MSc thesis on capturing the mobility of minority language groups in Finland using Twitter data

Author: Emil Ehnström

Why study the spatial mobility of language minorities?

People are increasingly more mobile, which is leading to a more complex world. One outcome of this is the linguistic diversification of societies. This raises the issue of language groups’ integration to a society, but also of their transnationality while people in their new society are still connected to their previous society and culture. One way to understand people’s connectedness to their origin society and integration to their host society is by studying their mobility patterns. With novel data sources, like geo-located social media data, it is possible to acquire information on both cross-border and local mobility patterns of language groups.

The three language groups studied in my thesis have different characteristics. Swedish is a national language of Finland and Swedish speakers are generally considered an integral part of Finnish society. Russian speakers have arrived in Finland during multiple time periods, but significantly more since the 1990s during the immigration of the Ingrian-rooted people from the former Soviet Union. Therefore, Russian speakers form a rather heterogeneous language group. Estonian speakers started moving to Finland since the 1990s and in particular after Estonia joined the EU and thus the Finnish labour market became more accessible for Estonians. Being geographically close, people from Estonia have moved to Finland mainly due to work, while keeping tight connections to Estonia. This has hindered them from fully integrating to the Finnish society.


In this thesis, I used geo-located Twitter data collected prior the Covid-19 pandemic. By using a language recognition model, I could identify the language of each tweet and thus aggregate tweets by each user and create a language profile for that person. This way I revealed people belonging to one of the three minority language groups studied. I also studied people belonging to the Finnish language group as the reference group for comparison.

For each language group I calculated the number of times they crossed the Finnish border as well as the number of times they crossed the border of a country where the language of the language group is predominantly spoken (Estonia, Russia, Sweden). I considered it as an indication of how strong the ties are to the neighbouring country. In the first boxplot (see below), we can see for each language group the share of travels that has been conducted to a neighbouring majority language country. We see that Estonian speakers tend to travel more often to Estonia, than for example Swedish speakers to Sweden. The variation is high among Russian speakers – some travel more often to Russia, while others rarely.

Emil_MSc_Figure1I also calculated how diverse the travel patterns were, by calculating the number of unique countries a user visited and using two diversity metrics, the Shannon entropy and Simpson’s Reciprocal index. I considered low cross-border mobility diversity as an indication of connectedness (or the level of transnationality) to neighbouring countries. The results confirm the same patterns as above – lowest diversity is among Estonian speakers, while among Swedish speakers it is the highest and is at the same level as Finnish-speaking people.

Another aspect I looked at was the domestic mobility pattern, and I calculated how many unique municipalities a user had visited and how long the mean distance they had travelled was. I considered the domestic movement patterns as an indication of integration to the Finnish society. I also examined the linkage between cross-border and domestic mobility patterns. In the second boxplot (below), the differences in the number of unique municipalities visited is presented. Here we can see that Estonian speakers visit on average fewer unique municipalities in Finland, than the other language groups. For Russian speakers the variation within the language group is larger, leading to a higher average but a similar median to Estonian speakers. The two national languages of Finland are quite similar in this regard – visiting equally different municipalities.

Emil_MSc_Figure2What did I find out?

To see if there are overall differences between the language groups regarding all variables examined, I used one-way ANOVA tests. Since all variables showed some significant difference, I further used a Games-Howell post-hoc test to see where the differences between groups lie. I found that mainly in all examined variables Estonian speakers had significantly different pattern than the other three language groups. For example, that there are significant differences between the number of unique countries visited between Estonian speakers and other three language groups, whereas other groups did not have statistically significant difference between them.

Also, for each language group I mapped their cross-border movements. The bar chart (below) shows the share of travels to each continent. Europe is as expected the most visited continent, but we can also spot some differences between the language groups. Finnish speakers for example tend to travel more to other continents than the other three language groups.

Emil_MSc_Figure3From the maps (below) we can see that Estonian speakers often travel between Helsinki and Tallinn, but on the Estonian side also Pärnu, Tartu, and Viljandi shows up. For Russian speakers we can see that the main travel lines go between Moscow and St. Petersburg in Russia to Helsinki in Finland. Petrozavodsk in Russia also seem to be highlighted, as well as some towns in eastern Finland. Swedish speakers mainly travel to Stockholm and some other major cities. Swedish speakers from Ostrobothnia also travel to Umeå.


