The largest city in Finland is Helsinki with 684,018 inhabitants. Helsinki is the capital of Finland, and it is located in the south within the Uusimaa region. In 2024, the second largest city was Espoo, a city located in the Greater Helsinki metropolitan area, which had approximately 320,900 inhabitants. After the cities of Helsinki and Espoo, the third largest and most populous city outside the capital region was Tampere, with roughly 280,200 inhabitants. The Finnish population is highly concentrated in southern Finland The total population of Finland is roughly 5.64 million. Finland is one of the most sparsely populated countries in Europe, and the population is highly concentrated in the southern and southwestern parts of the country. Since 1915 the population of Finland grew steadily from 3.1 million to more than 5.64 million inhabitants. But the upwards trend slowed down in recent years. The median age of the Finnish population is rising While the population growth slowed down the Finnish population also got older. The media age increased from 38.4 years in 2000 to 43 years in 2024. The estimated median age for the Finnish population in 2035 was 45.3 years.

Population in largest city in Finland was reported at 1346810 in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Finland - Population in largest city - actual values, historical data, forecasts and projections were sourced from the World Bank on October of 2025.

The most populous area in Finland is the capital region of Uusimaa, with almost 1.8 million inhabitants as of 2024. Almost one third of the 5.64 million population lived in the capital city and the surrounding Greater Helsinki area. The second-largest region in terms of population was Pirkanmaa, inhabited by 545,406 people. Three out of the ten largest cities located in Uusimaa The Uusimaa region also has Finland's highest population density with roughly 195.7 inhabitants per square kilometer. Pirkanmaa's population density is only 41.2 inhabitants per square meter. Out of the 10 largest cities in the country, three are located in the Uusimaa region, including the capital city Helsinki. Changing population structure The population of Finland is expected to grow in the following decade, reaching 6.18 million in 2050. However, the population is aging rapidly, as the number of inhabitants aged 75 years and older continues to increase in the future. At the same time, the population aged 14 and younger is estimated to constantly decline.

Finland FI: Population in Largest City data was reported at 1,259,875.000 Person in 2017. This records an increase from the previous number of 1,240,942.000 Person for 2016. Finland FI: Population in Largest City data is updated yearly, averaging 820,866.000 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 1,259,875.000 Person in 2017 and a record low of 448,192.000 Person in 1960. Finland FI: Population in Largest City data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Finland – Table FI.World Bank: Population and Urbanization Statistics. Population in largest city is the urban population living in the country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; ;

The number of children in early childhood education and care by age group and type of care since 2002, the attendance days of municipal day care centres from 2005 onwards and the number of employees since 2008, and the cost of the early childhood education system from 2009 in the six largest cities in Finland.

The reviews of early childhood education and care monitor the use and costs of early childhood education and care provided by municipalities and municipalities as outsourced services, private care support and service vouchers, as well as the use and costs of child home care support. The review also includes pre-primary education in accordance with the Basic Education Act and open early childhood education activities in accordance with the Act on Early Childhood Education.

The sixth cities are made up of the six most populous cities in Finland. The six cities in the order of the population include Helsinki, Espoo, Tampere, Vantaa, Turku and Oulu. The six working groups compare the social and health services of cities and early childhood education and care services. Data on customer numbers, performances, personnel and costs are mainly compiled from municipalities’ own information systems and financial statements. City experts agree on as uniform definitions as possible for data collection and implement the data collection in practice.

These recommendations are intended as a general policy to be applied alongside the strategic policies, principles and guidelines that often guide ICT and service development in cities. From a technological and service-oriented standpoint, the significance of APis is, mostly due to accelerating digitalisation, increasing at such a pace that a need has emerged for a document that describes the importance of APIs and the goals related to them from the perspective of the cities.

This document presents the consolidated view of the Six largest cities in Finland on how to develop open APIs through inter-city cooperation. The Six cities are Helsinki, Espoo, Vantaa, Tampere, Turku and Oulu.

In 2021, 98 percent of the Finnish households in the capital region had an internet connection. The corresponding figure for households in other large cities was 91 percent, and for households in rural areas 88 percent.

In 2023, 90 percent of internet users in Finland had used online banking services within the last three months. 94 percent of people in the capital region, and 93 percent of people in large cities used online banking services. The corresponding share in rural municipalities was 85 percent that year.

Data description:

This data is collected as part of the Urban Happiness project and includes the following datasets: Home locations, everyday errand points, Helsinki experience points, and Espoo experience points.

Who collected (person/organization):

The dataset is collected in department of Built Environment, Aalto University, Finland, in Prof. Marketta Kyttä’s research team.

