Les systèmes urbains français : une approche relationnelle

Berroir, Sandrine; Cattan, Nadine; Dobruszkes, Frédéric; Guérois, Marianne; Paulus, Fabien; Vacchiani-Marcuzzo, Céline

doi:10.4000/cybergeo.27945

Cited by 25 publications

(21 citation statements)

References 19 publications

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“…Model experiments were run with varying the parameters d 0 , σ, T 0 , c, and the type of setup between uniform and synthetic city system for a baseline experiment, as well as varying α on a targeted experiment on a synthetic city system. The meta-parameters (parameters for model geographical initialization which remain fixed in experiments) were fixed at N = 50 (one sector of reasonable size), γ = 1.3 (yielding a hierarchical city system (Cottineau, 2017)), β = 1.5 (supra-linear scaling law between population and industry, corresponding to a high added-value sector (Bettencourt et al, 2007)) and p = 5 centers within a square world of size 100km (typical of a regional city system as shown for example in the case of France by Berroir et al (2017), and being the magnitude of the application to Netherlands). Boundaries of varying parameters and details of numerical experiments are given in 4.…”

Section: Resultsmentioning

confidence: 99%

A spatial agent based model for simulating and optimizing networked eco-industrial systems

Raimbault¹,

Broere

Somveille

et al. 2020

Resources, Conservation and Recycling

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Industrial symbiosis involves creating integrated cycles of by-products and waste between networks of industrial actors in order to maximize economic value, while at the same time minimizing environmental strain. In such a network, the global environmental strain is no longer equal to the sum of the environmental strain of the individual actors, but it is dependent on how well the network performs as a whole. The development of methods to understand, manage or optimize such networks remains an open issue. In this paper we put forward a simulation model of by-product flow between industrial actors. The goal is to introduce a method for modelling symbiotic exchanges from a macro perspective. The model takes into account the effect of two main mechanisms on a multi-objective optimization of symbiotic processes. First it allows us to study the effect of geographical properties of the economic system, said differently, where actors are divided in space. Second, it allows us to study the effect of clustering complementary actors together as a function of distance, by means of a spatial correlation between the actors by-products. Our simulations unveil patterns that are relevant for macro-level policy. First, our results show that the geographical properties are an important factor for the macro performance of symbiotic processes. Second, spatial correlations, which can be interpreted as planned clusters such as Eco-industrial parks, can lead to a very effective macro performance, but only if these are strictly implemented. Finally, we provide a proof of concept by comparing the model to real world data from the European Pollutant Release and Transfer Register database using georeferencing of the companies in the dataset. This work opens up research opportunities in interactive data-driven models and platforms to support real-world implementation of industrial symbiosis.

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Section: Resultsmentioning

confidence: 99%

A spatial agent based model for simulating and optimizing networked eco-industrial systems

Raimbault¹,

Broere

Somveille

et al. 2020

Resources, Conservation and Recycling

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“…It can be obtained by looking at the infrastructure such as a railway, roads or postal road network (Bretagnolle & Franc, 2017;Derudder, Liu, Kunaka, & Roberts, 2014), by looking at the moves of vehicles such as ships (Ducruet, Cuyala, & El Hosni, 2018) or by looking at actual traffic, which covers both goods and people. Numerous studies have looked at flows of people to measure intercity relations at the regional, national or global scales, whether it is air passengers (Derudder & Witlox, 2005), train passengers (Berroir et al, 2017) or commuters (Nelson & Rae, 2016). Recently, flows of people have also been identified through geolocated posts of people on social media (Lenormand et al, 2015;Zhang, Derudder, Wang, Shen, & Witlox, 2016), which allows to overcome the national dimension of data collection, but is not necessarily without representative bias.…”

