Usos urbanos y actividades económicas a través de Google Places

El espacio público urbano como lugar de encuentro social ha sido, tradicionalmente, objeto de estudio desde distintas disciplinas cuyas metodologías han consistido, principalmente, en la recogida de datos a partir de la observación, encuestas, mediciones, entre otras. Hoy en día, las nuevas tecnologías ofrecen la posibilidad de incorporar nuevas metodologías en las que el estrato virtual de las relaciones sociales toma un gran protagonismo. Particularmente, el campo de la geolocalización social abre paso a la generación una gran cantidad de información que hoy en día supone una importante fuente de datos para analizar fenómenos urbanos desde distintas escalas y aproximaciones. A través de la red social Google Places estudiaremos las actividades que tienen lugar en planta baja de las edificaciones colindantes a 6 ejes de grandes ciudades

Urban and economic activities in metropolitan structuring axes. The contribution of Google Places geolocated data

Los ejes viarios metropolitanos son espacios de centralidad urbana y de oportunidad para promover una mejor conectividad entre las distintas partes del continuo urbano. En este sentido, la caracterización funcional de seis ejes representativos en Madrid, Barcelona, París, Londres, Nueva York y Ciudad de México permite obtener un diagnóstico actual sobre la densidad y diversidad de actividades económicas y urbanas, con el fin identificar aspectos clave sobre los que incidir para mejorar su estructura funcional y social. Para ello, se propone un método que adopta los datos geolocalizados de la red social Google Places como principal fuente de información. De la investigación se deducen importantes similitudes en el carácter funcional de los ejes, entre otras, la predominancia de las actividades relacionadas con los servicios y el comercio o la mayor diversidad de actividades económicas y urbanas en los espacios más centrales. Pero también se identifican diferencias, como son la especialización de determinadas actividades características en cada eje metropolitano o la diferencial relación entre la densidad de población y cantidad de actividades, tanto en términos de densidad como en cuantificación lineal. En definitiva, el método propuesto abre nuevas posibilidades para la planificación estratégica de actividades económicas y urbanas en ámbitos metropolitanos.Metropolitan road axes are spaces of urban centrality and opportunity to promote a greater connectivity between different parts of the urban continuum. In this sense, the functional characterization of six representative axes in Madrid, Barcelona, Paris, London, New York and Mexico City allows obtaining a current analysis of the density and diversity of economic and urban activities to identify key aspects over which to influence to improve their functional and social structure. For this, a method is proposed that adopts the geolocation data from Google Places social network as a main source of information. From the research, important similarities in the functional character of the axes are deduced, among other the predominance of activities related to services and shopping or the greater diversity of economic and urban activities in more central spaces. But differences are also identified, such as the specialization of certain activities characteristic in each metropolitan axis or the differential relationship between population density and the number of activities both in terms of density and linear quantification. All in all, the method proposed opens new possibilities for the strategic planning of economic and urban activities in metropolitan areas.Esta investigación ha recibido financiación de la Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital de la Generalitat Valenciana y el Fondo Social Europeo (ACIF/2020/173)

Reading Urban Transformation Based on Geolocated Crowdsourced Data

Social and economic instability in cities caused by the pandemic emergency has highlighted the necessity of carrying out diagnoses to identify courses of action for the purpose of reducing the vulnerability of urban areas in the face of future crisis. This research aims to identify how the impact of the COVID-19 pandemic and the measures adopted have influenced urban and economic activities and the use, presence and preferences of urban public spaces. Specifically, an analysis in several cities before and after the most critical phases of the pandemic is proposed based on virtual social network geodata. Since each individual represents a node of information exchange, it is hypothesized that a comparison between the data generated before and after the pandemic offer a first glance at how changes in the social (collective behaviors and preferences) and physical (economic and urban activities) dimensions in urban environments have been produced. The results provide a descriptive and contrasted analysis that evidences the relevance of using crowdsourced data for monitoring the changes and transformations that took place as a result of the pandemic crisis in order to inform decision-making for future urban policies and actions

Scoping out urban areas of tourist interest though geolocated social media data: Bucharest as a case study

