The Analysis of Networks Space Structures as Important Elements
of Sustainable Space Development

Kowalczyk, Anna

doi:10.3846/enviro.2017.107

Cited by 4 publications

(5 citation statements)

References 12 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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“…no centers in the network structure -the network is very sensitive to the deliberate exclusion of centers from the network structure an attack on several centers can lead to complete network disruption and structural dysfunction rarely appear in the real world -they characterize many spatial structures and are versatile in usage Source: Own analysis based on [6,28,39].…”

Section: Random Network Scale-free Networkmentioning

confidence: 99%

“…This theory appears to be a good tool for an integrated approach to sustainable urban development because of its wide approach to data modeling and to studying and measuring the quality of urban space. According to the idea of sustainable development, aspiring to fulfill human needs as well as improving the living conditions of the population cannot lead to the degradation and disturbance of the state of equilibrium in nature [28]. In order to ensure optimal spatial management, in accordance with the principles of sustainable development, this space should be analyzed adeptly.…”

Section: Random Network Scale-free Networkmentioning

confidence: 99%

“…Many constructions of networks were also described, including classical random graphs by Erdos and Renyi [17,18], equilibrium random graphs with a given degree distribution [19][20][21][22][23], 'small-world networks' [24], and networks growing under the mechanism of preferential linking [25]. Accordingly, in order for a network to exist and operate it must be comprised of two elements: nodes and the connections between them [26][27][28]. These connections may either be physical or result from other relationships.…”

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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“…Source: Own analysis based on (Kowalczyk, 2017;Barabasi, 2002). Table 2 The general characteristics of random networks and scale-free networks.…”

Section: Random Network Scale-free Networkmentioning

confidence: 99%

Identification of pseudo-nodal points on the basis precise leveling campaigns data and GNSS

Bednarczyk¹

2017

Acta Geodynamica Et Geomaterialia

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Four precise leveling campaigns has been carried out in Poland, and for several years there is a functioning system of permanent GNSS stations determining the height of network points. On the basis of these data, several variants of vertical crustal movements models have been developed (Wyrzykowski, 1987;Kowalczyk, 2005;Kontny and Bogusz, 2012). In order to develop a kinematic model of vertical crustal movements, one of the possibilities is an adjustment of the network formed simultaneously with the leveling data and GNSS stations data. The main problem is a need to identify fiducial points between the datasets. This problem can be solved by creation of coherent database containing attributes of both types of data and automatization of the joint point identification process. The article shows the results of such identification process, depending on the amount of data, on the example of the area of Poland. ARTICLE INFO

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The Analysis of Networks Space Structures as Important Elements of Sustainable Space Development

Cited by 4 publications

References 12 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

Identification of pseudo-nodal points on the basis precise leveling campaigns data and GNSS

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