Funding: The research was financed by the National Technology Agency of Finland. In addition, the cities of Espoo, Helsinki, and Turku, Ministry of the Environment, the Finnish Transport Agency, FCG Planeko Ltd, and Skanska Ltd helped to finance the project.

when collected the data:

Data is collected in 2009

Data characteristics:

Age range: Data is collected from individuals aged 15-65

Geographical area: The data is collected from Helsinki and Espoo

Spatial reference: ETRS89_TM35FIN_E_N

Data quality:

Tools and methods: The data was collected using the Maptionnaire tool (maptionnaire.com) (aka. SoftGIS) from a randomly collected sample of 15982 individuals.

Link to survey (if applicable): NA

Anonymization: The home locations are spatially anonymized using a customized Gaussian perturbation algorithm developed by the research team. Largest displacements were typically applied in the least dense areas. Sensitive data and attributes are removed.

Other points have been also randomly anonymized to a lesser extent.

The data addresses the dynamics of coexistence and conflict in increasingly diverse cities from a human-centred perspective. It was collected as part of the EU-funded project Coexistence and Conflict in the Age of Complexity (EmergentCommunity) in nine European cities in Finland, France, and Sweden. The dataset comprises of two parts: EmergentCommunityEthno (qualitative data) and EmergentCommunityVR (quantitative and qualitative data) that were collected during the project. In addition to these, desk research was conducted and these files have been included in the metadata description.

EmergentCommunityEthno (dataset 1):

Across the nine cities, participants consisted of people above 15-years of age, living in the studied urban neighbourhoods or using their public spaces. In Finland, data were collected in the neighbourhoods of Peltolammi and Multisilta in Tampere, in Malmi in Helsinki, and in Martti and Paavola in Hyvinkää. In Tampere, part of the data (n=31 interviews) was collected in collaboration with the EKOS research project (this part of the data is described and archived in the Finnish Social Science Data Archive, DoI: https://doi.org/10.60686/t-fsd3816). The second part of the data was collected in Sweden. The data collection sites there were the neighborhoods of Möllevången and Nydala in Malmö, Farsta and Rågsved in Stockholm, and Fröslunda and Årby in Eskilstuna. The French data were collected in the La Plaine area in Marseille; in La-Chapelle-Saint-Luc, Saint-Andre-Les-Vergers and Les Chartreux in Troyes; and in Guillotière in Lyon.

Across these sites shared methods were used in data collection, consisting of thematic interviews, walking interviews, and observations. The dataset emphasizes the diversity of experiences and the manifestations of distinctions in diverse urban environments and examines the ways in which people form bonds in relation to each other, their neighborhoods, and the broader society.

The first set of participants were located through social media groups (Facebook), from the premises of associations organizing community activities in the areas, libraries, cafes, community events, and youth centers. After this, snowball sampling was used, in addition to which targeted recruitment was applied if a population group represented in the area was completely missing from the dataset. Ethnographic observations were conducted in public spaces, community centres, cafés, stations, and shopping centres that were selected as potentially interesting places based on extant scholarship on living with difference and urban encounters. Here, attention was paid at how people used these sites, who were there and who were absent, as well as how people moved in and across the sites. Notes were made of what kinds of encounters, patterns of behaviour, cooperations, and conflicts occurred. These observations were made at various times of the day, to capture potential temporal changes. This resulted in a rich collection of fieldnotes, sketches, photographs, and movement maps.

Relevant files: 1) EmergentCommunity ethnographic matrix.pdf, 2) EmergentCommunityEthno interview questions.docx, 3) EmergentCommunity_metadata public.xlsx (contains all metadata from the project), 4) EmergentCommunityEthno_metadata.csv (contains metadata only on desk research, ethnographic interviews and fieldnotes).

EmergentCommunityVR (dataset 2):

Data collection was conducted in Helsinki, Marseille, and Malmö. The data was collected using 360-degree videos based on the aforementioned ethnographic data as stimuli to which participants were exposed. A separate video was created for each city, using specifically the data collected therein. We put together a mobile laboratory set-up that travelled to each city and collaborated with local NGOs whose premises were used as our laboratory space. The equipment and software used are explained in the document "EmergentCommunity mobile laboratory.pdf".

