Strengthening the Statistical Summaries of Economic Output Areas for Urban Planning Support Systems
| Autor: | Taekeon Hwang, Byungyun Yang, Seong-Yun Hong, Chul-sue Hwang |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Geography
Planning and Development Population lcsh:TJ807-830 0211 other engineering and technologies 0507 social and economic geography lcsh:Renewable energy sources 02 engineering and technology Management Monitoring Policy and Law national statistics urban planning Urban planning education Socioeconomic status Environmental planning lcsh:Environmental sciences lcsh:GE1-350 education.field_of_study Renewable Energy Sustainability and the Environment lcsh:Environmental effects of industries and plants 05 social sciences 021107 urban & regional planning Census GIS Geographic information services Urban structure Special economic zone lcsh:TD194-195 Support system Business 050703 geography census output areas |
| Zdroj: | Sustainability, Vol 12, Iss 5640, p 5640 (2020) Sustainability Volume 12 Issue 14 |
| ISSN: | 2071-1050 |
| Popis: | 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&rsquo s roles for public and urban planners and provide an important source for the national statistical geographic information services. |
| Databáze: | OpenAIRE |
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