In future, I think it would be interesting to examine these mobility patterns even further. For example, looking more closely at the travel diversity. Which countries does each language group visit more often than others? Another important aspect would be to look at the temporal variation. By looking at the temporal variation, we could for instance get a better understanding how mobility differs between weekdays and weekends. For instance, could we see if Estonian speakers tend to travel to Estonia for the weekend and spend their leisure time there, instead of Finland.

In general, the results show that there are different mobility patterns between the language groups. Estonian speakers are more immobile within Finland and travel a lot between Estonia and Finland, that provides some evidence about the tight connectedness to Estonian society even while they live in Finland. Russian speaker’s mobility patterns varied quite a lot, with some being very mobile and others not. Swedish speakers had very similar mobility patterns to the majority Finnish speaking population that confirms their full integration to the Finnish society. These results also indicate that spatial mobility derived from social media data could provide some insights about integration and transnationality. To understand these patterns more thoroughly, I look forward to more research on this topic.

Read the full MSc thesis here: Capturing International and Domestic Mobility Patterns ​of Minority Language Groups: ​Case of Finland using Twitter data

This thesis was part of the BORDERSPACE project led by Academy Research Fellow Olle Järv. BORDERSPACE combines cutting edge big data analytics and critical theorizations to study the socio-spatial phenomenon of transnationalism through bordering practices of people. The novelty of the project stems from the use of big data sources with the purpose of providing valuable insights for cross-border research and practice. The project is carried out at the Digital Geography Lab – an interdisciplinary research team focusing on spatial Big Data analytics for fair and sustainable societies at University of Helsinki.

Ihmisen kokoista kaupunkia suunnittelemassa webinaari 26.10.2021

Helsingin yliopiston Digital Geography Lab kutsuu lämpimästi sinut osallistumaan Ihmisen kokoista kaupunkia suunnittelemassa: oppeja tutkimuksesta ja liikennesuunnittelun arjesta -webinaariin 26. lokakuuta klo 14:00–16:00.

Webinaari on tarkoitettu niin kaupunki- ja liikennesuunnittelun ammattilaisille, tutkijoille, kuin myös kaikille kaupungeista ja liikenteestä yleisesti kiinnostuneille. Webinaari pidetään pääosin suomeksi.

Webinaari keskittyy pohtimaan, miten luoda miellyttäviä ja terveellisiä liikkumisympäristöjä kaupungeissa. Esittelemme webinaarin alkupuoliskolla tuoreita tutkimustuloksiamme sekä Helsingin seudun parhaita suunnittelukäytäntöjä. Esitysten aiheina ovat muun muassa liikkumisympäristöjen laatu sekä ihmisten liikkumisenaikainen altistuminen ympäristölle. Webinaarin toisella puoliskolla jatkamme paneelikeskustelulla, jossa kuullaan näkemyksiä siitä, miten liikennettä ja liikkumisympäristöjä voidaan tutkia ihmisenkokoisesta näkökulmasta sekä siitä, miten ihmisenkokoisuutta voidaan tuoda osaksi kaupunki- ja liikennesuunnittelua. Myös kaikki tilaisuuden osallistujat voivat ottaa osaa paneelikeskusteluun kysymysten ja kommenttien kautta.

Esittelemme tilaisuudessa myös tuoreen tilaisuuden teemaan kytkeytyvän kirjan “Transport in Human Scale Cities”, jonka ovat toimittaneet Miloš Mladenović, Tuuli Toivonen, Elias Willberg sekä Karst Geurs. Kirja Transport in Human Scale Cities on avoimesti ladattavissa.

Rekisteröidy webinaariin täyttämällä e-lomake 22.10 mennessä. Välitämme osallistumislinkin ilmoittautuneille sähköpostitse webinaaria edeltävänä päivänä.


14:00 Webinaarin avaus

14:05 Tuuli Toivonen – “Paikkatiedon avulla kohti ihmisenkokoisen kaupungin tutkimusta”

14:15 Johanna Palomäki – “Ihmisten kaupunkia ihmisten kanssa – yhteistoiminnallisen suunnittelun rakenteet Espoon yleiskaavoituksessa”

14:25 Age Poom – “Healthy travel environments for everyone: from individual route choice to just and sustainable societies”

14:35 Miloš Mladenović – “Transport in Human Scale Cities: reflections on a new open access book”

14:45 Kysymyksiä esityksistä

14:55 Tauko

15:00 Paneelikeskustelu – Ihmisen kokoista kaupunkia suunnittelemassa: oppeja tutkimuksesta ja liikennesuunnittelun arjesta. Panelisteina Marketta Kyttä, Johanna Palomäki, Sini Puntanen ja Kati Vierikko. Moderaattorina toimii väitöskirjatutkija Elias Willberg.

