BUSCADOR RECOLECTA

City nightlife supports a significant part of our social interactions, enhancing social wellbeing and community-building dynamics. COVID-19 impact on nightlife has been particularly dramatic and expanded over time. Few studies have analyzed this impact, and nightlife recovery remains even less explored. This study examines the
post-COVID-19 recovery of nightlife using mobile phone data in Kyoto (Japan) and Madrid (Spain), two cities with different culture and whose urban nightlife was heavily impacted. A detailed spatiotemporal analysis of the nightlife activity in both cities is conducted. The methodology is based on the estimation of the hourly presence of people over the course of the day, with a particular focus on evening and night hours. Kyoto, heavily dependent on tourism, faced a more pronounced and lasting impact, experiencing a decrease in the average presence of people in tourist areas by 51.9 % during COVID-19 and by 19.8 % after COVID-19. Despite fewer
constraints, revitalizing nightlife in Kyoto proves challenging compared to other sectors. Madrid reveals a shift in urban dynamics following the pandemic, influencing the utilization of different areas within the city, increasing the average presence of people by 15.5 % in the weekend activity area, from Monday to Thursday.

Changes in human mobility due to the COVID-19 pandemic have particularly impacted urban parks, altering their use patterns. The use of Big Data sources enables the quantification and tracking of changes, although few studies delve into their spatial representation and the socio-demographic characterisation of park users. In this research, we use anonymised cellular network-based data with associated user profile information to quantify and map the changes operated in trips to Madrid’s urban parks in a week of reference before and after the pandemic. Our results show a general decrease in trips to urban parks, especially by males in all age ranges. We also observe a marked decrease in trips by the high-income population. Finally, we have nicely presented some of these results in a composition of several maps that provide visual insight into the main changes.

Los datos GTFS del Consorcio Regional de Transportes de Madrid constituyen un conjunto estructurado de información sobre la red de transporte público, incluyendo horarios, rutas, paradas, frecuencias y correspondencias. Este formato estandarizado permite la integración con aplicaciones de movilidad y análisis de accesibilidad, facilitando el tratamiento automatizado y la interoperabilidad con otros sistemas de información geográfica o de planificación urbana.

Metadata for the Google Popular Times dataset. Access to the data requires a formal request.

This paper analyzes the accessibility of Curitiba, Brazil, by combining high-detail, big-data-informed automobile dynamic distance matrices from TomTom Traffic Stats and a bus network database - GTFS data - provided by the Curitiba City Council. Accessibility is measured dynamically, considering the changing conditions of congestion levels and bus frequencies, along with the daily variation of mobility patterns. The accessibility gap between private and bus modes is estimated, and its daily variation is analyzed regarding its spatial and temporal distribution. This study identifies places with greater public transport supply deficiencies and locations with the greatest needs for public transport improvements, suggesting priority intervention areas to improve the accessibility of the population while promoting a shift toward more sustainable transport modes. The outcomes show the relative advantage of cars versus buses and that a higher portion of Curitiba’s population lives in areas with high accessibility gaps.

Los datos GTFS de la ciudad de Curitiba recogen información detallada sobre la red de transporte público urbano, incluyendo rutas, paradas, horarios y frecuencias de paso. Este conjunto de datos, estructurado según el formato estándar GTFS, permite su uso en aplicaciones de planificación de movilidad, análisis espacial y estudios comparativos sobre accesibilidad y eficiencia del transporte.

Journey planners could be one of the most relevant aspects to consider when choosing and deciding our daily trips. However, many of these trip apps still do not consider the new forms of mobility that are emerging in cities, also known as micromobility services (shared bikes, mopeds and scooters). In this study, we pursue two main objectives. On one hand, we create a journey planner for micromobility in Madrid. On the other hand, we use the journey planner to estimate and analyze micromobility flow considering the origin and destination points of trips registered in 2019 from the three different shared modes. Our results involve a series of maps that illustrate how micromobility flow is distributed in the city and the different dynamics considering two scenarios (weekdays and weekends). The journey planner helps to visualize those streets where micromobility flow concentrates, making micromobility users more visible and thus promoting that their paths become safer, attracting new users to start using micromobility (positive loop). Also, the maps could help policy planners to allocate new infrastructure in the city where it is needed most.

Nightlife in urban areas is gaining interest due to its role as a stimulus of the local economy, tourism, safety, and public services. However, most studies analyse nighttime activity from a qualitative perspective and at a general urban scale, without going into a detailed spatial analysis. In this paper, we have used the spatio-temporal details of Google Places data, and the activity trends at a variety of facilities that provide Google Popular Times. We studied and mapped the recovery of nighttime activity in the city of Madrid after the pandemic restrictions. The results reveal that there was a significant decrease of over 80% in the activity levels of open premises, which also led to a decrease in their average occupancy rate. These reductions were particularly noticeable in the city center and during the late-night hours.