Person: Romanillos Arroyo, Gustavo
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First Name
Gustavo
Last Name
Romanillos Arroyo
Affiliation
Universidad Complutense de Madrid
Faculty / Institute
GeografÃa e Historia
Department
GeografÃa
Area
GeografÃa Humana
Identifiers
25 results
Search Results
Now showing 1 - 10 of 25
Item The pulse of the cycling city: visualising Madrid bike share system GPS routes and cycling flow(Journal of Maps, 2018) Romanillos Arroyo, Gustavo; Moya Gómez, Borja; Zaltz-Austwick, Martin; LamÃquiz-Daudén, Patxi J.With the aim of shifting towards a more sustainable urban transport model, cycling mobility isbeing promoted in many cities and, in consequence, Bike Share Systems have been the focus ofattention in an increasing number of studies over the past years. However, we know very littleabout the impact of these BSS in cities beyond the station level. What paths do cyclists follow?What are the most important urban arteries in terms of cycling flow? These are importantquestions to be addressed in order to implement policies and infrastructure where they arereally needed. The main goal of this study is to visualise the cycling flow derived fromMadrid BSS activity, obtained by processing over 250,000 GPS routes, and to provide ananalysis of how this flow is distributed across the urban street network at different moments.We explore the diverse levels of use over the course of the day, and during the weekdays,weekends or holidays, as well as the different cycling patterns of frequent and occasional users.Item Uncovering spatiotemporal micromobility patterns through the lens of space–time cubes and GIS tools(Journal of Geographical Systems, 2023) Arias Molinares, Daniela; GarcÃa Palomares, Juan Carlos; Romanillos Arroyo, Gustavo; Gutiérrez Puebla, JavierIn the past ten years, cities have experienced a burst of micromobility services as they offer a flexible transport option that allows users to cover short trips or the first/last mile of longer trips. Despite their potential impacts on mobility and the fact that they offer a cleaner, more environmentally friendly alternative to private cars, few efforts have been devoted to studying patterns of use. In this paper we introduce new ways of visualizing and understanding spatiotemporal patterns of micromobility in Madrid based on the conceptual framework of Time-Geography. Hägerstrand’s perspectives are taken and adapted to analyze data regarding use of micromobility, considering each trip departure location (origins) obtained from GPS records. The datasets are collected by three of the most important micromobility operators in the city. Trip origins (points) are processed and visualized using space–time cubes and then spatially analyzed in a GIS environment. The results of this analysis help to identify the landscape of micromobility in the city, detecting hotspot areas and location clusters that share similar behavior throughout space and time in terms of micromobility departures. The methods presented can have application in other cities and could offer insights for transport planners and micromobility operators to better inform urban planning and transportation policy. Additionally, the information could help operators to optimize vehicle redistribution and maintenance/recharging tasks, reducing congestion and increasing efficiency.Item Cómo aplicar Big Data en la planificación del transporte: El uso de datos de GPS en el análisis de la movilidad urbana(2020) Gutiérrez Puebla, Javier; BenÃtez, Carolina; GarcÃa Palomares, Juan Carlos; Romanillos Arroyo, Gustavo; Rubinstein da Silva, ElÃas; Leaño, Juan Manuel; Ribeiro, Karisa Maia; Scholl, Lynn; Moya Gómez, Borja; Condeço Melhorado, Ana Margarida; BenÃtez, CarolinaLa presente nota técnica explica de qué manera el análisis de grandes volúmenes de datos de la telefonÃa móvil puede aplicarse a la planificación del transporte y la infraestructura urbana. La actividad de los usuarios permite conocer su huella digital y, por lo tanto, entender sus trayectorias espacio-temporales de manera desagregada y extrapolada, estableciendo matrices de origen destino. La producción de grandes volúmenes de datos masivos, Big Data, abre interesantes posibilidades para entender los flujos de movilidad de nuestras ciudades de la región y su complementariedad con los métodos tradicionales de recolección de datos, como los son las encuestas de movilidad domiciliarias de origen destino de viajes, permitiendo disponer de información siempre actualizada y en menor tiempo. La nota técnica agrupa y sistematiza los conocimientos generados por especialistas e investigadores de distintos paÃses del mundo; y analiza 6 casos de éxito realizados de implementación en distintas ciudades latinoamericanas y en otros ámbitos internacionales, donde se indica cómo se han obtenido esas matrices de viajes y cuáles han sido sus aplicaciones.- Project number: 79
Item SIGUE - Materiales para actividades no presenciales en asignaturas vinculadas a los Sistemas de Información Geográfica (SIG): recopilación, preparación y evaluación(2017) GarcÃa Palomares, Juan Carlos; Gutiérrez Puebla, Javier; RodrÃguez Moya, Juana MarÃa; MÃnguez GarcÃa, Carmen; de Andrés de Pablo, Nuria; Tanarro GarcÃa, Luis Miguel; VÃa GarcÃa, Miguel; Salas Olmedo, MarÃa Henar; Moya Gómez, Borja; Romanillos Arroyo, Gustavo; Osorio Arjona, JoaquÃn; Fernández Fernández, José MarÃa Item The city turned off: Urban dynamics during the COVID-19 pandemic based on mobile phone data(Applied Geography, 2021) Romanillos Arroyo, Gustavo; GarcÃa Palomares, Juan Carlos; Moya Gómez, Borja; Gutiérrez Puebla, Javier; Torres, Javier; López, Mario; Cantú-Ros, Oliva G.; Herranz, RicardoDue to the rapid expansion of the COVID-19 pandemic, many countries ordained lockdowns, establishing different restrictions on