15:55 Tilaisuuden päätössanat

16:00 Webinaari päättyy

Continue reading “Ihmisen kokoista kaupunkia suunnittelemassa webinaari 26.10.2021”

New open access book out! Transport in Human Scale Cities

We have published a new open access book Transport in Human Scale Cities, which deals with sustainable urban transport

Sustainable urban transport is one of the biggest challenges facing cities worldwide. This means carbon neutrality, but also taking better into account the needs of people and their preferences and needs.  The new book deals exactly with that.

The new book offers fresh perspectives for both practitioners and researchers how to make cities and the transport in them more human-scale in order to meet the demands of the current sustainability crisis and the COVID19 pandemic.

The book provides multidisciplinary perspectives for the development of urban and transport planning processes with a human-scale approach, considering new data and methods and recognizing the diversity of needs of people. We hope that it brings new perspectives to all interested in urban transport.

The parts of the book include

I: Introduction

II:  Understanding human scale transport in cities

III: Responsible innovation practises for human scale cities

IV: Potentials for developing planning processes for human scale cities

V: Conclusion

The book is edited by Miloš Mladenović from Aalto University, Tuuli and Elias from the Digital Geography Lab and Karst Geurs from the University of Twente. Individual chapters are authored by over 50 Network on European Communications and Transport Activities Research (NECTAR) researchers representing various scientific fields and Universities.

The book originates from the NECTAR conference Towards Human Scale Cities – Open and Happy, which was organized by our Digital Geography Lab in 2019 in Helsinki. It collects together some of important works of the conference.

Our book is a testament to openness. It is open to all interested, from planners to students and citizens. We are very thankful to the NECTAR network, Aalto University, University of Helsinki and the Finnish Cultural Foundation who financially supported the openness of conference and have enabled the openness of the book.

The book is dedicated to the memory of dr. Moshe Givoni, lecturer at Tel-Aviv University, whose ambition was to continuously promote research and better policy making to transform our urban mobility systems.

Creating knowledge about exercising in the Helsinki Metropolitan Area using Twitter data

Sonja Koivisto introduces her MSc thesis

Why study exercising with social media data?

Sports and exercising are an integral part of a healthy lifestyle. Keeping oneself active is known to prevent obesity and the risk of many chronic diseases. Globally, inactivity is the fourth most common cause of death. The Finnish government has acknowledged the importance of the issue by stating three objectives for encouraging exercise and supporting sports in the current government programme.

There is surprisingly little spatial research about sports in different parts of the Helsinki Metropolitan Area. Only a few sports facilities collect visitors’ statistics and often this information is not openly available. Therefore, I decided to study the topic using social media data. I wanted to find out how people exercise in different parts of the Metropolitan Area and which spatial factors affect the number of sports-related posts.

According to Statistics Finland, 80% of Finns use social media. Among people under 45-years-old, the number is over 95%. People post to social media about topics and activities that are close to their hearts, like sports for instance. The most popular social media platforms in Finland are WhatsApp, Facebook and Instagram. However, these platforms do not share their data for research purposes unlike microblogging platform Twitter. Twitter is used by 10% of Finns.

How can exercising be studied from tweets?

A major advantage when using social media data for research is that there is a huge number of posts available for analysis. In my study, I analyzed 38.5 million tweets. However, the large quantity of data can also pose challenges to an efficient data analysis.

First I wanted to extract only the tweets that were related to sports and exercising. In order to achieve that, I converted all the words to their base form using Natural Language Processing methods. Then I programmatically checked if the words matched to the words in a sports-related key word list that I had prepared.

Once the data had been thematically filtered, I also wanted to limit it spatially to the Helsinki Metropolitan area. About 1% of the tweets include a geotag, meaning information about the location it has been posted from. From the geotagged tweets, I chose to use those which were from the Metropolitan Area. From the tweets that did not include a geotag, I programmatically searched for place names located in the Metropolitan Area. If I found a tweet with a place name, I attached the coordinates of the corresponding place to the tweets. Finally I ended up with 20 599 tweets out of which two thirds were geotagged and to a third I had programmatically attached the coordinates with the help of the place names mentioned. In the subsequent analyses, I grouped the tweets by the sport they mentioned and I used statistical methods to estimate the number of tweets.