The inclusion criteria for participation were: being a major, healthy, not having hearing or vision impairments, being a resident in the city that the video depicted, and knowledge of the local language in which the video was executed. During the viewing of the video stimulus, participants' physiological responses were measured and their eye movements were tracked. VR eye tracking was used as it enables the precise analysis of gaze behaviour – such as fixations and saccades – within immersive, ecologically valid environments. Regarding physiological signals, the focus was on the electrical activity of the heart using electrocardiography (ECG), the electrical activity of the facial muscles using facial electromyography (fEMG), and the electrical conductivity of the skin using galvanic skin response (GSR). To complement the physiological data, a multimodal setup was established to assess the affective content of the stimulus in terms of arousal/valence, avoidance/approach, and unpredictability. After viewing, the participants were asked to evaluate the intensity of their emotional experience and to name the emotional reactions elicited by the video using a questionnaire carried out with Gorilla Experiment Builder. The questionnaire also contained background questions, from basic participant information, such as age and gender, to aspects that relate to diversity and inequality in contemporary societies: language, income, housing, education, political activity, participation, as well as political opinions and social values. After completing the measurements and the questionnaire, participants were interviewed about their experience and the thoughts it provoked, and they were asked to share information regarding their daily lives.

The purpose of the dataset was to help understand the formation of emotional experiences and the significance and functioning of emotions in the everyday life of increasingly diverse and unequal cities. The call for participation was distributed in several thematic Facebook groups (related to e.g., urban development, multiculturalism, neighborhood, local NGOs and minority communities) and via Instagram, as well as through flyers/posters in libraries, local associations, shopping centers, cafes, and on the project's Facebook page and Instagram profile. In the case of Marseille and Malmö, local assistants were used to spread the invitation within their networks and distribute participation invitation leaflets on the streets. In each city, it was possible for already registered participants to invite additional participants as well. Overall, the goal was to ensure the representativeness of the data in terms of age, gender, and minority status.

Relevant files: 1) EmergentCommunity video stimuli.pdf, 2) EmergentCommunityVR interview questions.pdf, 3) EmergentCommunityVR Gorilla questionnaires.pdf, 4) EmergentCommunity mobile laboratory.pdf, 5) EmergentCommunity_metadata public.xlsx (contains all metadata from the project), 6) EmergentCommunityVR interviews.csv (contains metadata on interviews done after watching the 360-degree video), 7) EmergentCommunityVR physio.csv (contains metadata on physiological measuring and questionnaires).

Purpose of the data

The EmergentCommunity project aimed at producing knowledge about what community means and how it is formed in increasingly diverse societies, as well as the conflicts and tensions that everyday life brings out. The project empirically examined the concrete challenges that societal changes produce for cities and coexistence. The aim was to identify how peaceful coexistence could be supported and population relations promoted in urban everyday life. The project emphasized that community relations and everyday coexistence are affective, social, and spatial phenomena, which is why a wide range of research methods from ethnography and observation to psychophysiological measurements and interviews were applied. These approaches were brought into dialogue through virtual reality by utilizing ethnography-based 360-degree videos depicting everyday life in the latter part of the project (EmergentCommunityVR). Thus, the project created new understanding of emotions formed in everyday life and produced unique knowledge in the fields of psychological and sociological emotion research. Bringing these areas together enabled a critical examination of the concept of community and the identification of the practices and ways in which communities are produced in the everyday life of diverse and unequal cities (see CORDIS database for public description, results, and reporting).

Throughout the data collection, the research focused on everyday life and the forms, practices, and interpretations of everyday coexistence in public urban spaces in the selected research neighbourhoods. Participants were also asked to share their experiences, interpretations, and views on societal change and how the change has been visible in their own neighborhoods and what thoughts and feelings it evokes in them. The data was formed through non-probability sampling (self-formed sample).

The research sites were selected by examining statistics, policy reports, and available data on demographic changes and diversity, income inequality, trends of residential and ethnic segregation in different countries and cities (desk research). We chose the countries and cities so that they would complement each other and that changes were observable in each selected context, although their forms, emphases, and manifestations might vary. After this extensive background review, we focused on the city level, complementing the available

The 2008 financial crisis and the subsequent austerity measures were harsh on cities. Despite receiving little academic attention, in progressive Nordic countries, such as Finland, cities faced fiscal stress and implemented austerity. As a solution to cities’ budget deficits, austerity became a widely accepted ‘common-sense' policy. During this time, the seemingly contradictory sustainability policies increased support. This article analyses how austerity and sustainability, narrated as common-sense solutions, changed the urban development policy in Tampere. The narrative analysis identifies a significant change in urban policy that occurred during the recession. At first, an ‘austerity for efficiency' narrative argued that urban development and sustainability must meet the budget and service provision should be economically efficient. During the recession, a ‘green growth' narrative began to assert that growth investments in sustainable city development could be financed with debt, while service provision must meet fiscal austerity. The city’s political elite made narrative arguments to justify downsizing the public sector while at the same time using sustainability to justify debt investments in urban development, enabling private investments. Despite containing contradictory elements, the ‘common-sense' neoliberalism of the Finnish city is to boost sustainable city development and gradually shrink the welfare state.

