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In recent years, what has become known as collaborative consumption has undergone rapid expansion through peer-to-peer (P2P) platforms. In the field of tourism, a particularly notable example is that of Airbnb. This article analyses the spatial patterns of Airbnb in Barcelona and compares them with hotels and sightseeing spots. New sources of data, such as Airbnb listings and geolocated photographs are used. Analysis of bivariate spatial autocorrelation reveals a close spatial relationship between Airbnb and hotels, with a marked centre-periphery pattern, although Airbnb predominates around the city's main hotel axis and hotels predominate in some peripheral areas of the city. Another interesting finding is that Airbnb capitalises more on the advantages of proximity to the city's main tourist attractions than does the hotel sector. Multiple regression analysis shows that the factors explaining location are also different for hotels and Airbnb. Finally, it was possible to detect those parts of the city that have seen the greatest increase in pressure from tourism related to Airbnb's recent expansion., Ministerio de Economía y Competitividad of Spain, Comisión Europea, Depto. de Geografía, Fac. de Geografía e Historia, TRUE, pub

There is little knowledge available on the spatial behaviour of urban tourists, and yet tourists generate an enormous quantity of data when they visit cities. These data sources can be used to track their presence through their activities. The aim of this paper is to analyse the digital footprint of urban tourists through Big Data. Unlike other papers that use a single data source, this article examines three sources of data to reflect different tourism activities in cities: Panoramio (sightseeing), Foursquare (consumption), and Twitter (being connected-accommodation). The results show that the data from the three activities are partly spatially redundant and partly complementary, and allow the characterisation of multifunction tourist spaces and spaces specialising in one or various activities. The main conclusion is that it is not sufficient to use one data source to analyse the presence of tourists in cities; several must be used in a complementary manner., Comisión Europea, Ministerio de Economía y Competitividad, Comunidad de Madrid, Depto. de Geografía, Fac. de Geografía e Historia, TRUE, pub

As a consequence of the accelerated globalization process, today major cities all over the world are characterized by an increasing multiculturalism. The integration of immigrant communities may be affected by social polarization and spatial segregation. How are these dynamics evolving over time? To what extent the different policies launched to tackle these problems are working? These are critical questions traditionally addressed by studies based on surveys and census data. Such sources are safe to avoid spurious biases, but the data collection becomes an intensive and rather expensive work. Here, we conduct a comprehensive study on immigrant integration in 53 world cities by introducing an innovative approach: an analysis of the spatio-temporal communication patterns of immigrant and local communities based on language detection in Twitter and on novel metrics of spatial integration. We quantify the Power of Integration of cities –their capacity to spatially integrate diverse cultures– and characterize the relations between different cultures when acting as hosts or immigrants., Spanish Ministry of Economy (MINECO) and FEDER (EU), EU Commission, Depto. de Geografía, Fac. de Geografía e Historia, TRUE, pub

Accessibility is essentially a dynamic concept. However, most studies on urban accessibility take a static approach, overlooking the fact that accessibility conditions change dramatically throughout the day. Due to their high spatial and temporal resolution, the new data sources (Big Data) offer new possibilities for the study of accessibility. The aim of this paper is to analyse urban accessibility considering its two components –the performance of the transport network and the attractiveness of the destinations– using a dynamic approach using data from TomTom and Twitter respectively. This allows us to obtain profiles that highlight the daily variations in accessibility in the city of Madrid, and identify the influence of congestion and the changes in location of the population. These profiles reveal significant variations according to transport zones. Each transport zone has its own accessibility profile, and thus its own specific problems, which require solutions that are also specific., Comisión Europea, Ministerio de Economía y Competitividad, Fondo Europeo de Desarrollo Regional, Comunidad de Madrid, Depto. de Geografía, Fac. de Geografía e Historia, TRUE, pub

Social network data offer interesting opportunities in urban studies. In this study, we used Twitter data to analyse city dynamics over the course of the day. Users of this social network were grouped according to city zone and time slot in order to analyse the daily dynamics of the city and the relationship between this and land use. First, daytime activity in each zone was compared with activity at night in order to determine which zones showed increased activity in each of the time slots. Then, typical Twitter activity profiles were obtained based on the predominant land use in each zone, indicating how land uses linked to activities were activated during the day, but at different rates depending on the type of land use. Lastly, a multiple regression analysis was performed to determine the influence of the different land uses on each of the major time slots (morning, afternoon, evening and night) through their changing coefficients. Activity tended to decrease throughout the day for most land uses (e.g. offices, education, health and transport), but remained constant in parks and increased in retail and residential zones. Our results show that social network data can be used to improve our understanding of the link between land use and urban dynamics., Comisión Europea, Comunidad de Madrid, Ministerio de Economía y Competitividad, Fondo Europeo de Desarrollo Regional, Depto. de Geografía, Fac. de Geografía e Historia, TRUE, pub