Hotspots of different sports are located in different parts of Metropolitan area

Most sports and exercising tweets are located on the peninsula of Helsinki. Other hotspots are neighbourhoods of Tapiola, Leppävaara and Tikkurila. However, when the tweets are aggregated to the postal code areas and divided by population, their distribution becomes quite even.

From the socio-economic parameters chosen for the study, the best estimates for tweets per population were the number of sports facilities in the area, the employment rate and the share of children in the postal code area. The number of sports facilities per person and employment rate affect the number of tweets positively as the percentage of children affect it negatively. These three variables combined explain 38% of the variation of the number of tweets per person.

Tweets about different types of sports provide interesting details. 20% of the tweets were caught by general sports keywords such as sport, workout, sweat, etc. Followed by this were tweets related to running and third came the walking-related tweets. Percentage of tweets related to football, ice hockey and floorball appears to be higher when compared to the percentage of those who actually physically participate in these sports as reported by the National sport survey. This may be because these sports are popular spectator sports, hence more people engage online. Swimming and skiing, on the other hand, have more physical participations compared to the amount of tweets.

The different types of sports are distributed differently in the Metropolitan Area. Many sports are clustered to the center of Helsinki and to other residential and sports facilities hotspots.

For some of the sports, like skiing and racket sports, tweets are more concentrated around the respective sporting facilities. Most skiing tweets can be found in the neighbourhoods of Olari, Paloheinä, Leppävaara and Hakunila which maintain good skiing tracks. Racket sports tweets (including tennis, badminton, squash and table tennis) have hotspots in Smash center Myllypuro and Tali tennis center. Water sports tweets (kayaking, rowing and sailing) are distributed evenly along the coast and there is a hotspot in a lake in Nuuksio.


In this study, new information was revealed about the potential factors affecting the number of sports tweets and their distribution in the Helsinki Metropolitan area. Sports tweets are distributed in a similar manner as the population. More sports tweets are likely found where there are more sports facilities per person.

Some sports are over-represented and some others are under-represented in the tweets compared to the number of hobbyists that actually play the sports. Factors that affect the representation on Twitter are the trendiness of the sport, its popularity as a spectator sport, and the age of the hobbyist and their activeness on Twitter. For some types of sports, the tweets distribution correspond to the facilities distribution. For example running and walking are easy to do anywhere but skiers often want a maintained skiing track and racket players prefer a hall with respective courts.

The MSc thesis was conducted within the YLLI-project (Equality in suburban physical activity environments / Yhdenvertainen liikunnallinen lähiö) that studies active lifestyles, sports activities and residents’ equal possibilities to access sport facilities and physical activity environments in Finnish suburbans. The project combines researchers from the research group Digital Geography Lab and Geography of Well-being and Education from the University of Helsinki, and researchers from the Social Sciences of Sport, University of Jyväskylä. The Digital Geography Lab is an interdisciplinary research team focusing on spatial Big Data analytics for fair and sustainable societies.

WE ARE RECRUITING! Looking for a postdoctoral researcher in big data analytics in the area of human mobility and social interactions

Are you interested in studying human mobility and social interactions that take place in the cross-border context, and doing advanced spatial and content analysis using millions of social media posts? If so, consider applying for a postdoc position at the Digital Geography Lab (DGL) to work with Academy Research Fellow Olle Järv from November 2021 (or sooner/later as agreed)!

We are looking for an enthusiastic, innovative, and open-minded team player with strong technical knowledge and skills to join our interdisciplinary DGL research group and work in the Academy of Finland-funded project BORDERSPACE – Tracing Interactions and Mobilities Beyond State Borders: Towards New Transnational Spaces.

The possible research topic can be among the following four lines of research:

  • quantifying human mobility and activity spaces across country borders, based on social media data (Twitter), including developing concepts and methods of the field;
  • examining people’s perceptions and embodied experiences regarding transnational lifestyle, and their feelings of belonging using quantitative content analysis of millions of social media posts;
  • identifying functional cross-border regions based on human mobility and interactions, including developing concepts and methods of the field;
  • investigating the influence of external factors such as the global COVID-19 pandemic on cross-border mobilities, people’s perceptions and embodied experiences regarding transnational lifestyle, and their feelings of belonging to different societies.

The successful applicant is expected to have: 1) strong fluency in programming and automation; 2) experience in working with large-scale quantitative datasets (e.g., mobile phone & social media data) and machine-learning; 3) experience in advanced spatial analytics and/or (social media) textual content analysis; 4) an excellent command of oral and written English as demonstrated by published studies in peer-reviewed journals and active participation in research community; and 5) high motivation to pursue an academic career. Prior theoretical knowledge on one or several of the project’s four research lines (see above) is an asset.

