New Travel Time Matrix 2023 and GREENTRAVEL project

Digital Geography Lab presented a new travel time matrix 2023 and a new big project GREENTRAVEL in a seminar held in Think Corner.

Helsinki region travel time matrix was published now for the fourth time. The matrix is an interactive open access dataset that allows investigation of travel times for different travel modes in Helsinki region. Professor Tuuli Toivonen gave an insight to the history of the matrix which was first published already ten years ago in 2013.

Since the first matrix was computed, the technology has improved and enabled the use of new methods. Christoph Fink explained how the new matrix was calculated and showed how it works.  Current accessibility prospects and changes in the regional structures of accessibility in Helsinki region were described by Elias Willberg. We also had two guest speekers, Miikka Haimila and Iiris Karvinen, from the city of Helsinki. Haimila reflected the importance of matrix for the city and its open data activities. Karvinen took the angle of a planner and demonstrated how the matrix has been serving the planning needs of the city.

In the end Tuuli Toivonen presented our new big project GREENTRAVEL which aims to explore the availability and quality of green urban travel environments and their impacts on wellbeing through the prism of urban informatics. We continued the discussions right after the seminar in a GREENTRAVEL workshop where we focused on the role of greenery in urban travel environments and how greenery can be better incorporated in current green infrastructure and travel and mobility planning.

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Uusi matka-aikamatriisi 2023 ja GREENTRAVEL-projekti (available in English as separate post)

Digital Geography Lab esitteli uuden pääkaupunkiseudun matka-aika-aineiston 2023 ja juuri käynnistyneen GREENTRAVEL-tutkimushankkeen Tidekulmassa järjestetyssä julkaisutapahtumassa.

Pääkaupunkiseudun matka-aikamatriisi julkaistiin nyt jo neljättä kertaa. Matriisi on avoin paikkatietoaineisto, joka mahdollistaa matka-aikojen vertailun eri kulkutavoilla pääkaupunkiseudulla. Professori Tuuli Toivonen kertoi matriisin historiaa valaisseessa puheenvuorossaan ensimmäisen matriisin julkaisusta kuluneen jo 10 vuotta.

Teknologian kehittyminen ensimmäisten matriisien tuottamisen jälkeen on mahdollistanut uusien menetelmien käytön laskennassa. Christoph Fink esitteli miten uusi matriisi on laskettu ja miten se toimii. Elias Willberg valotti pääkaupunkiseudun nykyistä saavutettavuusmaisemaa sekä muutoksia saavutettavuuden alueellisissa rakenteissa kuluneiden 10 vuoden aikana. Mukana olivat myös vierailevat puhujamme Miikka Haimila ja Iiris Karvinen Helsingin kaupungilta. Haimila kertoi matriisin merkityksestä kaupungille ja sen avoimen datan toiminnalle. Karvinen osoitti suunnittelijan näkökulmasta miten matriisi on palvellut kaupungin suunnittelutarpeita.

Lopuksi Tuuli Toivonen esitteli uuden viisivuotisen GREENTRAVEL-tutkimushankkeen, jossa selvitetään liikkumisympäristöjen laatuun ja vihreyteen liittyviä mieltymyksiä sekä niihin kytkeytyviä hyvinvointivaikutuksia ja näiden alueellista, vuodenaikaista ja yhdenvertaista saatavuutta. Jatkoimme keskustelua aiheesta seminaarin jälkeen pidetyssä GREENTRAVEL-työpajassa, jossa keskityimme vehreyden rooliin kaupunkien liikkumisympäristöissä sekä tapoihin tuoda vehreys näkyvämmin osaksi liikkumisympäristöjen suunnittelua.

Continue reading “Uusi matka-aikamatriisi 2023 ja GREENTRAVEL-projekti (available in English as separate post)”

How long does it take to park a private car in Helsinki Capital Region? – A map based survey

The parking survey is available in English and in Finnish.

Read in Finnish

How long does it take to park a private car in Helsinki Capital Region? Is there variation in parking times in different districts of the Capital Region? How can we explain the hypothetical variation?

