5,276 research outputs found

    Diverse cities or the systematic paradox of Urban Scaling Laws

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    Scaling laws are powerful summaries of the variations of urban attributes with city size. However, the validity of their universal meaning for cities is hampered by the observation that different scaling regimes can be encountered for the same territory, time and attribute, depending on the criteria used to delineate cities. The aim of this paper is to present new insights concerning this variation, coupled with a sensitivity analysis of urban scaling in France, for several socio-economic and infrastructural attributes from data collected exhaustively at the local level. The sensitivity analysis considers different aggregations of local units for which data are given by the Population Census. We produce a large variety of definitions of cities (approximatively 5000) by aggregating local Census units corresponding to the systematic combination of three definitional criteria: density, commuting flows and population cutoffs. We then measure the magnitude of scaling estimations and their sensitivity to city definitions for several urban indicators, showing for example that simple population cutoffs impact dramatically on the results obtained for a given system and attribute. Variations are interpreted with respect to the meaning of the attributes (socio-economic descriptors as well as infrastructure) and the urban definitions used (understood as the combination of the three criteria). Because of the Modifiable Areal Unit Problem (MAUP) and of the heterogeneous morphologies and social landscapes in the cities' internal space, scaling estimations are subject to large variations, distorting many of the conclusions on which generative models are based. We conclude that examining scaling variations might be an opportunity to understand better the inner composition of cities with regard to their size, i.e. to link the scales of the city-system with the system of cities

    Scaling in Words on Twitter

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    Mobile phone indicators and their relation to the socioeconomic organisation of cities

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    Thanks to the use of geolocated big data in computational social science research, the spatial and temporal heterogeneity of human activities are increasingly being revealed. Paired with smaller and more traditional data, this opens new ways of understanding how people act and move, and how these movements crystallise into the structural patterns observed by censuses. In this article we explore the convergence of mobile phone data with more classical socioeconomic data from census in French cities. We extract mobile phone indicators from six months worth of Call Detail Records (CDR) data, while census and administrative data are used to characterize the socioeconomic organisation of French cities. We address various definitions of cities and investigate how they impact the relation between mobile phone indicators, such as the number of calls or the entropy of visited cell towers, and measures of economic organisation based on census data, such as the level of deprivation, inequality and segregation. Our findings show that some mobile phone indicators relate significantly with different socioeconomic organisation of cities. However, we show that found relations are sensitive to the way cities are defined and delineated. In several cases, differing city definitions delineations can change the significance or even the signs of found correlations. In general, cities delineated in a restricted way (central cores only) exhibit traces of human activity which are less related to their socioeconomic organisation than cities delineated as metropolitan areas and dispersed urban regions.Comment: 19 pages, 9 figures, 2 table

    Large cities are less efficient for sustainable transport: The ABC of mobility

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    The distance travelled by car in a city has many negative impacts on its population, including pollution, noise and the use of space. Yet, quantifying the motorisation of urban mobility is a serious challenge, particularly across cities of different regions. Here we model the number of kilometres travelled by different modes of transport in a city by aggregating active mobility (A), public transport (B) and cars (C), thus expressing the modal share of a city by its ABC triplet. Data for over 800 cities across over 60 countries is used to model kilometres travelled by car and its relationship with city size. Our findings suggest that although public transport is more prominent in large cities, it is insufficient to reduce the distance travelled by car users within the city and, ultimately, their emissions. For cities outside the US, results show that although the proportion of journeys by car decreases in larger cities, distances become more prolonged, thus experiencing more distance travelled by car. When a city doubles its size, it has 87\% more car journeys, but they are 41% longer, thus experiencing 2.6 times more vehicle kilometres travelled. Further, by matching cities of similar size inside and outside the US, we estimate that cities in the US have 2.3 times more vehicle kilometres travelled than cities elsewhere.Comment: 14 pages, 6 figure
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