Cartography of interaction fields in and around Brussels: commuting, moves and telephone calls

Adam, Arnaud; Delvenne, Jean‐Charles; Thomas, Isabelle

doi:10.4000/brussels.1601

Cited by 5 publications

(9 citation statements)

References 29 publications

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“…As a consequence one could conclude that the range for commuting is larger than for other dimensions of daily life. These differences are important as they reflect that work-related urban systems differ from not-work related urban systems, this was also revealed by Adam et al (2017).…”

Section: Figmentioning

confidence: 85%

“…The partitioning was exerted using the Louvain method (Blondel et al 2008). We chose the Louvain method as it has been frequently applied to Belgian data (telephone data, commuting data, migration data, logistics networks) and the methodological pitfalls are well known (Adam et al 2017;Beckers et al 2017;Thomas et al 2017). This community detection algorithm evaluates the gain in modularity that would take place by including a certain node in one of the communities.…”

Section: Aq2mentioning

confidence: 99%

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Assessing Daily Urban Systems: A Heterogeneous Commuting Network Approach

2018

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Daily Urban Systems (DUSs) are not only an attractive concept for planning locations for jobs, housing, schools and retail, but also for managing services such as public transportation and health care. If we can match geographically demand and supply of goods and services, higher levels of spatial efficiency can be reached. Since 50 years most of the research delineating DUSs uses thresholds of commuting levels, thus identifying labor markets polarized towards central cities. Few research grasps the more recent complex interactions within metropolitan areas due to growth and decentralization of activities. In this paper, we use techniques of complex network theory, namely community detection, on nearly 4,500,000 Belgian commuting links to define DUSs. Secondly, we explore differences for DUSs by gender and by income group. The results confirm the usefulness of community detection techniques for delineating Daily Urban Systems. Commuting patterns of females and low and very low income commuters are geographically more restricted than those of male and high and very high income commuters.

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Section: Figmentioning

confidence: 85%

Section: Aq2mentioning

confidence: 99%

Assessing Daily Urban Systems: A Heterogeneous Commuting Network Approach

2018

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“…Researchers have focused on the division of human activity space to discover more actual ways that people interact across space. For example, Adam, Delvenne, and Thomas [2] investigated the subjective partitioning of urban space in Brussels and confirmed the sprawling of the metropolitan territory. Kallus et al [3] redrew the geo-political borders from the worldwide Twitter communication networks, which showed the effects of local conflicts and globalization on entire continents.…”

Section: A the Division Of Human Activity Spacementioning

confidence: 94%

“…Accompanied by the subjectivity of human beings, various unprecedented types of activity data have been produced. These activity data, such as taxi GPS data, mobile phone data, and social media data, are regarded as inherent driving forces for the subjective partitioning of urban space [2]- [4]. Combined with human activity data, network analysis methods have been expanded as a support for the subjective partitioning of urban space.…”

Section: Introductionmentioning

confidence: 99%

Fine-Grained Subjective Partitioning of Urban Space Using Human Interactions From Social Media Data

Qiao

Wang

et al. 2019

IEEE Access

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Fine-grained subjective partitioning of urban space using human activity flows reveals actual human activity spaces with high resolution, which has great implications for the development and validation of planning strategies. This paper presents a new method for fine-grained subjective partitioning of urban space based on the combination of network analysis and human interactions from social media. Three main procedures are involved in this method: 1) a cut-off point for hierarchical partitioning is determined by fitting the probability distribution function of human activity patterns; 2) based on this cut-off point, improved hierarchical weighted-directed spatial networks are constructed by incorporating a gravity model into conventional spatial networks to take into account the importance of the attraction of nodes in shaping urban space; and 3) the hierarchical and fine-grained partitioning results, which reveal the actual human activity spaces with high resolution at multiscale are obtained by implementing a spatial community detection algorithm in these networks. A case study, using a real-world dataset from the capital of China validates the effectiveness of the proposed method. By analyzing the results from Beijing, we concluded that the social media, a gravity model, and the hierarchical subjective communities detected from the hierarchical human activity networks are all outstanding contributors to the fine-grained subjective partitioning of urban spaces.INDEX TERMS Gravity model, hierarchy, network analysis, social media, subjective partitioning.

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“…Le schéma général « 1 jeu de données = 1 article » a abouti à la détection de bassins de mobilité dans lesquels les habitant•e•s ont significativement tendance à résider et à travailler à la fois, ou dans lesquels ils ou elles ont tendance à déménager significativement plus ; de bassins d'interactions interpersonnelles, dans lesquels les appels téléphoniques ou les échanges sur les réseaux sociaux sont significativement plus marqués ; de bassins économiques, dans lesquels les échanges de marchandises par le réseau de fret routier sont plus intenses ; etc. (Jones et al, 2016 ;Thomas et al, 2017 ;Adam et al, 2017Adam et al, , 2018aAdam et al, , 2018bDecuyper et al, 2018 ;Finance et al, 2019aFinance et al, , 2019b. Autant de réseaux qui révèlent comment les interrelations entre acteurs de la ville (et ainsi entre portions de la ville) la forgent à diverses échelles.…”

Section: Mappemonde 130 | 2021unclassified