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Updated: Feb 20, 2026

Monitoring Spatial Segregation in Surface Colonizing Microbial Populations
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Structure and information in spatial segregation.

Philip S Chodrow1,2,3

  • 1Operations Research Center, Massachusetts Institute of Technology, Cambridge, MA 02139; pchodrow@mit.edu.

Proceedings of the National Academy of Sciences of the United States of America
|October 29, 2017
PubMed
Summary

New information theory methods reveal complex patterns in ethnoracial residential segregation. These tools offer detailed insights into urban segregation dynamics for sociology and urban planning, improving spatial analysis.

Keywords:
diversityinformation theorymachine learningmultiscale analysissegregation

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Area of Science:

  • Sociology
  • Urban Planning
  • Spatial Analysis

Background:

  • Ethnoracial residential segregation presents significant social and economic challenges.
  • Existing methods for modeling segregation have notable limitations in capturing its complexity.

Purpose of the Study:

  • To develop novel, information theory-based methods for analyzing the spatial structure of segregation.
  • To advance existing regionalization and decomposition techniques for segregation studies.

Main Methods:

  • Developed new regionalization methods enabling analysis of segregation at nonconstant spatial scales.
  • Formulated a measure of local spatial scale for detailed within-city and intercity comparisons.
  • Utilized information theory to create a suite of computationally efficient segregation analysis tools.

Main Results:

  • The new methods provide detailed insights into urban segregation structures often missed by traditional approaches.
  • The techniques allow for segregation decomposition using nonarbitrary areal units.
  • A measure of local spatial scale facilitates nuanced spatial analysis.

Conclusions:

  • The developed information theory methods offer a powerful and flexible approach to studying ethnoracial residential segregation.
  • These tools enhance the quantitative analysis of segregation's spatial dynamics.
  • The open-source availability of these methods promotes broader application in research and planning.