The Japanese city presents a certain number of peculiarities in the organization of its physical space (weak zoning regulations, fast piecemeal destruction/reconstruction of buildings and blocks, high compacity, incremental reorganization). Compared to countries where urban fabrics are more perennial and easily distinguishable (old centers, modern planned projects, residential areas, etc.), in Japanese metropolitan areas we often observe higher heterogeneity and more complex spatial patterns. Even within such a model, it should be possible to recognize the internal organization of the physical city. The aim of this paper is thus to study the spatial structure of the contemporary Japanese city, generalizing on the case study of Osaka and Kobe. In order to achieve this goal, we will need to identify urban forms at different local scales (building types, urban fabrics) and to analyze them at a wider scale to delineate morphological regions and their structuring of the overall layout of the contemporary Japanese city. Several analytical protocols are used together with field observations and literature. The results, and more particularly the building and urban fabric types and their location within the Osaka-Kobe metropolitan area, are interpreted in the light of Japanese history and model of urbanization. A synoptic graphical model of an urban morphological structure based upon Osaka is produced and proposed as an interpretative pattern for the Japanese metropolitan city in general.

Urban–rural differences seem particularly pronounced in India, especially when based on the official figures provided by the Census of India, which are heavily dependent on the administrative status of settlements. India, one of the world’s most dynamic and populous countries, still possesses an official urbanisation rate lagging well behind other developing economies. To investigate the extent of Indian urbanisation, this article develops a multi-step methodology using indicators specifically conceived for identifying urban structures in India. In this article, an emphasis is given to the conception and to the spatial analysis of two indicators: metropolitan ranking and meta-agglomerations. A method combining these indicators then allows identifying urban macro-structures acting as a larger organising framework in the regional space. Our results show a multitude of different functional areas that have developed specific urban morphologies over time. Some are particularly marked by high values of urban macrocephaly, small settlements taking the shape of nebulae, urban sprawl, etc.

This paper compares Hierarchical Clustering, Bayesian Networks and Self-Organizing Map Neural Networks (SOM and superSOM) approaches used for clustering purposes in geographic space. The same dataset, covering the Republic of India and made of 55 indicators for 640 spatial units (administrative districts), is used in the three analyses. Indicators descry the several aspects of urban, economic and socio-demographic development in India. Bayesian Networks use a likelihood function while SOM/SuperSOM and Hierarchical Clustering minimize variance of Euclidean distance in variable space, the former by preserving the topological properties within the output space and the latter by successively combining similar items. Relatively similar multi-step protocols have been implemented for the three techniques, to take into account variable redundancy. Methods as well as clustering results are compared. From this perspective, the aim of the paper is to highlight the similarities between the protocols and to evaluate the differences between the segmentation approaches (geographical and variable space comparisons). A few key points are also discussed such as the data pre-processing steps, the conception of latent factors and the choice of the number of clusters.

According to the Japanese government, vacant lots are randomly generated and accumulated (without being rebuilt after demolition) in the process of increasing vacant lots, a phenomenon called urban perforation. Urban perforation in urban areas may trigger a high degree of inefficiency in public infrastructure management. However, this observation lacks theoretical and empirical foundations, a lacuna to which this paper will focus on. Consequently, our research objectives are to confirm: (1) whether or not vacant lots are randomly generated and (2) whether or not vacant lots are randomly accumulated as a result of random generation. The methodology includes a consistent and bottom-up approach to delineate urban areas (alongside statistical spatial analysis). Through theoretical and empirical analyses in Chiba Prefecture (situated in the eastern part of the Tokyo metropolitan region), we find that the random generation of vacant lots does not tend to continue in the same urban areas. Rather, in most urban areas, this process is a temporary phenomenon. Subsequently, phase transition generally shifts from random to clustered generation or vice versa. Nevertheless, once vacant lots are randomly accumulated in an urban area, this process tends to continue. The contributions of this article are not only to provide important spatiotemporal findings regarding the generation and accumulation patterns of vacant lots, but also to discuss how to apply policy for urban perforation where phenomena are significantly pronounced.