We are now researching how long does it take for a private car to find a parking spot, park and walk to one’s final destination in different areas of Helsinki Capital Region using a map based survey. In the survey linked below the user chooses postal code areas where they remember having parked in the last two years. For each postal code area user is asked to fill a short form how their parking experience usually is in that area. The survey is created in such a way that data can be sent from as many postal code areas as the user wants – all in one session.

Please find the map based web application survey here. We ask you to answer to the survey latest at 30th June 2019. The survey starts up by default in English. If you wish to fill out the survey in Finnish, you can change the language by clicking the EN/FI button located in the upper left corner of the screen.

About the research

This survey research is a part of the Master’s thesis of Sampo Vesanen. The work is connected to the Helsinki Region Travel Time Matrix, a tool created by Digital Geography Lab which represents travel time distances between statistical grid cells in Helsinki Region by public transport, walking and bicycling. The values in the travel time matrix are calculated using the door-to-door approach. For private cars this means that searching for parking, the parking proper and walking to one’s destination is a part of the travel time. Up until now the time it takes to carry out this process has been a singular estimation deployed to the entire Helsinki Capital Region. This does not represent reality well enough.

The data collected from this survey are used to answer the following questions: what is the variation in parking times between postal code areas in Helsinki Capital Region, what could cause the variation and what is the significance of the parking time in the context of the total travel time of a private car in Helsinki Capital Region. The finalised results of the Master’s thesis will be used to supplement the private car parking process data in the Helsinki Region Travel Time Matrix.

Filling the survey

In the survey the user is asked to estimate how their parking experience usually is in each postal code area. Please answer to each question using your best judgement and answer to each postal code area only once. We seek responses not older than two years because the urban structure of Helsinki Capital Region experiences constant change and possibilities for private car parking change with it. If you require additional information about the questions in the survey, please refer to the information dialog window in the survey. This window will appear on the screen of your device at survey start-up.

You can use a desktop computer, a laptop or a mobile device to fill out the survey. It requires 1-10 minutes of your time. On desktop or laptop it is important you use the latest browser software, recommendations being Chrome or Firefox. On mobile devices it is recommended to use a device that runs Android with Chrome being the browser software. If you wish to fill out the survey using your mobile device (especially if using an Apple device), please read the mobile usage instructions in the information dialog window.

Usage of gathered data

The data gathered in this survey do not reveal any personal information about respondents because of the general scope of the questions used. The web application running the survey will save your IP address for tracking user activity. In the analysis phase of the thesis all collected IP addresses will be altered into random and anonymous string of characters and all the IP addresses will be deleted. The survey web application uses cookies to save user preferences. If you do not delete the cookies manually, they will expire 90 days from their creation.

Further information

In any inquiries regarding the survey or the research, please contact Sampo by email: sampo.vesanen(at)

Diversity in digital urban spaces of Helsinki

Digital urban spaces of Helsinki seen from Instagram data have high language diversity, the topics of Finnish and English posts differ spatiotemporally and content-wise to some extent and more is discovered in my Master’s thesis. Finnish and English language posts dominate different areas of Helsinki and topics of Finnish posts have connections to everyday life while English topics are influenced by tourists

With ubiquitous internet access and increasing amounts of social media users and content, an ever larger part of social interactions and common discussions are being augmented with digital means of communication. This renders social media data valuable for scientific inquiry in order to understand contemporary societies, cultures, and phenomena. Social media data is being produced constantly in vast quantities and is mostly produced by users living in urban areas. The data produced in social media can have a reference to a real-world location e.g. in the form of a geotag or geographic coordinates enabling spatiotemporal analysis. In order for scientific knowledge to keep up with the quick changes in society and cultures enabled by the internet and social media, social media data sets need to be investigated and doing this requires powerful novel and interdisciplinary methods.

