Katya Letunovsky’s presentation discusses the use of space-time data to analyze urban mobility and social interactions. Inspired by Swedish time geography, which visualizes individual activities over time in a 3D space, her team sought to adapt this concept to aggregated data while maintaining privacy standards. This led to the development of the chronotope system, which layers static maps over time to create a spatial-temporal volume that can be analyzed in various ways, such as by location or time period.
One notable application of the chronotope system was in Barcelona, where the team used it to study the interactions between tourists and locals. By examining social media data and mobile phone movements, they could identify times and places with high concentrations of both groups, highlighting potential areas of tension. This analysis helped visualize the impact of tourism on local communities, particularly during peak commuting times.
During the COVID-19 pandemic, the chronotope system proved invaluable for monitoring changes in mobility patterns. The Mobility Monitor tool was developed to show how people’s movements and dwell times in different city areas changed over time. For instance, areas with severe lockdown restrictions showed less movement, while others with lighter restrictions had more active streets. This visualization used color coding to indicate changes, with blue representing less change and brown indicating more significant changes. This tool provided insights into how different areas adapted to lockdown measures and where people were still moving actively.
In addition to mobility patterns, the team explored the impact of events on urban environments. By analyzing data before, during, and after events such as football matches, they could visualize how crowds gathered, dispersed, and moved across the city. This information is crucial for event planning and managing urban spaces during significant gatherings, helping to ensure smooth and safe movement of people.
The research also integrated qualitative methods from ethnographic studies to enhance the understanding of community dynamics. By identifying key metrics such as the frequency of visits, duration of stays, and proximity to home, the team developed a comprehensive map of community networks and important local spaces, referred to as "foams." These foams represent places that matter to local communities, needing frequent and substantial visits and being located near people's homes.
The combined approach of qualitative and quantitative data analysis provides a richer understanding of urban mobility and social interactions. For example, the team’s analysis of changes in infection rates over time, combined with mobility data, allowed them to map areas with high and low social interaction, informing public health strategies and urban planning.
By using the chronotope system and the concept of foams, the research provides valuable insights into how urban spaces are utilized and how they can be optimized for better social interactions and public health outcomes. The goal is to create more resilient and inclusive urban environments that cater to the needs of diverse populations.
Katya’s work underscores the importance of integrating different types of data and methodologies to understand the complexities of urban life. The innovative use of space-time data visualization offers a powerful tool for urban planners and policymakers, enabling them to make informed decisions that enhance the livability and functionality of cities.