Read more about the position announcement and apply HERE. The deadline is September 14th 2021.

For more information about the position, or any questions about the BORDERSPACE project and potential fit, please contact Olle Järv, olle.jarv(at)

Understanding functional cross-border regions from Twitter data: The Nordics case study

Håvard Wallin Aagesen introduces his MSc thesis

How can Twitter data be used to study cross-border regions in the Nordics? And how are the effects of the COVID-19 pandemic reflected in the spatial pattern of Twitter usage? These were some of the questions that Håvard Wallin Aagesen, a fresh PhD candidate at the Digital Geography Lab, addressed in his MSc thesis “Understanding Functional Cross-border Regions from Twitter Data in the Nordics“. In this blog post, Håvard looks back to and summarizes his MSc work.

Why this matters?

As part of the BORDERSPACE project, I set out to investigate how cross-border interactions in the Nordic countries can be studied, using Big Data from Twitter. In light of the COVID-19 pandemic, a newfound need for studying cross-border flows has arisen, and Twitter data could provide the possibility to quickly and easily explore the changes in human mobility patterns before and during the pandemic.

The Nordic region is a connected region with a long history of cooperation, shared cultures, and social and economic interactions. Cross-border cooperation and cross-border mobility has been a central aspect in the region for over half a century. Despite of shared borders and all countries being part of the Schengen Area, allowing free movement, little research has been made on the extent of daily cross-border movements and little data exist on the topic.

As a well-connected region, the Nordic region saw a sudden decrease in mobility and areas across borders were suddenly isolated from each other. The spread of the COVID-19 virus, and the most important measures to counter the pandemic, have been spatial in their nature. Restrictions on mobility, and lockdown of regions and countries have been some of the measures set in place at varying degrees in different locations. Understanding the effects of mobility on the spread of COVID-19 and effectiveness of different measures is important in handling the ongoing and future pandemics.


In my thesis, I collected geotagged Twitter data from March 2019 to February 2021 to be able to utilize a person-based approach to reveal the spatial extents of human mobility across the Nordic countries, both before (March 2019 – February 2020) and during the COVID-19 pandemic (March 2020 – February 2021). With 11M tweets from 21K users, I was able to reveal cross-border movements (Figure 1), and to infer functional cross-border regions (using a kernel density estimation) in the Nordics.

All the scripts and codes used in the MSc thesis can be found in this Digital Geography Lab GitHub-repository.

                           Figure 1. Cross-border movements in the Nordics derived from 11M tweets from 21K users.

The estimations of functional cross-border regions based on human mobility before and during the pandemic clearly showed the effect of COVID-19 and the measures taken to limit cross-border mobility. The volume of cross-border mobility reduced severely (Figure 2), and the composition of functional regions changed differently in different regions. In general, the spatial extent of cross-border regions reduced and gravitated towards the largest cities on either side of the border in all Nordic countries.

Figure 2. During the COVID-19 period, the volume of cross-border mobility between countries decreased severely, while it varied between different country pairs.

However, when delineating functional cross-border regions, one has to remember that spatial scale matters. When looking at the cross-border mobility between Finland and Sweden, running a kernel density estimation with travels starting and ending on either side of the border provided different results depending on which spatial level was investigated. At the national level, taking into account all travels between the two countries, there are clear indications of strong connections between the capital cities with most start and end points of travels being clustered around Helsinki and Stockholm (Figure 3).

Figure 3. Functional cross-border regions between Finland and Sweden on the country level.

When subsetting the data to the northern regions of both Finland and Sweden (Figure 4), another clear functional cross-border region appears. The area around Tornio (FI) and Haparanda (SE) is known to be tightly connected, something that the functional cross-border region derived from Twitter data also shows. Most travels in the region start and end close to the two cities. As smoothing is inherent in kernel density estimation, lower spatial levels provide more detailed results.

Figure 4. Functional cross-border regions between Finland and Sweden on the multi-regional level.

Finally, focusing only on the most northern NUTS 2 regions of Finland and Sweden, the functional cross-border region around Tornio and Haparanda becomes very clear (Figure 5). The changes in travel patterns from the year preceding the COVID-19 travel restrictions are also evident and spatially unevenly distributed. For instance, the cities of Kiruna (SE) and Rovaniemi (FI) seem to be affected to a larger degree than Tornio and Haparanda. A similar effect of spatial scaling on delineating cross-border regions was found for all countries in the Nordic region.