In my thesis, I delved into the digital urban space of Helsinki by applying topic modeling to Finnish and English Instagram posts’ captions from Helsinki. By looking at the topics of Instagram posts made in both English and Finnish languages, my aim was to discover how language affects Instagram topics, the spatiotemporal distributions of these topics and whether linguistic technologies are applicable in geographic research. In order to do all of this, a number of preprocessing steps were required. The language of the posts had to be identified in order to separate Finnish and English posts from another. After this, the caption texts were lemmatized to make LDA topic modeling viable. Lemmatization is a natural language processing technique with which inflected words are returned to their basic ‘dictionary’ form. For topic modeling of morphologically rich languages, such as Finnish, this is a critically important step without which LDA topic modeling would not yield sensible results, but it is recommended for English as well. Then the lemmatized captions were vectorized and fed into an LDA topic model which modeled language-specific topics for the Helsinki area and a few city districts.

Instagram posting activity in Helsinki follows a three-peak rhythmicity.
Instagram posting activity in Helsinki follows three-peak rhythmicity.

Plotting the hourly Instagram posting activity by each weekday reveals that Instagram posting frequency in Helsinki follows a three-peak rhythmic structure: peaking at common meal times each day of the week. The temporal structure also shows that Saturdays and Sundays are the most popular days to post on Instagram in Helsinki. These findings hint at a connection between Instagram posting in Helsinki and leisure time activities quite strongly, suggesting Instagram data might be suitable to find out where Instagram users are and what they’re doing on their own time.

The linguistic landscape of Helsinki from Instagram posts.

To decipher which topics are popular in Finnish and English Instagram posts, the language of the posts was identified revealing the diverse linguistic landscape of Instagram posts in Helsinki. By only focusing on Finnish and English, a lot of knowledge is lost in my analysis, underscoring the importance of a multilingual approach in future work. The geolinguistic division between Finnish and English Instagram posts in Helsinki shows a few key patterns. Firstly, the city center is the area of highest posting intensity, but smaller posting hubs appear along with major transport nodes in Helsinki. Secondly and perhaps more interestingly, central Helsinki is quite clearly divided in two between the languages. Finnish is more popular in areas north of Hakaniemi, while English comes out on top in the southern parts of the center. The main dividing line seems to be Töölönlahti and the small channel connecting Töölönlahti to the Baltic sea, which has historically been the dividing line between the working class in the north and the bourgeoisie in the south. The biggest relative differences between the languages are in peripheral areas with very low post counts suggesting that popular areas for posting are popular for both languages.

Two most common languages of Instagram posts in Helsinki divide the city.

Finnish and English Instagram posts’ topics differ both spatially and temporally at different scales, even though Instagram data was shown to be similar in content and temporal rhythm between the languages. Posts in both languages mostly deal with leisure-related topics, but Finnish topics have several references to everyday life, while English topics do not. Also, Finnish posts didn’t have one numerically dominant topic while as English posts did: ‘morning’. The spatial structure of the topics reflects the complexity of social media content, generality of the topics and the fact that posting location might not specifically relate to the topic of the post. Also, Instagram’s geotagging is based on points-of-interest which introduces slight to moderate spatial inaccuracy into the data as the exact posting coordinates are not recorded. There is, however, some spatial logic to the topics, for instance, the prevalent topic of Suomenlinna island is ‘summer’ for Finnish posts and ‘New Year’ for English posts, topics around the Olympic stadium revolve around sports. Statistically validating the connection between the topic and the underlying geographic region is highly problematic if the topic is very general.

Topics of Finnish Instagram posts in Helsinki aggregated into a 250-meter grid.

The topics become more specific at city district level which is to be expected with the limited spatial extent of a city district. However, at the city district level, the POI-based location structure becomes more problematic due to the aggregation of posts under POIs. At the city district scale, English topics have clearer references to touristic sights in the city districts suggesting a presence of tourists or at least sightseeing as an activity in the data set. Finnish topics, however, maintain a connection to everyday life with topics like “work”, “family” and “everyday life” and touristic sights are not mentioned.