As a consequence of the accelerated globalization process, today major cities all over the world are characterized by an increasing multiculturalism. The integration of immigrant communities may be affected by social polarization and spatial segregation. How are these dynamics evolving over time? To what extent the different policies launched to tackle these problems are working? These are critical questions traditionally addressed by studies based on surveys and census data. Such sources are safe to avoid spurious biases, but the data collection becomes an intensive and rather expensive work. Here, we conduct a comprehensive study on immigrant integration in 53 world cities by introducing an innovative approach: an analysis of the spatio-temporal communication patterns of immigrant and local communities based on language detection in Twitter and on novel metrics of spatial integration. We quantify the Power of Integration of cities –their capacity to spatially integrate diverse cultures– and characterize the relations between different cultures when acting as hosts or immigrants.

El indicador de potencial de mercado es una herramienta que se aplica frecuentemente en la planificación del transporte con el objetivo de evaluar los efectos económicos y territoriales que pueden provocar las mejoras en las infraestructuras. Este proceso se basa en el supuesto de que el aumento de la accesibilidad de una región está directamente relacionado con el aumento de sus exportaciones, y por ende, puede favorecer también al resto de sus actividades económicas. Interpretar la accesibilidad a partir del potencial de mercado significa establecer una relación positiva del nivel de oportunidades entre un origen i y un destino j con la masa del destino, e inversamente proporcional a la distancia o al tiempo de viaje entre ambos. Parte de la aceptación de la especificación del potencial de mercado se basa en su simplicidad estructural y operativa. La desventaja de esta condición es que se trata de un modelo que ignora efectos tales como el impacto de la competencia entre rivales o las barreas al comercio, los cuales se han mostrado significativos en los modelos de interacción espacial para el comercio. Esta situación implica que los resultados que se obtienen pueden reflejar desviaciones respecto a la realidad. Para aportar alternativas, esta tesis mejora el modelo clásico de potencial de mercado hacia una especificación más completa, integrando la competencia entre rivales y las barreras al comercio, y calibrando simultáneamente el impacto de la distancia con datos reales de comercio internacional que se aplican al caso concreto de los países Miembros de la Unión Europea (UE). Adicionalmente, la construcción de escenarios y el uso de análisis spillover valida el modelo propuesto como un instrumento para la evaluación de proyectos de infraestructuras de transporte de alto valor explicativo y de mayor ajuste a la realidad que los habitualmente utilizados. La obtención de este resultado se consigue a partir de la desagregación previa de la investigación en múltiples, The market potential indicator is frequently applied in transport planning in order to assess the economic and territorial effects derived from infrastructure improvements. This process is rooted on the principle that the increase of accessibility in a region is directly related to the increase in exports, and thus, can also help boosting the rest of their economic activities. Understanding accessibility through the market potential means to establish a positive relationship between the opportunities of an origin i and a destination j and the mass of the destination, and inversely proportional to the distance or the travel time between the two. Part of the wide acceptance of the market potential specification is based on its structural and operational simplicity. The disadvantage of this condition is that this model ignores some effects, like the impact of the competition between rivals or the barriers to trade, which proved significant in spatial interaction trade models. This situation implies that the obtained results may reflect deviations from reality. To provide alternatives, this thesis enhances the classic model of market potential towards a more complete specification. This is done with the integration of the competition between rivals and barriers to trade while calibrating the impact of distance with real data on international trade between the members of the European Union (EU). In addition, the construction of scenarios and spillover analysis validates the proposed model as a high performance instrument for the evaluation of transport infrastructure projects, leading to more realistic results than the classic ones. The research was divided into multiple tasks in order to achieve this result. First, the concept of accessibility and the different types of measures developed in the literature was thoroughly analysed. The main goal was to select and justify an effective indicator for the evaluation of transport projects, such as market potential. This fact

