Is spatial information in ICT data reliable?

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

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 ($\sim 5 \%$) 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

Comparer les morphogénèses urbaines en Europe et aux États-Unis par la simulation à base d'agents -- Approches multi-niveaux et environnements de simulation spatiale

The multilevel comparison of spatial and hierarchical organisations of urban systems over the world highlights some generic and universal properties (rank-size law, center-periphery structure) but also a variety of more specific patterns (in terms of spatial repartition of populations, densities, prices, activities, etc.). The spatial economy and the urban evolutionnary theory both focus on the explanation of the emergence of such patterns, but the simulation models they support classicaly consider one level of spatial organisation only, respectively intra- and inter-urban. Understanding and reconstructing those levels' interdependancies is a crucial issue for long-term sustainable urban planning. This thesis presents a set of models and tools that are dedicated to the study of this question through agent-based simulation. They have been developed in the context of the Simpop project, and particulary on the comparison of the morphogenesis of urban systems in Europe and in the United States over the period 1800-2000. These tools include the simpopNano agent-based model, and some experimentation modules gathered in an extensible and generic GIS-based platform, which is dedicated to a systematic, collective and intelligent exploration of spatial simulation models. Together they reinforce the idea that the sole difference of topology of the streets networks could be sufficient to generate some more diluted spatial repartitions, as observed in US cities when compared to european ones. This intra-urban model is then articulated with an inter-urban one, Simpop2, in a multilevel model. The latter serves to engage a comparison among a variety of approaches in agent-based simulation litterature for integrating models of multiple levels of abstraction.La comparaison, à différents niveaux (systèmes de villes, villes, quartiers), de l'organisation spatiale et hiérarchique des systèmes urbains dans le monde fait apparaître des propriétés universelles (loi rang-taille, structure centre-périphérie des villes, etc.) mais également une grande variété de formes (notamment en termes de répartition des populations, densités, prix, activités). Si la théorie évolutionnaire urbaine et celles d'économie spatiale offrent des schémas explicatifs de cette émergence de formes, les modèles qui en sont issus se sont jusqu'à présent focalisé sur un seul niveau d'organisation spatiale, qu'il soit intra- ou inter-urbain. Dans une optique d'aménagement durable, il est important de disposer de modèles permettant de raisonner sur les inter-dépendances qu'entretiennent ces niveaux d'organisation du peuplement. Cette thèse présente une famille de modèles entités-centrés et d'outils dédiés à l'étude de cette problématique par la simulation à base d'agents. Ils s'inscrivent dans le projet Simpop et sont mis en oeuvre sur la comparaison des morphogenèses urbaines en Europe et aux Etats-Unis, sur la période 1800-2000. Ils incluent notamment le simulateur simpopNano, accompagné d'un environnement modulaire construit autour d'un SIG pour une exploitation systématique, intelligente et collective de modèles spatiaux. Ensemble, ils confortent l'idée que la seule différence des maillages des réseaux viaires des villes suffit à exprimer des répartitions spatiales plus diffuses sur les grilles américaines que sur les plans radioconcentriques européens. Ce modèle intra-urbain est ensuite articulé avec le modèle de systèmes de villes Simpop2 dans un modèle multi-niveaux, inter et intra-urbain. Il est le point d'ancrage d'une comparaison d'approches dédiées à l'intégration de modèles dynamiques associés à différents niveaux d'abstraction

From mobile phone data to the spatial structure of cities

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

Uncovering the spatial structure of mobility networks

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 $2\times 2$ 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

Comparing and modeling land use organization in cities

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

The 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.Partial financial support has been received from the Spanish Ministry of Economy (MINECO) and FEDER (EU) under projects MODASS (FIS2011-24785) and INTENSE@COSYP (FIS2012-30634), and from the EU Commission through projects EUNOIA, LASAGNE and INSIGHT. ML acknowledges funding from the Conselleria d'Educació, Cultura i Universitats of the Government of the Balearic Islands, and JJR from the Ramón y Cajal program of MINECO.Peer Reviewe

Cross-Checking Different Sources of Mobility Information

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

Human mobility:Models and applications

Recent years have witnessed an explosion of extensive geolocated datasets related to human movement, enabling scientists to quantitatively study individual and collective mobility patterns, and to generate models that can capture and reproduce the spatiotemporal structures and regularities in human trajectories. The study of human mobility is especially important for applications such as estimating migratory flows, traffic forecasting, urban planning, and epidemic modeling. In this survey, we review the approaches developed to reproduce various mobility patterns, with the main focus on recent developments. This review can be used both as an introduction to the fundamental modeling principles of human mobility, and as a collection of technical methods applicable to specific mobility-related problems. The review organizes the subject by differentiating between individual and population mobility and also between short-range and long-range mobility. Throughout the text the description of the theory is intertwined with real-world applications.Comment: 126 pages, 45+ figure