Distribution Of Urban Facilities Research Articles

Identifying Relationship between Regional Centrality and POI Facilities: A Case Study of Seoul Metropolitan Area

While understanding the dynamic urban network through the concept of regional centrality has provided various implications on the structure and hierarchy of cities, the macroscopic focus of previous studies has largely overlooked the small-scale physical and social urban entities in central places. Meanwhile, recent advances in real-time Point-of-Interest (POI) data have quickly replaced much of traditional urban facility data, emerging as a new representation of urban activities and demands. Therefore, this study proposes a method to identify the relationship between regional centrality and the distribution of POI facilities, particularly focused on the Seoul metropolitan area of South Korea. To this end, this study conducts a correlation analysis between regional centrality results derived from social network analysis and POI indices obtained from POI distribution analysis. The results indicate that a statistically significant relationship exists between regional centrality and the distribution of urban facilities, with a particularly strong correlation exhibited in specific POI categories. The results also demonstrate the effectiveness of the method in capturing disparities in the provision of facilities concerning growing commuting centers. The findings of the study provide pragmatic implications for prioritization and planning of facility development, as well as making informed decisions in real estate and facility investment.

DAMPAK URBANISASI BAGI PERKEMBANGAN KOTA DI INDONESIA

This paper discusses the impact of urbanization posed by the rapidly developing city. Urbanization is the result of urban development and economic which ultimately affect the dynamics of the city, especially in contact with the city's ability as an attraction for people to work and live. The impact of urban development is first, physical: land vs land up green, the distribution of urban facilities, transportation networks, patterns of movement to the city center, the development of land use, environmental issues, and slums. Second, socially; unemployment, poverty, and criminalitas.

A Network-Based Spatial Analytical Method for Detecting Agglomerations in a Point Distribution on a Network and Its Implementation

Many kinds of phenomena, including traffic accidents, road kills of wild animals and distribution of urban facilities, occur on a network. To analyze their spatial patterns, this paper proposes a new spatial analytical method, called NT-VCM (Network Variable Clumping Method), as an extension of Variable Clumping Method on a plane, which we developed earlier and named PLN-VCM (Planar Variable Clumping Method). The major function of NT-VCM is to statistically detect significant multi-level network clumps in the distribution of points on a network using Monte Carlo simulations. Applying NT-VCM and PLN-VCM to the same data set, this paper shows that NT-VCM preserves connectivity of points on a network better than PLN-VCM.