RESEARCH ARTICLE


Population vs. Intersection Densities: An Assessment of a Correlation Using Spatial Comparison and Regression Analysis in Yaoundé, Cameroon



Edouard Bengono Essola1, Chunho Yeom2, *
1 International School of Urban Science, University of Seoul, Seoul 02504, Korea
2 International School of Urban Science, University of Seoul, Law School, 517, Seoulsiripdaero 163, Dongdaemun-gu, Seoul 02504, Korea


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Creative Commons License
© 2022 Essola

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at the International School of Urban Science, University of Seoul, Law School, 517, Seoulsiripdaero 163, Dongdaemun-gu, Seoul 02504, Korea; E-mail: chunhoy7@uos.ac.kr


Abstract

Background:

Intersection density is associated with block size and positively affects pedestrian volume.

Objective:

This study aimed to show that intersection density and population match across Yaoundé using spatial comparison and regression analysis.

Methods:

For spatial comparison, the mean values of the variables (intersection and population densities) were computed for each administrative subdivision in Yaoundé. The results are reported in a table representing Yaoundé and how the subdivisions share boundaries. For comparison, a table was created for each variable. Simple linear regression with a confidence level of 95% was used for regression analysis.

Results:

Spatial analysis revealed that the pattern of population density was similar to that of intersection density. However, this was disturbed by the proximity to the central business district (CBD). Regression analysis demonstrated that both variables moderately covariate with the influence of CBD. When assuming a weak influence of CBD, they are strong covariates. Statistically, in both cases, the correlation between population and intersection densities did not occur randomly (small p-values).

Conclusion:

The results imply that intersection density is a strong lever that influences citizen behavior. Future planning policies in Yaoundé should consider increasing intersection density in the most crowded areas. It will contribute to the better management of high pedestrian flows in these areas.

Keywords: Population density, Intersection density, Spatial comparison, Regression analysis, Central business district, Vector analysis.