There are a few things to consider when doing research with social media data. First, social media posts are often about subjects the user considers positive creating a positivity bias into the data. Second, results from social media analyses only represent the users of its particular social media platform and finding out to what extent this group represents the population as a whole is difficult. Third, the locational accuracy of posts isn’t in all cases very good, because geo-tagging functionality can be based on fixed points-of-interest and not to the actual coordinates of the user at the time of posting. This means that large amounts of posts can be and are aggregated on to commonly named points-of-interest. For instance, “Helsinki, Finland” was one of the most popular location names in the data and surprisingly consisted of numerous different points across Helsinki. Fourth, social media posts are multilingual and most of the tools for content analysis have been developed for English and most of social media research deal with English content. Including minor languages into the analysis would ensure a broader and less biased understanding of what is going on in social media. Fifth, social media companies are constantly developing and changing their APIs making access to data and reproducibility depend on the whims of social media corporations. Regardless of these error elements and limitations, social media data can be a very fruitful data set for scientific analyses of the city and (some of) its people.

Tuomas Väisänen

Here’s the link to my Master’s Thesis (only in Finnish)

Who are using urban bikes in Helsinki?

The users of the popular local bike-sharing system in Helsinki are mainly young adults and living in the downtown shows my recently finished master’s thesis. Almost 80 % of the trips were made by the users who were living in a postal area with at least one bike station in 2017, which shows how the service has been embraced especially by those living in the central ares of Helsinki.

The new bike-sharing season is here again and the system coverage are has expanded In Helsinki! Bike-sharing systems have become popular and attracted wide interest in Finland and elsewhere in recent years. Many cities have employed shared bikes, which aim to provide new mobility option for citizens. Shared bikes are also strongly linking to targets to increase the share of sustainable travel modes in cities, which partly explains their enthusiastic reception by many.

My master’s thesis titled as  ”Bike sharing as part of urban mobility in Helsinki – A user perspective”, which examined bike-sharing users is now accepted and published. The work, accepted with the highest grade, focused on bike-sharing users, usage patterns and how equally the system is serving the citizens. The aim of the work was to bring new information to support planning and development of the bike-sharing systems in Helsinki and elsewhere. I used a data set provided by Helsinki Region Transport and City Bike Finland, which contained all the bike-sharing trips (~1.5 million) from 2017. Before the data analysis, I had systematically reviewed almost 800 scientific articles focusing on bike sharing.

Internationally, bike-sharing system have been hugely popular and in the public discussion, the systems are often covered positively. Meanwhile, there has been critique in the scientific literature that shared bikes would only be serving certain population groups. This contradiction got me interested in to examine the local users in Helsinki more closely.

The study showed that in Helsinki, the use of bike-sharing system has been internationally high. Young adults are emphasized in the user base and especially when comparing by the number of trips, male users are over represented. Compared to regular cycling, the profile of bike-sharing users is less diverse than among all cyclists in Helsinki. Most of use is generated by those, who have a bike-sharing station in their neighborhood. The usage patterns of these users are also different compared to those who are living outside the station coverage area. For example, the users living outside the area have significantly higher shares of potential public transport integrated trips on average. Use activity and the subscription type were also found to be important factors shaping usage patterns.

The study also showed that bike-sharing systems have been actively and extensively studied. However, the study areas seemed to be concentrated to cities where bike-sharing data were available. This observation highlights the role and the need for open data in studying new mobility modes.

The upcoming summer will be interesting from my results’ perspective now when the bike-sharing system area in Helsinki expands. It remains to be seen whether the over-represented user groups were only more eager to quickly embrace the new system in 2017 or whether the same usage patterns still prevail after the expansion. From the equity perspective, the bike-sharing system will be now available to a larger group of citizens better than before. Young adults have found the system well, but it is important to pay attention that shared bikes and cycling are being promoted among the whole population to better advance and increase their role as part of sustainable urban mobility.

Elias Willberg

The full work can be found from here: MasterThesis_EliasWillberg

Animated visualization of the system dynamics can be found from here

Record number of abstracts for the NECTAR conference 2019!

The abstract selection for the NECTAR conference 2019 is now done! We received a record number of abstracts, 190, which was fantastic!

The conference, which will be organized by us and the University of Helsinki together with the Aalto University, Helsinki Institute for Sustainability Science (HELSUS), Urbaria, and the City of Helsinki takes place 5-7th June in Helsinki.

