New relationships between activities and locations

Currently, one of the important devices that collects data and transforms it into digital maps is the mobile phone. The Digital Skin (Jagdish, Re-Mapping the City) can be comprised of many different layers, each one having different temporal properties and entities that it represents. Each layer is the result of collaborative annotation of spaces done by citizens using mobile devices, or by other dedicated mapping efforts which result in artefacts. Technologies being developed and tested include so-called Personal Guidance Systems (PGS) that incorporate detailed spatial databases, GPSs, and inertial compasses, combined into a unit worn or carried by the traveller (Montello & Sas, 2006); video recording; or recording of the subject’s verbal descriptions (Lahav & Mioduser, 2000). More and more pieces of data are now tagged with geographic references – such as geographic coordinates, addresses, and place names – and more and more often these data are accessible through maps (Caquard, 2013).
Several questions to be addressed: How do these new layers of information influence travel behaviour? How do these new layers of information influence the mental maps of different social and age groups? Will it reinforce social exclusion or improve social inclusion?
How to adjust our transport and land-use planning strategies?
Activity space is the part of the environment which a traveller is using for his/her activities, and can also be thought of as an approximation of the mental map of the traveller (Schönfelder & Axhausen, 2003). The mental map stresses the spatial knowledge about activity opportunities and their relative positions and connections, while the activity repertoire looks at the type, quality and costs of different activities or activity types at different locations. Mobile communications disconnect activities from specific locations, leading to increasing flexibility in timing and location of activities: mobility patterns are less structured and less predictable. This has made it even more difficult to assess travel decision processes.

• Understand the non-work travel behaviour of individuals and households by using additional dimension of mobility: activity spaces.

• The size of the area is an indicator for the dispersion of visited locations and may be used to compare the dispersion between travellers or of one respondent on different days of the week.

• The main driver of the size of the activity spaces is the overall number of unique locations visited by the respondents and to a lesser extent, their socio-demographic characteristics.

• Lifestyles influence activity spaces even when the life situation is controlled, but, the impact of life situation on activity spaces is higher than the impact of lifestyle.

Activity Theory focuses on the constituent influences on activity and places; the participants and their goals in ‘systems of activity’ that includes motivations and goals, ideas and values, the community context and the artefacts that they create (Sclater & Lally, 2014). Hence, the activity system becomes the unit of analysis.

The early literature in transport and geography on activity spaces was based on cross-sectional data for groups of respondents. Currently, due to technology changes, there is a shift in the way data is collected and analysed by using also mobile phone data (Järv et. al., 2014); geocoding and GIS data and measurements, ICT, Virtual world technology, and additional technology based tools.

Schönfelder and Axhausen (2003) emphasise three measures for an activity space size: 1) a two-dimensional confidence ellipse (interval) around a suitably chosen centre point; 2) measured by using information about the locations; and 3) based on the idea of a minimum spanning tree (network) – the length of the minimum distance routes between the locations visited, or the area covered by a buffer around those routes.

  • Harding, C., Patterson, Z., Miranda-Moreno, L. F., & Zahabi, S. A. (2014). A spatial and temporal comparative analysis of the effects of land-use clusters on activity spaces in three Quebec cities. Environment and Planning B: Planning and Design, 41, 1044-1062.
  • Horton, F. E., & Reynolds, D. R. (1971). Effects of urban spatial structure on individual behavior. Economic Geography, 36-48.
  • Schönfelder, S., & Axhausen, K. W. (2003). Activity spaces: measures of social exclusion?. Transport policy, 10(4), 273-286.
  • Sclater, M., & Lally, V. (2014). The realities of researching alongside virtual youth in late modernity creative practices and activity theory. Journal of Youth Studies, 17(1), 1-25.

Leave a Reply

Your email address will not be published.