Abstract
Urban commercial facilities significantly influence neighborhood residents, with changes like store closures disrupting their routines. Especially for the elderly, proximity to these facilities is crucial. Although introducing well-known brands can rejuvenate areas, they might also lead to overcrowding, potentially diminishing the quality of life for locals. It is imperative in urban planning to understand these dynamics and their implications. This chapter delves into the formation of commercial clusters in urban zones and introduces techniques for analyzing and visualizing these trends. Utilizing data from Shibuya Ward, Tokyo, the study demonstrates the efficacy of these methods. The analysis focuses on the expansion direction of commercial clusters using spatiotemporal point data. By tracking when each store opened, the research identifies how new establishments influence the growth trajectory of existing commercial conglomerates. Using a circular statistical method, the study visualizes the expansion of commercial clusters.
This contents of this paper are based on the following papers originally published in a Japanese journal:
Inasaka, A. and Sadahiro, Y. (2010): A Method of Analysis and Visualization of Expanding Direction of Retail Distribution, Transactions of AIJ, Journal of Architecture Planning and Environmental Engineering, Vol.75, No. 650, pp.889–896 (in Japanese).
Inasaka, A. (2013): Visualization of Expanding Direction Pattern of Retail Distribution using High Resolution Spatiotemporal Data, The 36th Symposium on Computer Technology of Information, Systems and Application of Architectural Institute of Japan, pp.265–268 (in Japanese).
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Notes
- 1.
(Note 1) See Statistical Survey of Business Establishments and Enterprises 2004 (Tokyo Metropolitan Government, Table 20, Shibuya Ward). (http://www.stat.go.jp/data/jigyou/2004/)
- 2.
(Note 2) Sometimes referred to as directional statistics
This method has recently been attracting attention in computational statistics, such as Shimizu (2008)
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Inasaka, A. (2024). A Method of Visual Analytics and Data Visualization in Design Context: Case Study of Spatiotemporal Data Visualization of Urban Retail Agglomeration Growth. In: Asami, Y., Sadahiro, Y., Yamada, I., Hino, K. (eds) Studies in Housing and Urban Analysis in Japan. New Frontiers in Regional Science: Asian Perspectives, vol 75. Springer, Singapore. https://doi.org/10.1007/978-981-99-8027-7_13
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