Person:
Gutiérrez Puebla, Javier

First Name

Javier

Last Name

Gutiérrez Puebla

Affiliation

Universidad Complutense de Madrid

Faculty / Institute

Geografía e Historia

Department

Geografía

Area

Geografía Humana

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Now showing 1 - 10 of 11

Aplicación de técnicas de ordenación del territorio al area metropolitana de Madrid : el análisis del comportamiento espacial de la población
(Universidad Complutense de Madrid, 2015) Gutiérrez Puebla, Javier
The city turned off: Urban dynamics during the COVID-19 pandemic based on mobile phone data
(Elsevier, 2021-07-28) Romanillos Arroyo, Gustavo; García Palomares, Juan Carlos; Moya Gómez, Borja; Gutiérrez Puebla, Javier; Torres, Javier; López, Mario; Cantú-Ros, Oliva G.; Herranz, Ricardo
Due 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.
Towards a new urban geography of expenditure: Using bank card transactions data to analyze multi-sector spatiotemporal distributions
(Elsevier, 2022-08-10) Carpio Pinedo, Jose; Romanillos Arroyo, Gustavo; Aparicio, Daniel; Hernández Martín-Caro, María Soledad; García Palomares, Juan Carlos; Gutiérrez Puebla, Javier
The 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.
Exploring the spatio-temporal dynamics of moped-style scooter sharing services in urban areas
(Elsevier, 2021-09-14) Arias Molinares, Daniela; Romanillos Arroyo, Gustavo; García Palomares, Juan Carlos; Gutiérrez Puebla, Javier
Spain 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.
Exploring night and day socio-spatial segregation based on mobile phone data: The case of Medellin (Colombia)
(Elsevier, 2021-06-14) Moya Gómez, Borja; Stępniak, Marcin; García Palomares, Juan Carlos; Frías Martínez, Enrique; Gutiérrez Puebla, Javier
Social segregation research has a long tradition in urban studies. Usually, these studies focus on the residential dimension, using official registries (e.g., census data), which show population distribution at night. Nevertheless, these studies disregard the fact that the population in cities is highly mobile, and its spatial distribution dramatically changes between night and day. The emergence of new data sources (Big Data) creates perfect conditions to consider segregation as a process, by providing the opportunity to dynamically analyse temporal changes in social segregation. This study uses mobile phone data to analyse changes in social segregation between night and day. Our case study is Medellin (Colombia), a highly socially-segregated, South American city, where social integration policies are being developed, targeting the population in the most disadvantaged neighbourhoods. We use several complementary indicators of social segregation, supplementing them with mobility indicators that help explain changes in spatial segregation between night and day. The main conclusion is that daily mobility reduces the concentration of a particular group within neighbourhoods and increases the degree of social mixing (exposure) in local settings. This greater social exposure softens local contrasts (outliers) and increases the extension of spatial clusters (positive spatial autocorrelation), so general clustering trends emerge more clearly. The study also makes clear that increased exposure during the day mainly occurs due to the mobility of the low-income population, who are the most likely to leave their neighbourhood during the day and who travel the greatest distances to the most diverse set of destinations.
Exploring micromobility services: Characteristics of station-based bike-sharing users and their relationship with dockless services
(Elsevier, 2021-12) Arias Molinares, Daniela; Julio, Raky; García Palomares, Juan Carlos; Gutiérrez Puebla, Javier
As shared mobility burst in different cities as one of the most innovative transport solutions, few efforts are found related to the exploration of dockless services and more specifically, to analysing opinions from those users that are subscribed to both, docked and dockless services simultaneously. Therefore, our study explores station-based bike-sharing users’ preferences for other dockless services. To that end, we firstly divide the sample into two groups: Group 1 being users that only use Bicimad (Madrid’s station-based bike-sharing) and Group 2 being Bicimad users that are also subscribed to other dockless services. Results show that both groups have similar users’ profiles according to their socio-demographic characteristics (male, 35–49 years old, well-educated, medium income and employee), although Group 2 shows a slightly higher rate of under-26-year-olds, which could be supporting the idea that these services are more attractive for the youngest. Moreover, our findings show that approximately 12% of station-based bike-sharing users are also subscribed to dockless services. At a higher rate, those subscribed to dockless services live outside the city centre, where the bike-sharing system is not available, showing that the two models may essentially have a complemental relationship, especially in the peripheries. Finally, results point at the importance of bike-sharing systems having a positive impact on its users, as they are keener to try new dockless options and a reduced willingness to use private cars. Insights may help to better inform public policy and promote the use of shared micromobility.
COLABORA – Aprendizaje colaborativo en geografía para la generación y uso de datos geolocalizados
(2020-06-22) Condeço-Melhorado, Ana; García Palomares, Juan Carlos; Gutiérrez Puebla, Javier; López López, María Victoria; Michelini, Juan José; Moya Gómez, Borja; Osorio Arjona, Joaquín; Pérez Campaña, Rocío; Rodríguez Moya, Juana María; Romanillos Arroyo, Gustavo; Stepniak, Marcín; Talavera García, Rubén
Este 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 metodologías de aprendizaje colaborativo centradas en el uso de datos geolocalizados en relación con las tecnologías de la información geográfica (TIG), con el fin de incorporar este tipo de herramientas en sus asignaturas.
BLOGtGIS: Espacio virtual de difusión y discusión sobre material docente y otros contenidos de interés académico relacionados con los Sistemas de Información Geográfica
(2021-09-28) Romanillos Arroyo, Gustavo; Gutiérrez Puebla, Javier; García Palomares, Juan Carlos; Condeço Melhorado, Ana Margarida; Pérez Campaña, Rocío; Arias Molinares, Daniela; Barros Sulca, Diana Carolina; Santiago Iglesias, Enrique
Memoria 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".
SIGUE - Materiales para actividades no presenciales en asignaturas vinculadas a los Sistemas de Información Geográfica (SIG): recopilación, preparación y evaluación
(2017-06-25) García Palomares, Juan Carlos; Gutiérrez Puebla, Javier; Rodríguez Moya, Juana María; Mínguez García, Carmen; de Andrés de Pablo, Nuria; Tanarro García, Luis Miguel; Vía García, Miguel; Salas Olmedo, María Henar; Moya Gómez, Borja; Romanillos Arroyo, Gustavo; Osorio Arjona, Joaquín; Fernández Fernández, José María
BDinnova – Formación del profesorado en herramientas de manejo, análisis y visualización de BigData geolocalizado
(2019-06-13) García Palomares, Juan Carlos; Gutiérrez Puebla, Javier; Rodríguez Moya, Juana María; Mínguez García, María del Carmen; Michelini, Juan José; García Ruiz, Yolanda; Condeço Melhorado, Ana; Romanillos Arroyo, Gustavo; Vía García, Miguel; Jiménez Gómez, Isidro; Stepniak, Marcin; Moya Gómez, Borja; Osorio Arjona, Joaquín