[Updated on Apr. 18] Integration of CiNii Articles into CiNii Research


DOI Web Site Open Access

Bibliographic Information

Other Title
  • 相対的な人口集中地区の抽出を通じた全国市町村の都市縮小傾向の分析
  • 相対的な人口集中地区の抽出を通じた全国市町村の都市縮小傾向の分析 : 人口減少時代を迎えるわが国の都市圏の形態変化に関する研究(その2)
  • ソウタイテキ ナ ジンコウ シュウチュウ チク ノ チュウシュツ オ ツウジタ ゼンコク シチョウソン ノ トシ シュクショウ ケイコウ ノ ブンセキ : ジンコウ ゲンショウ ジダイ オ ムカエル ワガクニ ノ トシケン ノ ケイタイ ヘンカ ニ カンスル ケンキュウ(ソノ 2)
  • -Urban form changes of Japanese cities in an era of shrinking population part 2-
  • -人口減少時代を迎えるわが国の都市圏の形態変化に関する研究(その2)-

Search this article


<p> To grasp the actual situations of urban shrinkage dispassionately is considered important for the urban planning in an era of shrinking population in Japan. For analyzing method of the urban shrinkage and urban structure changing in an era of shrinking population, Densely Inhabited District (DID) has been applied in some past studies as an index of urban area. As an issue of this method, shrinkage or urban structure change in the cities where no DID exist or the whole area is DID can’t be analyzed.</p><p> In the previous paper, we identified Relative Densely Inhabited District (RDID) in whole Japanese cities as the relative population centers which are detected by an urban form analyzing method “Polycentricity” proposed in Amindarbari et al. (2013). the RDID identified in the previous paper is detected by relative density level and population level of each cities, therefore It can be detected in the cities where no DID exist and analyzing the city shrinkage with RDID shrinking as an index. However, the method of setting a density level for RDID in the previous paper tends to overestimate the density level at a large city. Although this setting method can be adjusted by decreasing a parameter to avoid overestimating, the density level with a decreased parameter tends to be underestimated at small cities.</p><p> In this paper, we improved the detecting method of RDID applying “Information Loss Minimization” proposed by Osaragi (2003). Applying this method of “Information Loss Minimization” to the setting of density threshold, It is expected that more appropriately RDID criterion can be decided in the sense that the information loss which occurs in classification of density data of the target city becomes the minimum. Furthermore, we identified the urban shrinkage or structure changes in Japanese cities and analyzed the changing those trends from 1995 to 2015 with the RDID applied “Information Loss Minimization” in this paper. The main findings are summarized as follows:</p><p> 1. With regard to the urban structure, the trends of centralization became stronger. On the other hand, cities where density decreasing in whole area and population weight increasing in center area occurred at the same time tend to have a large proportion in each population size group.</p><p> 2. The number of cities where the RDID area shrank under population decline is increasing in each population size group in each period from 1995 to 2015. Those cities accounted for about 72% of all Japanese cities in the period of 2010 to 2015. This trend can be confirmed in the group of larger cities which the number of cities where the RDID area expanded under population growth was occupied the majority among larger cities in the period of 1995 to 2000.</p><p> 3. It was suggested that the number of cities where the RDID shrinkage occur at the central location was increased after the period of 2000 to 2005.</p>


Citations (0)*help

See more


See more

Related Articles

See more

Related Data

See more

Related Books

See more

Related Dissertations

See more

Related Projects

See more

Related Products

See more


Report a problem

Back to top