The evolution of the commuting network in Germany: Spatial and connectivity patterns

Patuelli, Roberto; Reggiani, Aura; Nijkamp, Peter; Bade, Franz-Josef

doi:10.5198/jtlu.v2i3.23

Cited by 23 publications

(16 citation statements)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Consequently, we might conjecture an 'intermediate' structure between homogeneous and heterogeneous configurations for the trip-makers (see Section 2). In addition, given recent results which highlight the polarization characteristics of the German commuting flows in the year 2005 (Patuelli et al 2007(Patuelli et al , 2010, we may infer here a tendency towards heterogeneity/ polarization in the commuter flows between the German districts.…”

Section: Impedance Function Based On Observed Datamentioning

confidence: 90%

“…Good reviews on this topic can be found in, amongst others, Barabási and Oltvai (2004), Grubesic et al (2008), and Jeong et al (2003). Recent applications in transport concern the identification of an RN vs. an SF network with reference to the evolution of commuting flows (De Montis et al 2007;Patuelli et al 2010;Russo et al 2007), and of air transport flows (Barrat et al 2004;Reggiani et al 2010a).…”

Section: Network Models: a Brief Reviewmentioning

confidence: 97%

See 1 more Smart Citation

Accessibility and Network Structures in the German Commuting

Reggiani

Bucci²,

Russo

2010

Netw Spat Econ

Self Cite

View full text Add to dashboard Cite

A great deal of attention has recently been paid to the analysis of the structure and evolution of (complex) networks, starting from pioneering contributions in the physical and social sciences-and more recently in the regional and transportation sciences-mainly concerning the relevance of highly connected nodes (hubs). The presence of hubs identifies a network as Scale-Free (SF), because of its intrinsic characteristic of exhibiting power-law distributions in its connectivity structure, and thus highly heterogeneous patterns. The focus of this paper is to explore the homogeneous vs. heterogeneous characteristics of the German commuting network, by focusing on the role of accessibility. The concept of accessibility has a long tradition in the transport economics literature, starting with the fundamental works by Hansen in the 1950's and later on by Weibull in the 1980's. These authors defined accessibility as the potential of opportunities for spatial interaction. Accessibility conceived in this manner should also capture spatial structure effects and thus the network configuration properties, such as connectivity. This conventional accessibility function-in the light of the related economic activities-is be used as a suitable instrument to identify the major German hub/attraction nodes. As the functional form in this potential accessibility, the powerdecay function will be considered-in addition to the negative exponential function-in order to explore the spatial configuration patterns, i.e. whether people perceive commuting cost in log-like way. The connectivity network analysis will then be developed as a benchmark to testing the results emerging from the spatial-economic

show abstract

Section: Impedance Function Based On Observed Datamentioning

confidence: 90%

Section: Network Models: a Brief Reviewmentioning

confidence: 97%

Accessibility and Network Structures in the German Commuting

Reggiani

Bucci²,

Russo

2010

Netw Spat Econ

Self Cite

View full text Add to dashboard Cite

show abstract

“…In the last decade, the field of distributed processing of large-scale graphs has attracted considerable attention [5]. This attention has been motivated not only by the increasing size of graph data, but also by its huge number of applications, such as the analysis of social networks [8], web graphs [2] and spatial networks [18]. In this context, many distributed/parallel graph processing systems have been proposed, such as Pregel [16], GraphLab [15], and Trinity [23].…”

Section: Introductionmentioning

confidence: 99%

BLADYG: A Graph Processing Framework for Large Dynamic Graphs

Aridhi¹,

Montresor²,

Velegrakis³

2017

Big Data Research

View full text Add to dashboard Cite

Recently, distributed processing of large dynamic graphs has become very popular, especially in certain domains such as social network analysis, Web graph analysis and spatial network analysis. In this context, many distributed/parallel graph processing systems have been proposed, such as Pregel, GraphLab, and Trinity. These systems can be divided into two categories: (1) vertex-centric and (2) block-centric approaches. In vertex-centric approaches, each vertex corresponds to a process, and message are exchanged among vertices. In blockcentric approaches, the unit of computation is a block, a connected subgraph of the graph, and message exchanges occur among blocks. In this paper, we are considering the issues of scale and dynamism in the case of block-centric approaches. We present bladyg, a block-centric framework that addresses the issue of dynamism in large-scale graphs. We present an implementation of bladyg on top of akka framework. We experimentally evaluate the performance of the proposed framework.

show abstract

“…Patuelli et al (2010) conducted an analysis of German commuting trends from both a spatial and network perspective to understand the hierarchies among 439 German districts. Zhang et al (2012) analyzed the association between road network structure and nonmotorist safety using data from census tracts in Alameda County, California.…”

Section: Network Structurementioning

confidence: 99%

Network structure and metropolitan mobility

Parthasarathi¹

2014

JTLU

View full text Add to dashboard Cite

a Abstract: is research aims to develop quantitative measures that capture various aspects of the underlying network structure, using aggregate level travel data from fiy metropolitan areas across the US. e influence of these measures on system performance is then tested using statistical regression models. e results corroborate that the quantitative measures of network structure affect the system performance. e results from this analysis can be used to develop network design guidelines that can be used to address current transportation problems.

show abstract

The evolution of the commuting network in Germany: Spatial and connectivity patterns

Cited by 23 publications

References 44 publications

Accessibility and Network Structures in the German Commuting

Accessibility and Network Structures in the German Commuting

BLADYG: A Graph Processing Framework for Large Dynamic Graphs

Network structure and metropolitan mobility

Contact Info

Product

Resources

About