Figure 5. Functional cross-border regions between Finland and Sweden on the regional level (NUTS 2).

The methods and results developed in this thesis provide new insights into the dynamics of mobility flows in the Nordic region and are first steps to make more use of novel data sources in cross-border mobility research in the Nordics. Further research into methods for expanding the data basis, and for deepening the understanding of demographic and temporal aspects of functional cross-border regions is however needed.

Read the full MSc thesis here: Understanding Functional Cross-border Regions from Twitter Data in the Nordics.

The BORDERSPACE project, led by Academy Research Fellow Olle Järv, combines cutting edge big data analytics and critical theorizations to study the socio-spatial phenomenon of transnationalism through bordering practices of people. The novelty of the project stems from the use of novel big data sources with the purpose of providing valuable insights for cross-border research and practice. The project is carried out at the Digital Geography Lab, University of Helsinki. The Digital Geography Lab is an interdisciplinary research team focusing on spatial Big Data analytics for fair and sustainable societies.

New paper out! Environmental exposure during travel: A research review and suggestions forward

Age Poom, Elias Willberg, Tuuli Toivonen

Our seminal research review paper on environmental exposures during travel is now published in the journal Health & Place! 

Urban travel environments exposure people to a range of environmental conditions, such as traffic noise, air pollution or street-level greenery. These exposures may cause both positive and negative health and wellbeing consequences. Knowledge of the dynamics of environmental exposures during travel, and their social and health outcomes would help improve the liveability and sustainability of our cities through evidence-based transport and urban planning.

We conducted a systematic review of the scholarly literature on environmental exposure during travel. We aimed to understand the state of the art of the research field and identify areas for further studies. We identified 104 relevant peer-reviewed journal articles worldwide. The research field is clearly emerging with increasing number of studies published each year. The distribution of the study areas indicates a global bias in the research field towards western cities, where the research tradition is longer. However, last years have witnessed a rapid increase in the number of studies conducted in China and India. A good global coverage of research supports local planning and governance, and better mitigates the risk of environmental health disparities in all parts of the world.

The number of studies published globally in different year ranges (A), and the spatial distribution of studies in different world regions using the same year ranges for the bars (B). The locations of individual study sites are indicated as points on the map (B). Source: Poom et al. 2021

The review showed that the key methodological challenge of the research field is the spatiotemporal coupling of travel and environmental data. Different travel modes, routes, and times expose people to different environmental conditions. The research field has strongly benefitted from the emerging location-aware sensor technology to capture the dynamics of both travel behaviour as well as environmental conditions. The future research could take the advantage of mobile Big Data to examine travel-related exposure also at the scale of populations.

Environmental exposure during travel is an interplay between people, their travel behaviour, and the surrounding travel environment. Understanding environmental exposures during travel calls for spatially and temporally detailed data on all aspects, on human scale. Source: Poom et al. 2021

The review gave evidence that most of the travel-related exposure research focuses on air pollution. Exposure to other environmental conditions, such as traffic noise or street-level greenery, has received only little scholarly attention. Even less is known about the patterns of multiple and cumulative environmental exposures during travel. More research attention is needed on the associations between travel behaviour, multiple environmental exposures, and resulting health and wellbeing effects. The future research should aim to develop shared and standardised study protocols as well as provide open data sets to make travel-related exposure studies comparable and draw conclusions of health and wellbeing effects through dedicated meta-analyses.

We conclude that there is a need to overcome disciplinary silos and integrate the expertise of exposure and health researchers, environmental scientists, transport and geospatial researchers, and sustainability and welfare scholars to advance the research field. Scholarly emphasis on good travel environments on human scale can advance the designing of just and sustainable cities.

Full reference of the article:

Poom, A., Willberg, E., Toivonen, T. (2021). Environmental exposure during travel: A research review and suggestions forward. Health & Place 70, 102584,

The Digital Geography Lab at the University of Helsinki is an interdisciplinary research team focusing on spatial Big Data analytics for fair and sustainable societies.

Warm reflections from the course GEOG-326 on accessibility and human mobility research

Time flies – the course “GEOG-326 Quantitative methods for sustainable land use planning I: Accessibility & mobility analyses“, given by the researchers of the Digital Geography Lab, ended already before Christmas 2020. Yet it’s worthwhile to reflect on it!

It is heart-warming to go through the positive feedback from students regarding the course structure and balance between theory and practice, and constructive suggestions for improving the course.