Social media data has frequently sourced research on topics such as traveller planning or the factors that influence travel decisions. The literature on the location of tourist activities, however, is scarce. The studies in this line that do exist focus mainly on identifying points of interest and rarely on the urban areas that attract tourists. Specifically, as acknowledged in the literature, tourist attractions produce major imbalances with respect to adjacent urban areas. The present study aims to fill this research gap by addressing a twofold objective. The first was to design a methodology allowing to identify the preferred tourist areas based on concentrations of places and activities. The tourist area was delimited using Instasights heatmaps information and the areas of interest were identified by linking data from the location-based social network Foursquare to TripAdvisor’s database. The second objective was to delimit areas of interest based on users’ existing urban dynamics. The method provides a thorough understanding of functional diversity and the location of a city’s different functions. In this way, it contributes to a better understanding of the spatial distribution imbalances of tourist activities. Tourist areas of interest were revealed via the identification of users’ preferences and experiences. A novel methodology was thus created that can be used in the design of future tourism strategies or, indeed, in urban planning. The city of Bucharest, Romania, was taken as a case study to develop this exploratory research.Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This research has been partially funded by the Valencian Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital, Generalitat Valenciana and the European Social Fund (ACIF/2020/173); and by the University of Alicante—Vicerrectorado de Investigación (GRE 21-15)

The urban impact of COVID-19: six neighbourhoods, three cities and three countries in social network data

La situación de emergencia sanitaria COVID-19 ha impactado múltiples dimensiones de la compleja estructura física, social, funcional y económica de las ciudades. Esta investigación lleva a cabo un diagnóstico comparado sobre algunos cambios y transformaciones que se han producido en el entorno urbano a causa de la crisis y que se reflejan en los datos de redes sociales geolocalizadas. Para ello, los datos de Google Places y Twitter se adoptan como principal fuente de información. Se propone un método mixto, cualitativo y cuantitativo, para analizar el aumento y la pérdida de actividad económica (Google Places) y presencia humana (Twitter) en dos periodos, pre y pos-pandemia. Como caso de estudio, se analizan dos ámbitos con condiciones socioeconómicas muy diferenciadas en tres ciudades localizadas en países que han adoptado distintas medidas de contención de la pandemia –Valencia en España; Ciudad de México en México y Gotemburgo en Suecia–. El diagnóstico informado por estas redes sociales es de gran utilidad para formular estrategias útiles tanto para identificar los cambios que se han venido produciendo como para afrontar futuros escenarios disruptivos.The COVID-19 health emergency has impacted multiple dimensions of the complex physical, social, functional and economic structure of cities. This research encompasses a comparative diagnosis of some of the changes and transformations that have occurred in the urban environment due to the crisis and are reflected in geolocalised social network data. For this purpose, data from Google Places and Twitter are adopted as the main source of information. A mixed qualitative and quantitative methodology is proposed to analyse the increase and loss of economic activity (Google Places) and human presence (Twitter) in two periods: pre- and post-pandemic. As a case study, two areas with very different socio-economic conditions are analysed in three cities located in countries that adopted different pandemic restrictions measures - Valencia in Spain, Mexico City in Mexico and Gothenburg in Sweden. The diagnosis reported by these social networks is of great use in formulating useful strategies both for identifying the changes that have been taking place and for dealing with future disruptive scenarios.Esta investigación ha sido cofinanciada por la Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital. Generalitat Valenciana, España (GV/2021/177) y la Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital, Generalitat Valenciana, y el Fondo Social Europeo (ACIF/2020/173)

The Geography of Social Media Data in Urban Areas: Representativeness and Complementarity

This research sheds light on the relationship between the presence of location-based social network (LBSN) data and other economic and demographic variables in the city of Valencia (Spain). For that purpose, a comparison is made between location patterns of geolocated data from various social networks (i.e., Google Places, Foursquare, Twitter, Airbnb and Idealista) and statistical information such as land value, average gross income, and population distribution by age range. The main findings show that there is no direct relationship between land value or age of registered population and the amount of social network data generated in a given area. However, a noteworthy coincidence was observed between Google Places data-clustering patterns, which represent the offer of economic activities, and the spatial concentration of the other LBSNs analyzed, suggesting that data from these sources are mostly generated in areas with a high density of economic activities

Nuevas herramientas para la enseñanza del Urbanismo. La incorporación de los Sistemas de Información Geográfica en la docencia universitaria