Accessibility-based land use and transport interaction (LUTI) models are tools for policy assessments that facilitate coherent implementation of sustainable strategic urban plans. This study aims to improve one of those LUTI models introducing the different impact of factors influencing residential and workplace choice by computing local coefficients. In particular, this research explores the methodology of integrating the public choice model into the MARS (Metropolitan Activity Relocation Simulator) model using a complex accessibility indicator. We established a new approach to input the variation of the influence of each public service across space with the use of Geographically Weighted Regression (GWR). The model update and extension of MARS are all based on the Region of Madrid, Spain. Using the new accessibility indicator yielded better results and corrected some under estimation and overestimations in the number of workplaces. The correlation using the new accessibility indicator is significantly higher than the one using the old one. The prediction using the new indicator achieves better results for the whole area whatever the zone is small or large. The analysis evidences the convenience of GIS and LUTI combination to improve model accuracy and precision. Using the new accessibility indicator based on local coefficients, MARS model fits better with the real data in respect of the distribution of workplaces and residents, which are the key representatives of the land use sub-model.

Actualmente asistimos a una verdadera revolución en la producción y el tratamiento de datos masivos (Big Data). Aunque los principales usuarios de este tipo de datos son las empresas, el mundo de la investigación ha encontrado también interesantes posibilidades en el análisis de Big Data, con abordajes nuevos a viejos problemas o incluso con el planteamiento de cuestiones que no podían ser abordadas con datos tradicionales. El presente artículo constituye una revisión de trabajos de investigación que utilizan datos masivos geolocalizados, Big (Geo)Data, y muestra ejemplos de aplicación en la investigación, ordenando los trabajos revisados según fuentes de datos: registros de llamadas de teléfonos móviles, redes sociales, comunidades de fotografías geolocalizadas, registros de transacciones con tarjetas de crédito, tarjetas inteligentes de transporte, navegadores, etc. El trabajo concluye con unas reflexiones sobre las ventajas que ofrece el Big (Geo)Data para el investigador, como la alta resolución espacial y temporal de los datos y, en muchos casos, su cobertura global y su carácter gratuito, pero también resalta algunos de los principales inconvenientes que plantea su uso, como el sesgo y la dificultad de su proceso y, en muchos casos, de acceso a los mismos., Currently we are witnessing a revolution in the production and processing of massive data (Big Data). Although the main users of such data are companies, social researchers have also found interesting possibilities in the analysis of Big Data, with new approaches to old questions or even with the approach to issues that could not be addressed with traditional data. This article is a review of research papers using geolocated massive data, Big (Geo)Data, and shows examples of their application in research, grouping the papers according to data sources: mobile phone calls records, social networks, communities of geolocated photos, credit card transactions records, transport smart cards, car navigators, etc. The paper concludes with some reflections on the advantages of Big (Geo)Data in social sciences research (high temporal and spatial resoluction, and, in many cases, global coverage and free of charge), but it also highlights some of the main problems arising from their use, such as bias, processing capacity and access barriers.

El indicador de potencial de mercado es una herramienta que se aplica frecuentemente en la planificación del transporte con el objetivo de evaluar los efectos económicos y territoriales que pueden provocar las mejoras en las infraestructuras. Este proceso se basa en el supuesto de que el aumento de la accesibilidad de una región está directamente relacionado con el aumento de sus exportaciones, y por ende, puede favorecer también al resto de sus actividades económicas. Interpretar la accesibilidad a partir del potencial de mercado significa establecer una relación positiva del nivel de oportunidades entre un origen i y un destino j con la masa del destino, e inversamente proporcional a la distancia o al tiempo de viaje entre ambos. Parte de la aceptación de la especificación del potencial de mercado se basa en su simplicidad estructural y operativa. La desventaja de esta condición es que se trata de un modelo que ignora efectos tales como el impacto de la competencia entre rivales o las barreas al comercio, los cuales se han mostrado significativos en los modelos de interacción espacial para el comercio. Esta situación implica que los resultados que se obtienen pueden reflejar desviaciones respecto a la realidad. Para aportar alternativas, esta tesis mejora el modelo clásico de potencial de mercado hacia una especificación más completa, integrando la competencia entre rivales y las barreras al comercio, y calibrando simultáneamente el impacto de la distancia con datos reales de comercio internacional que se aplican al caso concreto de los países Miembros de la Unión Europea (UE). Adicionalmente, la construcción de escenarios y el uso de análisis spillover valida el modelo propuesto como un instrumento para la evaluación de proyectos de infraestructuras de transporte de alto valor explicativo y de mayor ajuste a la realidad que los habitualmente utilizados. La obtención de este resultado se consigue a partir de la desagregación previa de la investigación en múltiples

