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Strengthening the Statistical Summaries of Economic Output Areas for Urban Planning Support Systems

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  • Chul Sue Hwang

    (Department of Geography, Kyung Hee University, Dongdaemun-Gu, Seoul 02447, Korea)

  • Seong-Yun Hong

    (Department of Geography, Kyung Hee University, Dongdaemun-Gu, Seoul 02447, Korea)

  • TaeKeon Hwang

    (Department of Geography, Kyung Hee University, Dongdaemun-Gu, Seoul 02447, Korea)

  • Byungyun Yang

    (Department of Geography Education, Dongguk University, Jung-gu, Seoul 04620, Korea)

Abstract

Despite efforts to research the transformation of urban structures, difficulties remain in estimating credible statistical information in the existing census output areas. This research proposes two alternatives to construct new economic output areas by considering the socioeconomic homogeneities where economic activities occur. In particular, we developed an algorithm to aggregate new economic zones into the existing census output areas. For this purpose, we utilized matrix systems that consider population sizes, the number of workers and workplaces, and a combination of these factors in the two alternatives. Urban planners need to provide credible statistical summaries at the census output areas. Our findings contribute to this research by suggesting that it is essential to consider the population and the number of workplaces with socioeconomic homogeneity. These findings will also help other researchers who study the transformation of urban structures because they can use more reliable statistical information for their simulation model that predicts an urban structure. Furthermore, it will help improve the national statistics office’s roles for public and urban planners and provide an important source for the national statistical geographic information services.

Suggested Citation

  • Chul Sue Hwang & Seong-Yun Hong & TaeKeon Hwang & Byungyun Yang, 2020. "Strengthening the Statistical Summaries of Economic Output Areas for Urban Planning Support Systems," Sustainability, MDPI, vol. 12(14), pages 1-21, July.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:14:p:5640-:d:383979
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    2. Byungyun Yang & Minjun Kim & Changkyu Lee & Suyeon Hwang & Jinmu Choi, 2022. "Developing an Automated Analytical Process for Disaster Response and Recovery in Communities Prone to Isolation," IJERPH, MDPI, vol. 19(21), pages 1-19, October.

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