Development of methods for detecting agglomerated area from spatial high resolution data with applications to urban and transportation fields

2017 Fiscal Year Final Research Report

• Project/Area Number: 26289169
• Research Category: Grant-in-Aid for Scientific Research (B)
• Allocation Type: Partial Multi-year Fund
• Section: 一般
• Research Field: Civil engineering project/Traffic engineering
• Research Institution: Tohoku University
• Principal Investigator: FUKUMOTO JUNYA 東北大学, 情報科学研究科, 准教授 (30323447)
• Co-Investigator(Kenkyū-buntansha): 井上 亮 東北大学, 工学(系)研究科(研究院), 准教授 (60401303)
• Research Collaborator: UJIIE AKIHITO
• Project Period (FY): 2014-04-01 – 2018-03-31
• Keywords: 集積領域検出 / 空間データ / モデルベースクラスタリング / 空間スキャン統計 / コミュニティ抽出法 / ランクサイズルール

Outline of Final Research Achievements

The objective of this research project is to develop various methods for detecting agglomerated area from spatial high resolution data, and to find spatial characteristics of spatial phenomenon by applying proposed methods to real urban and transportation data. First, we developed a method that can overcome the limitations of existing methods and detect flexible-shaped agglomerated area. Second, we developed a method that can find agglomerated area from time-space data. Third, we investigated the existence of rank-size rule in the spatial industrial agglomeration pattern, and investigated the spatial hierarchical pattern in the multiscale functional regions structures.

Free Research Field

土木計画学