Actualmente asistimos a una verdadera revolución en la producción y el tratamiento de datos masivos (Big Data). Aunque los principales usuarios de este tipo de datos son las empresas, el mundo de la investigación ha encontrado también interesantes posibilidades en el análisis de Big Data, con abordajes nuevos a viejos problemas o incluso con el planteamiento de cuestiones que no podían ser abordadas con datos tradicionales. El presente artículo constituye una revisión de trabajos de investigación que utilizan datos masivos geolocalizados, Big (Geo)Data, y muestra ejemplos de aplicación en la investigación, ordenando los trabajos revisados según fuentes de datos: registros de llamadas de teléfonos móviles, redes sociales, comunidades de fotografías geolocalizadas, registros de transacciones con tarjetas de crédito, tarjetas inteligentes de transporte, navegadores, etc. El trabajo concluye con unas reflexiones sobre las ventajas que ofrece el Big (Geo)Data para el investigador, como la alta resolución espacial y temporal de los datos y, en muchos casos, su cobertura global y su carácter gratuito, pero también resalta algunos de los principales inconvenientes que plantea su uso, como el sesgo y la dificultad de su proceso y, en muchos casos, de acceso a los mismos.

El comportamiento espacial de los turistas urbanos es poco conocido. Sin embargo, los turistas generan una enorme cantidad datos cuando visitan las ciudades y estas fuentes de datos permiten seguir sus actividades. Este trabajo tiene como objetivo seguir la huella digital de los turistas urbanos de nuevas fuentes de datos, asociadas a las redes sociales. Se utilizan dos fuentes: una comunidad de fotografías compartidas (Panoramio) y una red social (Twitter). La comparación entre la densidad de turistas según las dos fuentes de datos se realiza a partir de mapas, análisis de correlación (OLS) y análisis de autocorrelación espacial (Global Moran's I statistic y LISA). Finalmente, la integración de los datos se lleva a cabo a partir de la combinación de los clusters espaciales identificados en el análisis LISA para las dos fuentes de datos. Los resultados muestran que los datos aportados por las dos fuentes son en parte redundantes y en parte complementarios espacialmente, de forma que es posible caracterizar espacios turísticos polivalentes (cubiertos por las dos fuentes) y espacios especializados en una actividad. En el caso de estudio analizado (Madrid) se observa una fuerte presencia de turistas en el centro y una creciente especialización del centro a la periferia. La principal conclusión del trabajo es que para el seguimiento de los turistas en las ciudades no basta con utilizar una fuente de datos, sino que es necesario utilizar varias de forma complementaria

The market potential indicator is a commonly used tool in transport planning for evaluating the potential economic effects derived from improvements in transport infrastructures. The general assumption is that exports from a given region will rise with increased accessibility, thus benefiting economic activities. However, the specification of the market potential model is typically very simple and ignores both the impact of competing rivals and the role of international borders, which leads to unrealistic results. Spatial interaction models on bilateral trade have already proved that international trade is affected by multilateral resistance, borders, adjacency, language or currency. Nevertheless, apart from some recent analyses that simply calibrate the distance decay parameter from trade datasets, these variables have hardly been integrated into research on market potential. This paper sets out to demonstrate that more realistic results are obtained by calibrating the distance-decay parameter and introducing the impact of competing rivals and border effects into the market potential formulation. The proposed model is then applied to the assessment of the accessibility impacts of new road transport infrastructure in the European Union between 2001 and 2012, which shows that the greatest improvements in accessibility were experienced by peripheral countries with high road infrastructure investment.

This document describes the research developed in the INSIGHT project sub-work package WP4.4 Public Services Models, which is framed in the WP4 Theoretical Modelling work package. WP4 also includes research on retail models, housing models and housing-retail-public services interaction models. In the landscape left by the economic crisis, Public Services policies are extremely important but at the same time are dramatically limited. On the one hand, significant negative socio-demographic changes and imbalances, such as the increasing social segregation or the rising economic inequality, must be tackled through policies oriented to fostering public services or improving the existing ones. On the other hand, the economic decline has reduced public resources limiting the launching of these new services and affecting the delivery of the existing ones. In this scenario, the delivery of efficient Public Services is fundamental and the location of public facilities becomes crucial. The research explores the application of different location models to the four project case studies (Barcelona, London, Madrid and Rotterdam), creating new approaches and methodologies oriented to assisting policy makers and urban planners at some of the Policy Cycle stages (defined in the INSIGHT document D2.2 Urban Planning and governance: current practices and new challenges), such as the analysis of the current scenario, the definition of policies and measures and the evaluation of future scenarios.