Los Sistemas de Información Geográfica (SIG) son herramientas informáticas que permiten realizar análisis geoespaciales a escala urbana o territorial. Esta experiencia docente incorpora actividades formativas encaminadas al aprendizaje de herramientas SIG en el contexto de los grupos con docencia en inglés de cuatro asignaturas del Área de Urbanística y Ordenación del Territorio impartidas en la titulación del Grado en Fundamentos de la Arquitectura de la Universidad de Alicante. El objetivo de esta experiencia es que, mediante ejercicios prácticos enfocados en los objetivos y contenidos de cada asignatura, los estudiantes adquieran nuevos conocimientos acerca de los SIG y se familiaricen con su uso a lo largo de su trayectoria académica de cara a su futuro profesional. Los resultados evidencian [1] el adecuado seguimiento de las sesiones por parte del alumnado, [2] la aplicación de los resultados y los contenidos de las sesiones prácticas al desarrollo de los trabajos propuestos en cada asignatura; y [3] el interés de una parte del alumnado por el uso y desarrollo de nuevas habilidades con estas herramientas de forma autónoma. Esta experiencia permite seguir definiendo una propuesta metodológica para la mejora del proceso de aprendizaje de las herramientas SIG en las asignaturas de Urbanismo y adecuar los contenidos de las sesiones al desarrollo progresivo de nuevas habilidades por parte del alumnado.Esta investigación ha recibido financiación de la Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital de la Generalitat Valenciana y el Fondo Social Europeo (ACIF/2020/173)

Breakout Games as a teaching tool in Urban Planning: a didactic strategy

Gamification is a tool to promote student motivation in Higher Education. This teaching experience proposes the implementation of gamification, specifically Breakout Games, as a way to reinforce and assimilate certain concepts related to Urban Planning among Architecture students, while playing and working collaboratively. The activity involves the design of different games based on concept associations, which must be correctly solved in order to escape from the classroom, as well as a final evaluation based on students’ experience. Breakout Games format has been positively received by students, who express an overall satisfaction with this teaching experience, as they identify key aspects and detect difficulties in completing the tasks, thus reinforcing concepts from the course.La gamificación en la enseñanza universitaria es una herramienta para promover la motivación del alumnado en las aulas. Esta experiencia docente propone la incorporación de la gamificación y, en concreto, del formato Escape Room como medio para, a través del juego y el trabajo colaborativo, reforzar el aprendizaje y la asimilación de algunos conceptos relacionados con el Urbanismo entre los estudiantes de Arquitectura. La actividad incluye el diseño de diferentes juegos basados en la asociación de conceptos, los cuáles deben ser resueltos correctamente para poder escapar del aula, así como una evaluación final por parte de los estudiantes sobre su experiencia. El formato Escape Room ha sido valorado positivamente por el alumnado que se muestra satisfecho, de forma general, con esta experiencia docente, y que les ha permitido identificar aspectos clave, así como detectar dificultades en la realización de las pruebas, reforzando así conceptos de la asignatura

The Unexploited Potential of Converting Rail Tracks to Greenways: the Spanish Vías Verdes

The reuse of Spain’s obsolete railway infrastructure as greenways, namely vías verdes, reflects a Europe-wide territorial strategy, which has resulted in the refurbishment of more than 2500 km of abandoned Spanish railway lines. The potential of these vías verdes as strategical green infrastructure linkers between settlements and their peripheral natural environments is assessed in two Spanish case studies of Girona and Alicante. The territorial elements that affect vías verdes (natural landscape areas, urban settlements and population) are obtained from public administration sources. Additionally, users’ activity through the Wikilock social network is considered. The spatial analysis shows the role of vías verdes in terms of landscape value, accessibility and planning strategy: the itineraries of the vías verdes connect different valuable natural areas with diverse landscape patterns in near proximity to urban nuclei; more than 65% of the population can access a vía verde in less than 200 metres. Moreover, it offers the opportunity to complete a network which could link urban nuclei and their natural periphery through the refurbishment of the remaining stretches. Despite the fact that the full potential of these vías verdes as strategical greenways has not been fully considered in the green infrastructure planning, these corridors could meet environmental, cultural and social sustainable goals

The Geography of Social Media Data in Urban Areas: Representativeness and Complementarity

This research sheds light on the relationship between the presence of location-based social network (LBSN) data and other economic and demographic variables in the city of Valencia (Spain). For that purpose, a comparison is made between location patterns of geolocated data from various social networks (i.e., Google Places, Foursquare, Twitter, Airbnb and Idealista) and statistical information such as land value, average gross income, and population distribution by age range. The main findings show that there is no direct relationship between land value or age of registered population and the amount of social network data generated in a given area. However, a noteworthy coincidence was observed between Google Places data-clustering patterns, which represent the offer of economic activities, and the spatial concentration of the other LBSNs analyzed, suggesting that data from these sources are mostly generated in areas with a high density of economic activities.This research was co-funded by (i) Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital, Generalitat Valenciana and European Social Fund (ACIF/2020/173) and (ii) Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital, Generalitat Valenciana (GV/2021/177)