.

Suggested Citation

  • Dias, Fabio & Silver, Daniel, 2018. "Visualizing demographic evolution using geographically inconsistent census data," SocArXiv a3gtd, Center for Open Science.
    • Handle: RePEc:osf:socarx:a3gtd
    DOI: 10.31219/osf.io/a3gtd
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    References listed on IDEAS

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    1. Gotway C.A. & Young L.J., 2002. "Combining Incompatible Spatial Data," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 632-648, June.
    2. Elizabeth C. Delmelle, 2016. "Mapping the DNA of Urban Neighborhoods: Clustering Longitudinal Sequences of Neighborhood Socioeconomic Change," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 106(1), pages 36-56, January.
    3. Glenn Firebaugh & Chad R. Farrell, 2016. "Still Large, but Narrowing: The Sizable Decline in Racial Neighborhood Inequality in Metropolitan America, 1980–2010," Demography, Springer;Population Association of America (PAA), vol. 53(1), pages 139-164, February.
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    Cited by:

    1. Matheus Pereira Libório & Oseias da Silva Martinuci & Alexei Manso Correa Machado & Renata de Mello Lyrio & Patrícia Bernardes, 2022. "Time–Space Analysis of Multidimensional Phenomena: A Composite Indicator of Social Exclusion Through k-Means," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 159(2), pages 569-591, January.

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