Spatio-temporal changes in racial segregation and diversity in large US cities from 1990 to 2020: a visual data analysis

被引:0
|
作者
Anna Dmowska
Tomasz F. Stepinski
机构
[1] Adam Mickiewicz University,Institute of Geoecology and Geoinformation
[2] University of Cincinnati,Department of Geography and GIS, Space Informatics Lab
来源
关键词
Racial segregation; US Census data; Racial dynamics; Visual data analysis;
D O I
暂无
中图分类号
学科分类号
摘要
Urban populations in large US cities exhibit racial and ethnic diversity, yet they remain residentially segregated. The examination of temporal trends in segregation and diversity is crucial for sociologists and urban planners. In this study, we investigate the spatio-temporal changes in segregation and diversity across 61 major US cities, utilizing data from four US Censuses conducted between 1990 and 2020. Unlike previous studies, our approach relies on visual data analysis, enabling us to capture the overarching changes in racial coresidence during this period. We employ four distinct perspectives – geographical, temporal, groups evolution, and desegregation scale limit – to visualize and analyze the data. Geographical analysis uncovers a decrease in regional disparities in urban diversity and segregation since 1990, as urban racial integration extends beyond West Coast and Southwestern cities to encompass the entire US. Through temporal analysis, we observe a general trend of rapidly increasing diversity and gradual reduction in segregation, albeit with varying rates across different cities. Groups evolution analysis reveals that cities grouped based on their diversity and segregation metrics in 1990 follow the overall trend toward larger diversity and smaller segregation while preserving group’s coherence but not their distinctiveness. Finally, the desegregation scale limit perspective suggests that, on average, over the 1990 to 2020 period, the desegregation scale has started to subceed the lower limit of the census block. By employing these diverse analytical perspectives, our study provides a comprehensive understanding of the changes in racial segregation and diversity within US cities over the past three decades.
引用
收藏
相关论文
共 50 条
  • [1] Spatio-temporal changes in racial segregation and diversity in large US cities from 1990 to 2020: a visual data analysis
    Dmowska, Anna
    Stepinski, Tomasz F.
    EPJ DATA SCIENCE, 2023, 12 (01)
  • [2] Spatio-temporal changes in heat waves and cold spells: an analysis of 55 US cities
    Allen, Michael J.
    Sheridan, Scott C.
    PHYSICAL GEOGRAPHY, 2016, 37 (3-4) : 189 - 209
  • [3] Smoking, Ethnic Residential Segregation, and Ethnic Diversity: A Spatio-temporal Analysis
    Moon, Graham
    Pearce, Jamie
    Barnett, Ross
    ANNALS OF THE ASSOCIATION OF AMERICAN GEOGRAPHERS, 2012, 102 (05) : 912 - 921
  • [4] Mapping and Spatio-temporal Changes Analysis of Energy Mining and Producing Sites in China Using Multi-source Data from 1990 to 2020
    Guo C.
    Chi W.
    Kuang W.
    Dou Y.
    Fu S.
    Lei M.
    Journal of Geo-Information Science, 2022, 24 (01): : 127 - 140
  • [5] Spatio-Temporal Analysis of Large Air Pollution Data
    Bin Tarek, Mirza Farhan
    Asaduzzaman, Md
    Patwary, Mohammad
    2018 10TH INTERNATIONAL CONFERENCE ON ELECTRICAL AND COMPUTER ENGINEERING (ICECE), 2018, : 221 - 224
  • [6] SPATIO-TEMPORAL ANALYSIS OF CROPLAND CHANGES IN US IN THE LAST DECADE
    Singh, Nagendra
    2013 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2013, : 2817 - 2820
  • [7] Spatio-temporal analysis of road traffic accidents in Indian large cities
    Mahata, Dinabandhu
    Narzary, Pralip Kumar
    Govil, Dipti
    CLINICAL EPIDEMIOLOGY AND GLOBAL HEALTH, 2019, 7 (04): : 586 - 591
  • [8] Visual cluttering reduction for visualizing large spatio-temporal data sets
    Shrestha, Ayush
    Zhu, Ying
    Zhu, Yan
    2014 IEEE 17TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE AND ENGINEERING (CSE), 2014, : 137 - 143
  • [9] Visual Analysis of Spatio-Temporal Data: Applications in Weather Forecasting
    Diehl, A.
    Pelorosso, L.
    Delrieux, C.
    Saulo, C.
    Ruiz, J.
    Groeller, M. E.
    Bruckner, S.
    COMPUTER GRAPHICS FORUM, 2015, 34 (03) : 381 - 390
  • [10] Scalable Semiparametric Spatio-temporal Regression for Large Data Analysis
    Ma, Ting Fung
    Wang, Fangfang
    Zhu, Jun
    Ives, Anthony R.
    Lewinska, Katarzyna E.
    JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS, 2023, 28 (02) : 279 - 298