Section: Overview Of Methodsmentioning

confidence: 99%

“…Nowadays, the combination of several sources of information to study the different networks and flows connecting cities and their mutual interdependencies are increasingly popular (Berroir et al, 2017;Burger, Meijers, et al, 2014;Choi, Barnett, & Chon, 2006;Ducruet, Ietri, & Rozenblat, 2011), as are approaches that employ 'big data', some of which were discussed in the introduction. The toponym co-occurrence method that takes centre stage in this paper has also developed from an initial manual exercise to an example of a big data approach to analyzing systems of cities.…”

Section: Overview Of Methodsmentioning

confidence: 99%

“…Despite considerable progress over the last 20 years, which we review later, the availability and adequacy of data on relationships between cities still remains a critical issue because of a variety of problems. First of all, this relates to the use of indicators that only sketch a partial picture in that they cannot account for the multiplicity of networks, which refers to the fact that the spatial organization of different types of functional linkages is not necessarily identical (Berroir et al, 2017;Burger, Meijers, & van Oort, 2014;Limtanakool, Schwanen, & Dijst, 2009). Second, inadequate proxies are, or need to be used in the absence of more direct indicators.…”

Section: Introductionmentioning

confidence: 99%

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Using toponym co-occurrences to measure relationships between places: review, application and evaluation

Meijers

Peris

2018

International Journal of Urban Sciences

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While there is consensus that network embeddedness of cities is of great importance for their development, the precise effect is difficult to assess because of a lack of consistent information on relations between cities. This paper presents, applies and evaluates a rather novel method to establish the strength of relationships between places, a method we refer to as 'the toponym co-occurrence method'. This approach builds the urban system on the basis of co-occurrences of place names in a text corpus. We innovate by exploiting a so far unparalleled amount of data, namely the billions of web pages contained in the commoncrawl web archive, and by applying the method also to small places that tend to be ignored by other methods. The entire settlement system of the Netherlands is consequently explored. In addition, we innovatively apply machine learning techniques to classify these relations. Much attention is paid to solving biases deriving from place name disambiguation. Gravity modelling is employed to assess the resulting spatial organization of the Netherlands. It turns out that the gravity model fits very well with the pattern of relationships between places as found in digital space, which contributes to our assessment that the toponym co-occurrence method is a solid proxy for relationships in real space. Using the method, it is established that the relationships in the Randstad region, by many considered a coherent metropolitan entity, are actually somewhat less strong than expected. In contrast, historically important, but nowadays small cities in the periphery tend to have maintained their prominent position in the pattern of relationships. Suburban, relatively new places in the shadow of a larger city tend to be weakly related to other places. Several suggestions to further improve the method, in particular the classification of relationships, are discussed.

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“…In geography, one of the earliest examples of the kind was provided by Cattan (1995) in her study of barrier effects affecting air and rail flows between European cities (see also van Geenhuizen, 2000). Later on, Berroir et al (2012) revealed the emergence of subnetworks among French urban areas based on multiple interactions such as air flights, commuting flows, scientific collaborations, high-speed rail linkages, and firms' networks. This particular approach of the "French school" (P.A.R.I.S.…”

Section: Inter-network Externalitiesmentioning

confidence: 99%

Sea-Land Interdependence in the Global Maritime Network: the Case of Australian Port Cities

2018

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This article tackles the longstanding issue of intermodality head on. From a geomatics perspective, we model both maritime and road networks connecting port and non-port cities taking into account crucial features such as physical geography, shortest paths, and transport costs. This creates the opportunity to study a hybrid network -both planar and non-planar, and the centrality/accessibility of cities in this bilayered network. Based on the case of Australia, main results convey new empirical findings on how port and urban hierarchies correlate with single-layered and bi-layered connectivity. We discuss main results in the light of network science, spatial science, and transport studies.

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Les systèmes urbains français : une approche relationnelle

Cited by 25 publications

References 19 publications

A spatial agent based model for simulating and optimizing networked eco-industrial systems

A spatial agent based model for simulating and optimizing networked eco-industrial systems

Using toponym co-occurrences to measure relationships between places: review, application and evaluation

Sea-Land Interdependence in the Global Maritime Network: the Case of Australian Port Cities

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