367 research outputs found

    Is spatial information in ICT data reliable?

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    An increasing number of human activities are studied using data produced by individuals' ICT devices. In particular, when ICT data contain spatial information, they represent an invaluable source for analyzing urban dynamics. However, there have been relatively few contributions investigating the robustness of this type of results against fluctuations of data characteristics. Here, we present a stability analysis of higher-level information extracted from mobile phone data passively produced during an entire year by 9 million individuals in Senegal. We focus on two information-retrieval tasks: (a) the identification of land use in the region of Dakar from the temporal rhythms of the communication activity; (b) the identification of home and work locations of anonymized individuals, which enable to construct Origin-Destination (OD) matrices of commuting flows. Our analysis reveal that the uncertainty of results highly depends on the sample size, the scale and the period of the year at which the data were gathered. Nevertheless, the spatial distributions of land use computed for different samples are remarkably robust: on average, we observe more than 75% of shared surface area between the different spatial partitions when considering activity of at least 100,000 users whatever the scale. The OD matrix is less stable and depends on the scale with a share of at least 75% of commuters in common when considering all types of flows constructed from the home-work locations of 100,000 users. For both tasks, better results can be obtained at larger levels of aggregation or by considering more users. These results confirm that ICT data are very useful sources for the spatial analysis of urban systems, but that their reliability should in general be tested more thoroughly.Comment: 11 pages, 9 figures + Appendix, Extended version of the conference paper published in the proceedings of the 2016 Spatial Accuracy Conference, p 9-17, Montpellier, Franc

    Crowdsourcing the Robin Hood effect in cities

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    Socioeconomic inequalities in cities are embedded in space and result in neighborhood effects, whose harmful consequences have proved very hard to counterbalance efficiently by planning policies alone. Considering redistribution of money flows as a first step toward improved spatial equity, we study a bottom-up approach that would rely on a slight evolution of shopping mobility practices. Building on a database of anonymized credit card transactions in Madrid and Barcelona, we quantify the mobility effort required to reach a reference situation where commercial income is evenly shared among neighborhoods. The redirections of shopping trips preserve key properties of human mobility, including travel distances. Surprisingly, for both cities only a small fraction (5%\sim 5 \%) of trips need to be altered to reach equity situations, improving even other sustainability indicators. The method could be implemented in mobile applications that would assist individuals in reshaping their shopping practices, to promote the spatial redistribution of opportunities in the city.Comment: 9 pages, 4 figures + Appendi

    Uncovering the spatial structure of mobility networks

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    The extraction of a clear and simple footprint of the structure of large, weighted and directed networks is a general problem that has many applications. An important example is given by origin-destination matrices which contain the complete information on commuting flows, but are difficult to analyze and compare. We propose here a versatile method which extracts a coarse-grained signature of mobility networks, under the form of a 2×22\times 2 matrix that separates the flows into four categories. We apply this method to origin-destination matrices extracted from mobile phone data recorded in thirty-one Spanish cities. We show that these cities essentially differ by their proportion of two types of flows: integrated (between residential and employment hotspots) and random flows, whose importance increases with city size. Finally the method allows to determine categories of networks, and in the mobility case to classify cities according to their commuting structure.Comment: 10 pages, 5 figures +Supplementary informatio

    From mobile phone data to the spatial structure of cities

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    Pervasive infrastructures, such as cell phone networks, enable to capture large amounts of human behavioral data but also provide information about the structure of cities and their dynamical properties. In this article, we focus on these last aspects by studying phone data recorded during 55 days in 31 Spanish metropolitan areas. We first define an urban dilatation index which measures how the average distance between individuals evolves during the day, allowing us to highlight different types of city structure. We then focus on hotspots, the most crowded places in the city. We propose a parameter free method to detect them and to test the robustness of our results. The number of these hotspots scales sublinearly with the population size, a result in agreement with previous theoretical arguments and measures on employment datasets. We study the lifetime of these hotspots and show in particular that the hierarchy of permanent ones, which constitute the "heart" of the city, is very stable whatever the size of the city. The spatial structure of these hotspots is also of interest and allows us to distinguish different categories of cities, from monocentric and "segregated" where the spatial distribution is very dependent on land use, to polycentric where the spatial mixing between land uses is much more important. These results point towards the possibility of a new, quantitative classification of cities using high resolution spatio-temporal data.Comment: 14 pages, 15 figure