Registration links to the accepted participants have been sent via email!

There was a great deal of high-quality abstracts and the selection process was certainly not easy. The selection was done based the scope of the abstract, scientific quality, NECTAR membership and the possibility to fit the presentation in a coherent conference session. The sheer number of papers challenged us, but as the picture shows by sticking with the good old pen and paper style we were able to handle the task!

Looking forward to a great conference!

Call for papers now open for NECTAR 2019 conference!

Call for papers for NECTAR 2019 conference is now open!

Digital Geography Lab and University of Helsinki will organize an international NECTAR conference (5.-7. June 2019) in Helsinki together with the Aalto University, Urbaria and the City of Helsinki. NECTAR is a scientific research network concerned with transport and communication issues and the biannual conference brings together transport and mobility experts all over Europe and elsewhere.

We have two fantastic key note speakers in the conference, professors Jan Gehl from Denmark and Tim Schwanen from Oxford, UK.

The call for papers for the NECTAR 2019 conference has now opened, and closes on 21.1.2019.

The theme of the conference is “Towards Human Scale Cities – Open and Happy”. The conference calls for presentations on advancements in the field of transport, communication and mobility. The focus of the conference will be on urban transportation and the new possibilities that open data and digital technologies provide for mobility solutions. For example, presentations may discuss how transport policies are and should be changing, present emerging ways of organizing the daily mobility to make cities more sustainable and more pleasant or present novel ways of analyzing transportation and mobility from the perspective of people.

Welcome to “open and happy” Helsinki!*

*See more information and submit your abstract in the conference website:

The 24-h population dynamics of the Finnish Capital Region uncovered!

Figure 1. The estimated hourly distribution of people on an average weekday in the Finnish Capital Region based on network-driven cellular mobile phone data.

Understanding where people are and when – What is the pulse of the city? – is of high importance in urban planning, management and governance. Accurate information of the dynamic population distribution is crucial for example for land use and transport planning, disaster and conflict preparedness, evacuation purposes and for mitigating the spreading of diseases.

So far, our understanding of the whereabouts of people in time and space is scarce and predominantly based on static census data – people are expected to stay at home, although people rarely stay there the entire day. For instance, in (place-based) spatial accessibility research the use of home locations are considered as a proxy for origins of people despite the widely acknowledged criticism of the approach.

Fortunately, novel temporally sensitive spatial data sources, such as mobile phones, geotagged social media posts and smart cards can provide new solutions to uncovering the actual whereabouts of population in space and time.

In my thesis, I set out to uncover the spatio-temporal population dynamics in the Finnish Capital Region using mobile phone data. The data was provided by one of the main mobile network operators in Finland. Network-driven mobile phone data was interpolated to statistical 250 m x 250 m grid squares to estimate the hourly population distribution on a typical weekday (Monday-Thursday).

To refine the estimated population distribution derived from mobile phone data, I applied and adapted an advanced interpolation method developed by the Digital Geography Lab that uses ancillary information of land use, floor area and use type of buildings, and a time use survey to improve the accuracy of the results. The results were then validated against official census data during night-time (2 AM – 5 AM), which showed that the advanced interpolation method significantly improves the population distribution derived from mobile phone data.

Figure 2. The estimated hourly weekday distribution of people in six individual 250 m x 250 m grid cells. The graphs show the share of present population in the given grid square of the hourly total of all grid cells in HMA.

The results highlight, that network-driven mobile phone data can be used to catch the daily pulse of the Finnish Capital Region. The morning hours show a clear transition in the whereabouts of people from residential areas to work place areas. The afternoon pattern is however not as straightforward – people may stop by a store or undertake leisurely activities on their way back home. As a matter of fact, population concentrations in the shopping malls and recreational areas are highest in the evening according to the results. Also, the polycentricity of the study area as well as the incoming and outgoing population flows along the major roads in the morning and afternoon can be distinguished from the data.