The course aimed at linking the accessibility and mobility of people to sustainability, well-being and social (in)equality perspectives, exploring the potential of big data analysis approach, and studying the ways of implementing these in planning. We also focused on the impact of global crises on human mobility on the example of COVID-19.

Overall, all 35 students did a great job and received high grades, but most importantly, it was rewarding to see students getting motivated and inspired, and developing their skills and ideas during the course.

The final output of the course was an independent group work that was presented in the form of an academic poster. Me, Elias and Tuuli found the final poster presentation session excellent! Thus, we are delighted to share the posters here 🙂

Check out and get inspired!


GROUP 1: The change in mobility flows during the first COVID-19 restrictions: A case study for Helsinki (and the sub-region)

 Alisa Redding, Sanja-Riia Collin, Venla Salomaa


GROUP 2: Bike-sharing System Support for Public Transportation – studying the temporal aspects of shared bicycle trips in 2019

Emil Ehnström, Olivia Halme, Iivari Laaksonen & Tao Jiaxin


GROUP 3: Accessibility and spatial coverage of the bike-sharing systems in the Helsinki Metropolitan Area

Håvard Aagesen, Hanna Hirvonen, Miika Kastarinen, Jussi Torkko


GROUP 4: Bike sharing in Finland: A comparison of HSL and Föli city bikes ridership from 2018 2020

Emily Dovydaitis, Kia Kautonen, Matti Moisala, Juho Noro


GROUP 5: Impact of COVID-19 on dockless mobility in Austin, Texas

Benedikt Kohl, Tatu Leppämäki, Anna Levlin & Mathew Page


GROUP 7: Comparison of bike-sharing data in Helsinki and Espoo from 2019 and 2020 in relation to Covid-19

Matti Hästbacka, Jouko Lappalainen, Klara Lappalainen, Sarah Seidel


GROUP 8: Effects of COVID-19 on city bike usage

Emma Piela, Eero Perola, Antti Miettinen & Isaline Coquard


GROUP 9: Automating travel time matrix data preprocessing

Hanna Haurinen, Saku Saarimaa, Ekku Keurulainen, Jeanne Leroux


GROUP 10: Green Accessibility Index’ in dominant travel areas zonified by transportation mode in the Finnish Capital Region

Bryan Vallejo, Lauri Ovaska, Elli-Nora Kaarto & Miro Mujunen

Etsimme tutkijatohtoria tai tohtorikoulutettavaa!

Briefly in English: We are sharing an announcement for a post-doc/PhD student position at Digital Geography Lab and Ruralia Institute. The position benefits from the knowledge of Finnish language and hence is published in Finnish only.

Ja sitten suomeksi:

Kiinnostaako monipaikkaisuus, aluekehitys ja ihmisten liikkuvuus? Haluaisitko tietää, miten erilaisten digitaalisten aineistojen avulla voi monipaikkaisuutta tarkastella tai miten COVID-19 pandemia on vaikuttanut kakkosasuntojen käyttöä Suomessa?

Ruralia-instituutti ja Digital Geography Lab yhteiistyössä hakee tutkijatohtoria/tohtorikoulutettavaa hankkeeseen ”Monipaikkaisen asumisen rytmit”.

Tehtävät käsittävät digitaalisten massa-aineistojen (mm. rakennusten sähkönkäytön, matkapuhelinverkon ja Twitter aineistoja) hallinnointia, prosessointia ja analysointia. Hakijalta edellytetään riittäviä geoinformatiikan taitoja analyysien tekoon, massa-aineistojen käsittelyyn vaativaa osaamista (Python, R, PostgreSQL) ja tilastollista osaamista. Suurteholaskennan kokemus katsotaan eduksi.

Tarkemmat hakuohjeet löytyvät täältä.

Hakuaika päättyy 22.3.2021, ole nopea!

Lisätietoja saa: akatemiatutkija Olle Järv olle.jarv(at) ja professori Tuuli Toivonen, tuuli.toivonen(at)

Two new papers out on cycling!

We have published two new articles on cycling! 

What do trip data reveal about bike-sharing system users‘ was published in Journal of Transport Geography.


    • As cities strive to foster cycling, bike-sharing systems (BSS) have become increasingly common.
    • We used bike-sharing trip data from Helsinki and looked at user profiles and usage patterns. We also focused on the possibilities of BSS trip data.
    • The bike-sharing system in Helsinki has been actively used even in international comparison, but our results point toward challenges in BSS inclusivity in Helsinki in 2017. Most use was contributed by a limited group of ‘super-users’.
    • BSS trip data provides opportunities to understanding BSS user profiles & patterns. By being well available, unlike many other cycling data sources, and automatically collected, trip data can save resources, facilitates longitudinal research and reveals observed behaviour.

