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      On the nature of urban dependencies: How Manhattan and Barcelona reinforced a natural organisation despite planning intentionality

      1 , 1
      Environment and Planning B: Planning and Design
      SAGE Publications

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          Abstract

          Cities appear to display similar features and mechanisms across different geographies. This phenomenon seems to hold despite planning intentionality. In questioning the nature of this behaviour, an attempt is made in this paper to examine how cities retrieve their relational dependencies between street structures and other form-function attributes after the imposition of large-scale planning interventions. For the purpose of this investigation, indices of accessibility and form-function data are binned in a grid layer to enable mapping dependencies between these variables in Manhattan and Barcelona. Ordinal Regression models are fitted to empirical data in order to identify the effect of planning on urban dependencies. To reveal how these dependencies build up in time, we model and visualise a dependency network that captures the spatiotemporal relationships between accessibility and form-function variables in Manhattan (1880–2010). The hypothesis is that where planning interventions are more dominant, the natural organisation that couples urban dependencies will be destabilized. The results confirm the hypothesis true for some form-function variables and within certain grid resolutions. The dependency network representing urban transformations in Manhattan explained some aspects of temporality in the relationships between the network structure of streets, street width, building height, land values and retail land uses. The models presented in this paper are thought to highlight regularities in the growth and change of Manhattan and Barcelona. An explanatory theory on how cities display this convergent behaviour is thought to be vital for urban design and planning policies.

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          Most cited references24

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          Regression Modeling Strategies

          Springer Series in Statistics
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            Discovery of meaningful associations in genomic data using partial correlation coefficients.

            A major challenge of systems biology is to infer biochemical interactions from large-scale observations, such as transcriptomics, proteomics and metabolomics. We propose to use a partial correlation analysis to construct approximate Undirected Dependency Graphs from such large-scale biochemical data. This approach enables a distinction between direct and indirect interactions of biochemical compounds, thereby inferring the underlying network topology. The method is first thoroughly evaluated with a large set of simulated data. Results indicate that the approach has good statistical power and a low False Discovery Rate even in the presence of noise in the data. We then applied the method to an existing data set of yeast gene expression. Several small gene networks were inferred and found to contain genes known to be collectively involved in particular biochemical processes. In some of these networks there are also uncharacterized ORFs present, which lead to hypotheses about their functions. Programs running in MS-Windows and Linux for applying zeroth, first, second and third order partial correlation analysis can be downloaded at: http://mendes.vbi.vt.edu/tiki-index.php?page=Software. Supplementary information can be found at: URL to be decided.
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              Is Open Access

              Elementary processes governing the evolution of road networks

              Urbanisation is a fundamental phenomenon whose quantitative characterisation is still inadequate. We report here the empirical analysis of a unique data set regarding almost 200 years of evolution of the road network in a large area located north of Milan (Italy). We find that urbanisation is characterised by the homogenisation of cell shapes, and by the stability throughout time of high–centrality roads which constitute the backbone of the urban structure, confirming the importance of historical paths. We show quantitatively that the growth of the network is governed by two elementary processes: (i) ‘densification’, corresponding to an increase in the local density of roads around existing urban centres and (ii) ‘exploration’, whereby new roads trigger the spatial evolution of the urbanisation front. The empirical identification of such simple elementary mechanisms suggests the existence of general, simple properties of urbanisation and opens new directions for its modelling and quantitative description.
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                Author and article information

                Journal
                Environment and Planning B: Planning and Design
                Environ Plann B Plann Des
                SAGE Publications
                0265-8135
                1472-3417
                November 2016
                July 27 2016
                November 2016
                : 43
                : 6
                : 975-996
                Affiliations
                [1 ]Bartlett School of Architecture, University College London, UK
                Article
                10.1177/0265813516650200
                b14f3528-5954-4052-9752-b81c8c48edfa
                © 2016

                http://journals.sagepub.com/page/policies/text-and-data-mining-license

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