    From Local Adaptation to Speciation: Specialization and Reinforcement

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    Local adaptation is the first step in the process of ecological speciation. It is, however, an unstable and dynamic situation. It can be strengthened by the occurrence of alleles more specialized to the different habitats or vanish if generalist alleles arise by mutations and increase in frequency. This process can have complicated dynamics as specialist alleles may be much more common and may maintain local adaptation for a long time. Thus, even in the absence of an absolute fitness tradeoff between habitats, local adaptation may persist a long time before vanishing. Furthermore, several feedback loops can help to maintain it (the reinforcement, demographic, and recombination loops). This reinforcement can occur by modifying one of the three fundamental steps in a sexual life cycle (dispersal, syngamy, meiosis), which promotes genetic clustering by causing specific genetic associations. Distinguishing these mechanisms complements the one- versus two-allele classification. Overall, the relative rates of the two processes (specialization and reinforcement) dictate whether ecological speciation will occur

    Comparing and modeling land use organization in cities

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    The advent of geolocated ICT technologies opens the possibility of exploring how people use space in cities, bringing an important new tool for urban scientists and planners, especially for regions where data is scarce or not available. Here we apply a functional network approach to determine land use patterns from mobile phone records. The versatility of the method allows us to run a systematic comparison between Spanish cities of various sizes. The method detects four major land use types that correspond to different temporal patterns. The proportion of these types, their spatial organization and scaling show a strong similarity between all cities that breaks down at a very local scale, where land use mixing is specific to each urban area. Finally, we introduce a model inspired by Schelling's segregation, able to explain and reproduce these results with simple interaction rules between different land uses.Comment: 9 pages, 6 figures + Supplementary informatio

    Cross-Checking Different Sources of Mobility Information

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    International audienceThe pervasive use of new mobile devices has allowed a better characterization in space and time of human concentrations and mobility in general. Besides its theoretical interest, describing mobility is of great importance for a number of practical applications ranging from the forecast of disease spreading to the design of new spaces in urban environments. While classical data sources, such as surveys or census, have a limited level of geographical resolution (e.g., districts, municipalities, counties are typically used) or are restricted to generic workdays or weekends, the data coming from mobile devices can be precisely located both in time and space. Most previous works have used a single data source to study human mobility patterns. Here we perform instead a cross-check analysis by comparing results obtained with data collected from three different sources: Twitter, census and cell phones. The analysis is focused on the urban areas of Barcelona and Madrid, for which data of the three types is available. We assess the correlation between the datasets on different aspects: the spatial distribution of people concentration, the temporal evolution of people density and the mobility patterns of individuals. Our results show that the three data sources are providing comparable information. Even though the representativeness of Twitter geolocated data is lower than that of mobile phone and census data, the correlations between the population density profiles and mobility patterns detected by the three datasets are close to one in a grid with cells of 2 × 2 and 1 × 1 square kilometers. This level of correlation supports the feasibility of interchanging the three data sources at the spatio-temporal scales considered

    Uncovering cryptic asexuality in Daphnia magna by RAD sequencing

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    The breeding systems of many organisms are cryptic and difficult to investigate with observational data, yet they have profound effects on a species’ ecology, evolution, and genome organization. Genomic approaches offer a novel, indirect way to investigate breeding systems, specifically by studying the transmission of genetic information from parents to offspring. Here we exemplify this method through an assessment of self-fertilization vs. automictic parthenogenesis in Daphnia magna. Self-fertilization reduces heterozygosity by 50% compared to the parents, but under automixis, whereby two haploid products from a single meiosis fuse, the expected heterozygosity reduction depends on whether the two meiotic products are separated during meiosis I or II (i.e., central vs. terminal fusion). Reviewing the existing literature and incorporating recombination interference, we derive an interchromosomal and an intrachromosomal prediction of how to distinguish various forms of automixis from self-fertilization using offspring heterozygosity data. We then test these predictions using RAD-sequencing data on presumed automictic diapause offspring of so-called nonmale producing strains and compare them with “self-fertilized” offspring produced by within-clone mating. The results unequivocally show that these offspring were produced by automixis, mostly, but not exclusively, through terminal fusion. However, the results also show that this conclusion was only possible owing to genome-wide heterozygosity data, with phenotypic data as well as data from microsatellite markers yielding inconclusive or even misleading results. Our study thus demonstrates how to use the power of genomic approaches for elucidating breeding systems, and it provides the first demonstration of automictic parthenogenesis in Daphnia
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