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Updated: Feb 20, 2026

Monitoring Spatial Segregation in Surface Colonizing Microbial Populations

Monitoring Spatial Segregation in Surface Colonizing Microbial Populations

Published on: October 29, 2016

Structure and information in spatial segregation.

Philip S Chodrow^1,2,3

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

Summary

This summary is machine-generated.

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:

diversity information theory machine learning multiscale analysis segregation

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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.