Willberg E., Salonen M., Toivonen T. (2021). What do trip data reveal about bike-sharing system users? Journal of Transport Geography.


Comparing spatial data sources for cycling studies – a review will be published officially later this year in the NECTAR book ‘Transport in Human Scale Cities’, but we have made it available as a postprint already now.


    • We reviewed various spatial data sources on cycling
    • We built upon the expertise of a broad group of cycling experts and collected their views on the strengths, weaknesses and usability of the data sources.
    • With several reviewed data sources, having data is still a key challenge including difficulties in data collection, lack of suitable data and poor accessibility to it,
    • Data availability could be improved by increased data sharing by planning agencies and researchers. Development of data products to improve access to the data collected by private companies is also needed. However, this development must be carried our responsibly protecting users’ privacy.

Willberg, E., Tenkanen, H., Poom, A., Salonen, M., & Toivonen, T. (2021). Comparing spatial data sources for cycling studies – a review. SocArXiv


Here’s the press release on the articles:

Spatial  data for understanding urban cycling

Cities strive to increase their cycling levels and constantly more information is being collected on cycling. Two recent studies by the Digital Geography Lab group reveal what novel big data tell us about city bike users, for example, and how the availability of information collected about cycling remains a major challenge.

The popularity of cycling is growing, especially in urban areas. Also, as a result of the COVID-19 crisis,  many have switched to cycling. Cycling is one of the ways to promote sustainable mobility in cities. Bike-sharing systems have become one of the most visible measures to promote cycling in Finnish cities, and the reception of the systems has often been enthusiastic. Bike-sharing systems also provide a novel information about cycling.

The Digital Geography Lab group has studied cycling with novel big data. A recently published article considers the possibilities of bike-sharing trip data in cycling research. The information is used to analyze the spatial and temporal usage patterns of the Helsinki bike-sharing system in addition to understanding user characteristics and inclusivity of the system.

Demographics of BSS users (a) and BSS trips (c) compared to the Helsinki population. Bar charts show the comparison in regard to users’ home area (b) and users’ subscription type (d)

Young adult city dwellers are large consumers of urban bikes

“Helsinki bike-sharing system has been popular based on use activity. But in the scientific discussion, bike-sharing systems are often criticized for mainly serving only certain groups of people, ”says doctoral researcher Elias Willberg.

“This criticism made us interested in looking at users of the Helsinki system,” he continues. The aim for the research is to bring new perspectives to the practical design and management of bike-sharing systems in cities.

The study found that despite the high use, the user population in the early years of the bike-sharing system was strongly focused on young adults living within the system area. The survey was conducted with data from 2017, when the system still collected basic data variables on registered users. The study also showed the potential of bike-sharing trip data in understanding user needs and habits of various users.

“It is important to pay attention that bike-sharing systems would serve the widest possible range of different areas and groups of people, so that the systems can effectively support sustainable urban mobility. Data from shared bikes provide useful information for these needs, ”Willberg says.

On weekdays, most cyclists are on the move in the morning and afternoon. On weekends, people cycle less than on weekdays and go cycling throughout the day.

Various sensors and portable devices provide information about cycling to researchers

Another newly completed scientific article by our group involved cycling experts from across Europe and gathered information on the benefits and challenges of various data sources on cycling. The article will be published in the book “Transport in Human Scale Cities”  in the autumn, but it is already available online. “Various sensors and portable devices such as mobile phone apps and sports watches are increasingly storing information also about cyclists. A diverse use of various data sources is essential for holistic understanding of cycling, ”says Tuuli Toivonen, Professor of Geoinformatics, who led the research.

The main message of the study is that the availability of data remains a major bottleneck in cycling research and knowledge-based design. Novel data sources provide tools for understanding cycling and answer questions such as where and when people cycle in urban areas. But they are not a panacea. Automatically collected data from various systems do not provide much for understanding causes of cycling, for example. Such data may also be skewed on active users. In this case, they do not necessarily represent the entire population.

“There is still a lot of work to be done in improving the availability and transparency of cycling data,” Toivonen says. “Despite the great need, access to data must be promoted responsibly, taking into account privacy issues,” she concludes.

Suitability of cycling data sources to various types of questions