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
9 results
Search Results
Now showing 1 - 9 of 9
- Project number: 196
Item BLOGtGIS: Espacio virtual de difusión y discusión sobre material docente y otros contenidos de interés académico relacionados con los Sistemas de Información Geográfica(2021) Romanillos Arroyo, Gustavo; Gutiérrez Puebla, Javier; GarcÃa Palomares, Juan Carlos; Condeço Melhorado, Ana Margarida; Pérez Campaña, RocÃo; Arias Molinares, Daniela; Barros Sulca, Diana Carolina; Santiago Iglesias, EnriqueMemoria del Proyecto de Innovación Docente "BLOGtGIS: Espacio virtual de difusión y discusión sobre material docente y otros contenidos de interés académico relacionados con los Sistemas de Información Geográfica". Item Towards a new urban geography of expenditure: Using bank card transactions data to analyze multi-sector spatiotemporal distributions(Cities, 2022) Carpio Pinedo, Jose; Romanillos Arroyo, Gustavo; Aparicio, Daniel; Hernández MartÃn-Caro, MarÃa Soledad; GarcÃa Palomares, Juan Carlos; Gutiérrez Puebla, JavierThe spatial distribution of commercial activities is vital to support healthy lifestyles and to achieve livable public spaces and environmental, social and economic sustainability in our cities. However, commercial activities require a constant flow of expenditure for their own viability. As a result, understanding the spatial and temporal distribution of expenditure is fundamental, although the lack of detailed, complete data sources has impeded this task until now. Bank card data paves the way for a new urban geography of expenditure, thanks to its fine spatial and temporal granularity along with the uniform coverage of all commercial sectors. In this paper, we analyze temporal, spatial, and spatiotemporal distributions of expenditure at the intraurban scale of the city of Madrid (Spain), combining spatial statistical tools (Getis-Ord General for global autocorrelation and Getis-Ord Gi* hot spot analysis for local autocorrelation) with k-means cluster analysis and spatiotemporal tools (Time Series Clustering analysis and Temporal Hot Spot Analysis). Our analysis confirms the strong center-periphery gradient described in previous literature, but with a CBD integrated by distinct specialized areas. The paper demonstrates that bank card data has a great potential to support a new geography of expenditure that could strengthen decision-making in planning and retailing.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.Item Exploring the spatio-temporal dynamics of moped-style scooter sharing services in urban areas(Journal of Transport Geography, 2021) Arias Molinares, Daniela; Romanillos Arroyo, Gustavo; GarcÃa Palomares, Juan Carlos; Gutiérrez Puebla, JavierSpain is one of the countries with the highest shared mobility fleet in the world. The shared use of motorcycles, also known as moped-style scooter sharing, has spread far and wide throughout the country at a dramatic pace in recent years. Despite its increasing popularity and impact on urban mobility, efforts devoted to the study of its spatio-temporal travel patterns are still scant. Based on the analysis of GPS records of an operator present in seven Spanish cities, this study aims to contribute to this research gap by analysing mopeds’ location patterns over time and assessing how different dynamics influence its usage level and self-balance potential. Our study is replicable to different cities and different shared modes, since we propose a methodology to identify the most important origins and destinations over time and analyse the system’s self-balance capacity based on spatial autocorrelation tools. These insights are useful for operators to adjust and optimise vehicle distribution routes and maintenance/recharge tasks, decreasing congestion and increasing efficiency. The results may also be helpful for policy makers when planning and offering effective policies and infrastructure to encourage shared mobility.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 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.- Project number: 424
Item Realidad Aumentada para el aprendizaje en asignaturas vinculadas a las TecnologÃas de la Información Geográfica (TIG-RA)(2023) Talavera GarcÃa, Rubén; Condeço Melhorado, Ana Margarida; GarcÃa Palomares, Juan Carlos; Gutiérrez Puebla, Javier; Michelini, Juan José; Moya Gómez, Borja; Pérez Campaña, RocÃo; Romanillos Arroyo, Gustavo; Hewitt, Richard James; Santiago Iglesias, Enrique; Cara Santana, Yeray; RodrÃguez Pacheco, Farid Leonardo 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.