Mobility research in areas with seasonal population changes

In the end of 2019, SYKE, the Finnish Environmental Institute, arranged a miniseminar on mobility research in urban, rural and touristic settings. The seminar addressed mobility research interrelations with spatial planning and governance, stakeholder engagement in spatial and transportation planning, sustainable mobility challenges in remote and touristic settings, and various methods for acquiring, processing and analysing mobility data.

The seminar was held in Helsinki and was part of the InterReg Baltic Sea-funded project MARA. The overall aim of the project is to address mobility and accessibility challenges in rural areas. Project activities and the perspectives and challenges of various mobility data were presented in the seminar by Kari Oinonen (SYKE), Age Poom (Digital Geography Lab, University of Helsinki & Mobility Lab, University of Tartu), Daniel Brandt and Tobias Heldt (both from CeTLeR, Dalarna University). SYKE researchers introduced their studies on GIS use in urban and rural planning (Ville Helminen), rural mobility, accessibility and travel related to second homes (Antti Rehunen), public participatory GIS (Elina Nyberg) and the architecture of spatial data infrastructure in SYKE (Kaisu Harju).

Spatial planning and governance require data on people’s mobility for smart decision-making: on local and regional, daily and seasonal, regular and irregular spatial behaviour. Countries that conduct national travel surveys collect data on regular travel patterns of local residents. This information is very powerful for addressing a number of goals, as also demonstrated by Antti Rehunen, SYKE, in the seminar. However, it tends to uncover travel that takes place occasionally, such as seasonal leisure travel. Remote touristic areas may face temporary population flows that reach the magnitude of a mid-sized city in spatial conditions that have not been optimised for serving such an amount of people smoothly and sustainably.

Several remote touristic areas such as Nordic ski resorts are facing the above-mentioned problem. Within MARA project, they find out ways how to gain more meaningful data on mobility needs as well as on current mobility patterns in their region. The project also looks into the question on how to better manage local temporary travel flows. This involves both transportation as well as service infrastructure covering the full mobility behaviour of tourists, for example accessibility to cultural and natural amenities, sport facilities, accommodation, dining facilities or stores.

Currently, most regions lack explicit information on domestic and foreign tourist flows and their detailed mobility within the destination region. Apart from official statistics from accommodation service providers, traveller counts in local airports or data on ticket sales from touristic hotspots, questionnaires have been a convenient approach to address the mobility or activity of tourists in a region (Heldt and Mortazavi 2016). Spatiotemporally more explicit method is arranging GPS-supported tourist tracking campaigns during their stay in the region (Shoval and Ahas 2016). As GPS campaigns may be costly and require large managerial effort, other geocoded data collection methods such as use of destination card (Zoltan and McKercher 2015) or public participatory GIS (Kantola et al. 2018; Salonen et al. 2018) are used in tourism studies. The latter method was also applied in the MARA project within the Kymeenlaakso regional survey of non-resident population (Vierikko et al. 2019). Subject to the survey design, the above-mentioned methods may reveal individual activity locations and times, mobility chains and travel modes, as well as semantic meaning and reasons behind individual mobility decisions. At the same time, a drawback with these methods is that they cover either rather small number of volunteering visitors or involve sample biases due to sample management and enrolment issues.

To cover larger population flows in the region, other digital mobility data sources would be handy. There is an increasing body of studies applying social media (Toivonen et al. 2019) or mobile phone data (Ahas et al. 2014) in tourism related research. Passive mobile phone data has proven to be a rich data source for analysing the spatiotemporal behaviour of large anonymous population groups. The University of Tartu has extensive experience in applying mobile phone data also in tourism studies (Ahas et al. 2007; Nilbe et al. 2014; Raun et al., 2016; Saluveer et al. forthcoming). In the seminar, Age Poom gave insights to mobile phone based research conducted in Estonia. The MARA project involves development of a Population Mobility Monitor that among other data sources applies mobile phone data to visualise regional population flows.

There are many regulatory and operational issues to be solved before passive mobile phone data can be used in research, for example to secure privacy protection of individual subscribers who serve as anonymous data providers. As mobile phone data becomes more and more accessible elsewhere, including Sweden (Östh et al. 2016) and Finland (Bergroth 2018), there are strong perspectives of using it also in the mobility management of remote touristic areas.

Disclosure: The blog post is adjusted based on the original post published on the MARA project website.


Ahas, R., Aasa, A., Mark, Ü., Pae, T., Kull, A. 2007. Seasonal tourism spaces in Estonia: Case study with mobile positioning data. Tourism Management, 28(3), 898–910.

Ahas, R., Armoogum, J., Esko, S., Ilves, M., Karus, E., Madre, J.-L., Nurmi, O., Potier, F., Schmücker, D., Sonntag, U., Tiru, M. 2014. Feasibility Study on the Use of Mobile Positioning Data for Tourism Statistics Report 3a. Feasibility of Use: Methodological Issues.

Bergroth, C. 2018. The 24-h population dynamics of the Finnish Capital Region uncovered!

Heldt, T., Mortazavi, R. 2016. Estimating and comparing demand for a music event using stated choice and actual visitor behaviour data. Scandinavian Journal of Hospitality and Tourism, 16(2), 130–142.

Kantola, S., Uusitalo, M., Nivala, V., Tuulentie, S. 2018. Tourism resort users’ participation in planning: Testing the public participation geographic information system method in Levi, Finnish Lapland. Tourism Management Perspectives, 27, 22–32.

Nilbe, K., Ahas, R., Silm, S. 2014. Evaluating the Travel Distances of Events Visitors and Regular Visitors Using Mobile Positioning Data: The Case of Estonia. Journal of Urban Technology, 21(2), 91–107.

Östh, J., Reggiani, A., Schintler, L. 2016. Resilience in Spatial and Urban Systems 2. Presentation at Advanced Brainstorm Carrefour (ABC): ‘Smart People in Smart Cities’ Matej Bel University, Banská Bystrica, Slovakia (August, 2016).

Raun, J., Ahas, R., Tiru, M. 2016. Measuring tourism destinations using mobile tracking data. Tourism Management, 57, 202–212.

Salonen, M., Broberg, A., Kyttä, M., Toivonen, T. 2014. Do suburban residents prefer the fastest or low-carbon travel modes? Combining public participation GIS and multimodal travel time analysis for daily mobility research. Applied Geography, 53, 438–448.

Saluveer, E., Raun, J., Tiru, M., Altin, L., Kroon, J., Snitsarenko, T., Aasa, A., Silm, S. n.d. Methodological framework for producing national tourism statistics from mobile positioning data. Annals of Tourism Research.

Shoval, N., Ahas, R. 2016. The use of tracking technologies in tourism research: the first decade. Tourism Geographies, 18(5), 587–606.

Toivonen, T., Heikinheimo, V., Fink, C., Hausmann, A., Hiippala, T., Järv, O., Tenkanen, H., Di Minin, E. 2019. Social Media Data for Conservation Science: a Methodological Overview. Biological Conservation, 233(January), 1–18.

Zoltan, J., McKercher, B. 2015. Analysing intra-destination movements and activity participation of tourists through destination card consumption. Tourism Geographies, 17(1), 19–35.