people’s mobility. Exploring to what extent these measures have been effective is critical in order to better respond to similar future scenarios. This article uses anonymous mobile phone data to study the impact of the Spanish lockdown on the daily dynamics of the Madrid metropolitan area (Spain). The analysis has been carried out for a reference week prior to the lockdown and during several weeks of the lockdown in which different restrictions were in place. During these weeks, population distribution is compared during the day and at night and presence profiles are obtained throughout the day for each type of land use. In addition, a spatial multiple regression analysis is carried out to determine the impact of the different land uses on the local population. The results in the reference week, pre-COVID-19, show how the population in activity areas increases in each time slot on a specific day and how in residential areas it decreases. However, during the lockdown, activity areas cease to attract population during the day and the residential areas therefore no longer show a decrease. Only basic essential commercial activities, or others that require the presence of workers (industrial or logistics) maintain some activity during lockdown.Item Patrones espaciales de concentración de turistas en Madrid a partir de datos geolocalizados de redes sociales: Panoramio y Twitter(Aplicaciones geotecnológicas para el desarrollo económico sostenible., 2016) GarcÃa Palomares, Juan Carlos; Gutiérrez Puebla, Javier; Romanillos Arroyo, Gustavo; Salas Olmedo, MarÃa Henar; Galacho Jiménez, Federico BenjamÃn; VÃas MartÃnez, Jesús; Reyes Corredera, SergioEl 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 fotografÃas 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 turÃsticos 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- Project number: 230
Item BDinnova – Formación del profesorado en herramientas de manejo, análisis y visualización de BigData geolocalizado(2019) GarcÃa Palomares, Juan Carlos; Gutiérrez Puebla, Javier; RodrÃguez Moya, Juana MarÃa; MÃnguez GarcÃa, MarÃa del Carmen; Michelini, Juan José; GarcÃa Ruiz, Yolanda; Condeço Melhorado, Ana; Romanillos Arroyo, Gustavo; VÃa GarcÃa, Miguel; Jiménez Gómez, Isidro; Stepniak, Marcin; Moya Gómez, Borja; Osorio Arjona, JoaquÃn Item New Data and Computational Methods Opportunities to Enhance the Knowledge Base of Tourism(Handbook of Computational Social Science for Policy, 2023) Romanillos Arroyo, Gustavo; Moya Gómez, Borja; Bertolini, Eleonora; Fontana, Matteo; Gabrielli, Lorenzo; Signorelli, Serena; Vespe, MicheleTourism is becoming increasingly relevant at different levels, intensifying its impact on the environmental, the economic and the social spheres. For this reason, the study of this rapidly evolving sector is important for many disciplines and requires to be quickly updated. This chapter provides an overview and general guidelines on the potential use of new data and computational methods to enhance tourism’s knowledge base, encourage their institutional adoption and, ultimately, foster a more sustainable tourism.First, the chapter delivers a brief review of the literature on new data sources and innovative computational methods that can significantly improve our understanding of tourism, addressing the big data revolution and the emergence of new analytic tools, such as artificial intelligence (AI) or machine learning (ML). Then, the chapter provides some guidelines and applications of these new datasets and methods, articulated around three topics: (1) measuring the environmental impacts of tourism, (2) assessing the socio-economic resilience of the tourism sector and (3) uncovering new tourists’ preferences, facilitating the digital transition and fostering innovation in the tourism sector.- Project number: 165
Item COLABORA – Aprendizaje colaborativo en geografÃa para la generación y uso de datos geolocalizados(2020) Condeço-Melhorado, Ana; GarcÃa Palomares, Juan Carlos; Gutiérrez Puebla, Javier; López López, MarÃa Victoria; Michelini, Juan José; Moya Gómez, Borja; Osorio Arjona, JoaquÃn; Pérez Campaña, RocÃo; RodrÃguez Moya, Juana MarÃa; Romanillos Arroyo, Gustavo; Stepniak, MarcÃn; Talavera GarcÃa, RubénEste proyecto de innovación docente ha tenido como objetivo general emplear diferentes técnicas y actividades que fomenten el aprendizaje colaborativo en la generación, tratamiento y uso de los datos geolocalizados. Además, ha permitido la formación del profesorado en metodologÃas de aprendizaje colaborativo centradas en el uso de datos geolocalizados en relación con las tecnologÃas de la información geográfica (TIG), con el fin de incorporar este tipo de herramientas en sus asignaturas. Item Collaborative mapping of emerging cities in developing countries: the "León Emergente" project(Journal of Maps, 2016) Romanillos Arroyo, GustavoIn the expanding constellation of collaborative map-making initiatives, a growing number of small local projects coexist along with more ambitious and global ones. In developing countries, their existence is not only compatible and complementary, but also necessary, since they meet different needs and pursue diverse and essential objectives, in addition to collecting and sharing geo-located data. In this context, this paper describes the León Emergente initiative, a collaborative living atlas for the city of León in Nicaragua. The results are presented through two main maps that illustrate, for the first time, the formal and informal economic activity of the city as well as the health facilities in relation to the distribution of population across the city. The paper also describes the Leon Emergente online platform and presents a number of online maps that not only represent, but also collect data on different urban aspects and dynamics.