A bottom-up approach for delineating urban areas minimizing the connection cost of built clusters: Comparison with top-down-based densely inhabited districts. (September 2019)

• Record Type: Journal Article
• Authors: Usui, Hiroyuki
• Is Part Of: Computers, environment and urban systems. Volume 77(2019)
• Publication Date: 2019-09
• Subjects: Urban area -- Natural cities -- Building -- Nearest neighbour distance -- Optimization; City planning -- Data processing -- Periodicals; Regional planning -- Data processing -- Periodicals; 303.4834
• DOI: 10.1016/j.compenvurbsys.2019.101363
• Languages: English
• ISSNs: 0198-9715

Abstract

Abstract: The main purpose of my research is to propose a consistent and bottom-up-based approach for delineating present and future urban areas on the foundation of investigating the relationship between delineating urban areas and the connection cost of built clusters. In my approach, optimal urban built clusters are defined as the delineation of urban areas by grouping buildings that satisfy the following rules based on the head/tail division rule: (1) the nearest neighbour distance from a building centroid is shorter than the criterion that can minimize the average total cost to provide public infrastructure (road networks); and (2) the size of grouped buildings (called an urban built cluster) is equal to or more than the mean of urban built cluster sizes. In the literature, the difference between optimal urban built clusters and densely inhabited districts (DIDs), a top-down-based approach, has not been analysed in detail. In replacing a top-down approach (DIDs) with a bottom-up one (e.g., the method proposed in this article), this difference needs to be evaluated. Therefore, the difference between DIDs and optimal urban built clusters was investigated. For the empirical study, I have selected Chiba prefecture, in the east of the Tokyo metropolitan region. Results show that (1) the overlapping relations of urban built clusters and DIDs can be distinguished based on their hierarchical levels; and (2) 55% of DIDs are optimal urban built clusters. However, the size of optimal urban built clusters that are not intersected by DIDs is the same as that of those intersected by DIDs. This poses to urban planners the important question of how to deal with two types of zones: zones overlapping not DIDs but optimal urban built clusters, and zones overlapping not optimal urban built clusters but DIDs. Highlights: Buildings are more appropriate for delineating urban areas than census units (densely inhabited districts (DIDs)). A bottom-up approach for delineating optimal urban built clusters that minimizes their connection cost is proposed. The difference between DIDs and optimal urban built clusters based on their hierarchical levels is investigated. The size of optimal urban built clusters not being intersected by DIDs is the same as that of those intersected by DIDs.