The typical home-work-home rhythm can clearly be seen for instance in the Aalto University campus area in Otaniemi. During day time, the concentration of population is highest in the campus area, but as the evening draws closer, the concentration shifts to the Teekkarikylä residential area at the end of the cape.

So, what’s next? I will implement the dynamic population distribution to examine the 24-h accessibility to grocery stores and introduce the first fully dynamic accessibility model in the study area using an approach developed by the Digital Geography Lab. Stay tuned!

Claudia Bergroth,

Geoinformatics MSc. Student

After publishing this post the dataset has been released: A 24-hour dynamic population distribution dataset based on mobile phone data from Helsinki Metropolitan Area, Finland

DGL organizes a session at the Annual Meeting of Finnish Geographers 2018!

Digital Geography Lab organizes a session at the Annual Meeting of Finnish Geographers 2018: Cross-Bor­der Dia­lo­gues & Fin­land: Hu­man Mo­bi­li­ties, Social In­te­rac­tions & Trans­na­tio­na­lism.

Send your abstract to our session by September 23 or just come to see interesting presentations!

Session description:

Session chairs: Olle Järv, Kerli Müürisepp & Tuuli Toivonen  (Digital Geography Lab, University of Helsinki)

In the EU “borderless world”, cross-border interactions and integration are regarded as key drivers towards socially and economically more cohesive territorial development and well-functioning societies. Increasing human mobilities and socio-spatial interactions transcending state borders have a role in forming many societal phenomena such as new functional cross-border regions, transnational people and transnationalism, at large. These developments have further implications on societies in relation to integration processes, identity formation, social (in)equalities, governmentality, planning and security, among many others.

Cross-border interactions between Finland and its neighbouring countries follow the overall trend. For instance, while tens of thousands of people have their daily lives already connected to both Finland and Estonia, stakeholders advance the Helsinki-Tallinn twin-city concept by planning and executing new strategic infrastructure projects to better connect the countries. As cross-border mobility flows grow, a more comprehensive understanding about complex socio-spatial practices beyond state borders and its consecutive impacts on societies is needed. In addition to conventional approaches, the application of novel (big) data sources allows to develop new theoretical concepts and methodologies to provide valuable insights for given research.

The session aims to present and discuss theoretical, methodological and empirical research on cross-border mobilities and interactions, transnationalism, and implications on societies it involves. A concentrated discussion is facilitated at the end of the session.

The topics we welcome include, but are not limited to:

  • cross-border human mobility (daily, leisure, migration);
  • social and spatial interactions of people from the neighbouring countries in Finland;
  • transnational people and transnationalism;
  • inequality and segregation;
  • social engagement and integration;
  • applications of novel (big) data sources and new methodologies;
  • functional cross-border regions/transnational spaces;
  • Estonians and Russians in Finland.

All sessions descriptions at the 2018 Meeting can be found here

The Travel Time Matrix 2018 for the Helsinki metropolitan area is out!

Digital Geography Lab has published the 2018 version of the Helsinki Region Travel Time Matrix. The matrix contains travel times and distances between all 250 meter grid squares in the capital region of Finland, with public transportation, car, bike and walking, at different times of the day.

The previous versions of the matrix have been published in 2013 and 2015, allowing analyses of travel time changes due to big infrastructure projects in the region. Biking is included in the matrix for the first time. The data is available openly, alongside with the tools that were used to produce it.

Comparisons between different travel modes and years reveal interesting patterns in the accessibility of the Helsinki region. The most accessible grid squares have moved northwards from the city center. Still, the central area of the city is the best reachable by public transportation, while the ring roads in the outskirts of the city are well-reachable by the car-driving population. Biking is a competitive mode of transportation and beats other modes of transport in distances shorter than 5 km, a bit depending on the place and naturally the speed of the biker. The Travel Time Matrix provides biking travel times for fast and slow bikers. The speeds have been estimated based on Strava sports application, as well as city bike system of Helsinki.

The big infrastructure changes like the opening of a new metroline (Länsimetro) has had moderate impact on the accessibility of the region. The travel times have become shorter on average in Lauttasaari and Otaniemi, and longer in parts of Espoo.

Download the data from here.

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