Theory of Scale-Free Networks as a New Tool in Researching the Structure and Optimization of Spatial Planning

Biłozor, Andrzej; Kowalczyk, Anna; Bajerowski, Tomasz

doi:10.1061/(asce)up.1943-5444.0000424

Cited by 12 publications

(10 citation statements)

References 22 publications

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“…Uncovering spatial patterns of retail stores in street unit can address potential statistical issues induced by the area-based unit analysis. Thus, studies employing street networks play an important role in the evaluation of the retail industry aimed at sustainable development [45,46]. In this paper, we take Zhengzhou, a city in central China, as an example to analyze the distribution patterns of different types of retail stores by using the street as the analysis unit.…”

Section: Introductionmentioning

confidence: 99%

Identifying Spatial Patterns of Retail Stores in Road Network Structure

et al. 2019

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Understanding the spatial patterns of retail stores in urban areas contributes to effective urban planning and business administration. A variety of methods have been proposed in the scientific literature to identify the spatial patterns of retail stores. These methods invariably employ arbitrary grid cells or administrative units (e.g., census tracts) as the fundamental analysis units. As most urban retail stores are distributed along street networks, using area-based analysis units is subject to statistical biases and may obfuscate the spatial pattern to some extent. Using the street segment as the analysis unit, this paper derives the spatial patterns of retail stores by crawling points of interest (POI) data in Zhengzhou, a city in central China. Then, the paper performs the network-based kernel density estimation (NKDE) and employs several network metrics, including the global, local, and weighted closeness centrality. Additionally, the paper discusses the correlation between the NKDE value and the closeness centrality across different store types. Further analysis indicates that stores with a high correlation tend to be distributed in city centers and subnetwork centers. The comparison between NKDE and cell-based KDE shows that our proposed method can address potential statistical issues induced by the area-based unit analysis. Our finding can help stakeholders better understand the spatial patterns and trends of small business expansion in urban areas and provide strategies for sustainable planning and development.

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Section: Introductionmentioning

confidence: 99%

Identifying Spatial Patterns of Retail Stores in Road Network Structure

et al. 2019

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“…This preference may result from either the actions of the law of nature or decisions made by humans. Therefore, the preferences can be natural (spontaneous), for example, those which generate a hydrological network [30] or natural phenomena [31], an anthropogenic phenomena resulting from decisions made by humans, such as a network of scenic point connections [32], a transport connection network [33,34], a network of cooperation between cities [12], or networks of social relations [35,36]. For scale-free networks [26,29], the preferentiality of the selection of connections within a specific hierarchy lies in the fact that when a new node emerges, it tends to connect to existing nodes with an already large number of connections; this results in nodes with an increasing number of connections as opposed to their neighboring nodes with a smaller number of connections.…”

Section: Random Network Scale-free Networkmentioning

confidence: 99%

“…The developed theory is the result of several years of empirical research. In this way, values representing various phenomena and structures of urbanized areas can be modeled and analyzed, including earth crust movements, values representing the level of security, and the quality of landscape in the city [12,32,[40][41][42]. These spatial structure modeling operations are aimed at enabling active planning, development, and management of network structures while maintaining them at a stable level.…”

Section: Random Network Scale-free Networkmentioning

confidence: 99%

“…These are questions about the relationships between individual elements of a space. These relationships form a network of links, which result in an overall network-based organization of space; this has been proven and described by many authors [4][5][6][7][8][9][10][11][12]. During research into network structures over the course of many years, numerous algorithms were developed, including algorithms by Bellman-Ford [13], Johnson [14], Kruskal [15], and Dijkstra [16].…”

Section: Introductionmentioning

confidence: 99%

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Development of the Theory of Six Value Aggregation Paths in Network Modeling for Spatial Analyses

Kowalczyk¹,

Bajerowski²

2020

IJGI

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The dynamic development of spatial structures entails looking for new methods of spatial analysis. The aim of this article is to develop a new theory of space modeling of network structures according to six value aggregation paths: minimum and maximum value difference, minimum and maximum value decrease, and minimum and maximum value increase. The authors show how values presenting (describing) various phenomena or states in urban space can be designed as network structures. The dynamic development of spatial structures entails looking for new methods of spatial analysis. This study analyzes these networks in terms of their nature: random or scale-free. The results show that the paths of minimum and maximum value differences reveal one stage of the aggregation of those values. They generate many small network structures with a random nature. Next four value aggregation paths lead to the emergence of several levels of value aggregation and to the creation of scale-free hierarchical network structures. The models developed according to described theory present the quality of urban areas in various versions. The theory of six paths of value combination includes new measuring tools and methods which can impact quality of life and minimize costs of bad designs or space destructions. They are the proper tools for the sustainable development of urban areas.

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“…The identified factors also tend to have limited spatial coverage. Therefore, the use of the existing databases appears to be a much simpler and sensible solution [60].…”

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confidence: 99%

An Analysis of an Area’s Vulnerability to the Emergence of Land-Use Conflicts

Cieślak

Biłozor

2021

Land

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The optimization of space is the priority goal of spatial planning. Spatial planning policies have numerous objectives, including the prevention of land-use conflicts. Conflicts arise whenever two entities have contradictory expectations regarding the surrounding space. In the process of spatial development, humans impart new characteristics to space, which, under specific circumstances, can give rise to land-use conflict. The elements of space that are particularly vulnerable to conflict include boundary points, property boundaries, density of development, or the shared use of infrastructure. The main aim of this study was to develop a procedure for evaluating the risk of land-use conflict based on the characteristic attributes of space. The proposed procedure for assessing the accumulation of conflict-generating traits in space was developed with the use of databases, GIS tools, and statistical data processing methods.

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Theory of Scale-Free Networks as a New Tool in Researching the Structure and Optimization of Spatial Planning

Cited by 12 publications

References 22 publications

Identifying Spatial Patterns of Retail Stores in Road Network Structure

Identifying Spatial Patterns of Retail Stores in Road Network Structure

Development of the Theory of Six Value Aggregation Paths in Network Modeling for Spatial Analyses

An Analysis of an Area’s Vulnerability to the Emergence of Land-Use Conflicts

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