Valtakunnallisessa yhdyskuntarakenteen seurannassa (YKR) kaupunkiseutu muodostuu suurimpien kaupunkikeskusten keskustaajamasta, siihen fyysisesti ja toiminnallisesti tiiviisti liittyvistä lähitaajamista sekä näitä ympäröivästä lievealueesta, joka on haja-asutusaluetta. Kaikkiaan Suomessa kaupunkiseutuja on 34, joista kolme on kaksoiskaupunkeja. Keskustaajamia ovat sellaiset taajamat, joissa väestömäärä oli vuoden 2000 taajamarajauksessa yli 15 000 ja taajama ei ole kaupunkiseudun lähitaajama. Näille keskustaajamille muodostetaan kaupunkiseudut ja joiden kehitystä rajauksella seurataan. Kaksoiskaupungit muodostuvat sellaisista keskustaajamista, joiden reunat ovat alle viiden kilometrin päässä toisistaan ja jotka ovat väestömäärältään samaa kokoluokkaa. Lähitaajama kuuluu kaupunkiseutuun aina siinä tapauksessa jos etäisyys keskustaajaman reunaan on enintään kolme kilometriä. Lähitaajama kuuluu kaupunkiseutuun myös siinä tapauksessa, jos se on yli kolmen kilometrin päässä keskustaajamasta, mutta sen työllisistä yli 20 % käy töissä keskustaajamassa ja lähitaajaman ja keskustaajaman välillä on yhtenäinen alue, jossa talotiheys yhden kilometrin säteellä on yli 45 ja lähitaajaman reuna on alle 40 kilometrin päässä keskustaajaman toiminnallisesta keskipisteestä. Lähitaajaman ja keskustaajaman välillä on oltava myös suora tieyhteys ja kaupunkiseudun on muodostettava lievealueineen yhtenäinen kokonaisuus.

Lähitaajama voi kuulua ainoastaan yhteen kaupunkiseutuun ja ollessaan kriteereiltään osa useampaa kuin yhtä kaupunkiseutu, taajama katsotaan kuuluvaksi suurempaan kaupunkiseutuun. Lievealue on kaupunkiseuduille muodostuva yhtenäinen alue, joka ulottuu viiden kilometrin päähän keskustaajaman ulkoreunasta ja kolmen kilometrin päähän kaupunkiseudun lähitaajaman ulkoreunasta. Lievealueeseen eivät kuulu vesistöt, Suomen rajojen ulkopuoliset alueet, eivätkä kaupunkiseutujen ulkopuoliset taajama-alueet. Aineisto kuuluu SYKEn avoimiin aineistoihin (CC BY 4.0).

Avoin tieto -palvelussa jaossa on aina uusin versio, joka päivitetään keskimäärin kahden vuoden välein sekä joka viidennen vuoden versio alkaen vuodesta 2010. Ympäristöhallinnon sisäiseen käyttöön aineisto on

saatavissa viisivuosittain alkaen vuodesta 1990 lukuunottamatta vuotta 1995.

Kaupunkiseutujen muodostamisen lähtötietoina käytetään aina uusimpia mahdollisia YKR-tietoja. Kuitenkin muun muassa työmatkatieodot ovat siihen vuoteen nähden, jota kaupunkiseudut kuvaavat yleensä kaksi vuotta vanhoja. Tämä johtuu aineistojen tuotannossa olevasta viiveestä.

Käyttötarkoitus: YKR-kaupunkiseudut on rajattu SYKEssä yhdyskuntarakenteen seurannan tarpeisiin.

Lisätietoja: https://geoportal.ymparisto.fi/meta/julkinen/dokumentit/YkrKaupunkiseutu.pdf http://www.ymparisto.fi/fi-FI/Elinymparisto_ja_kaavoitus/Yhdyskuntarakenne/Tietoa_yhdyskuntarakenteesta/Kaupunkiseutujen_rajaus

The YKR Urban Regions is a spatial dataset based on the Monitoring System of Spatial Structure and Urban Form (YKR). The definition of urban regions is based on the delineation of localities. The Urban regions consist of the urban localities, which exceed population threshold of 15 000 inhabitants, neighboring localities, which are physically and functionally connected to the urban localities and surrounding urban fringe areas with sparse population.

In total there are 34 urban regions in Finland, out of which three are so called twin cities. Twin cities are formed from two urban localities having less than a 5 km distance between their borders and share approximately the same amount of inhabitants.

An urban locality is formed of a locality (densely populated area) with a population of at least 15 000 inhabitants and which is not categorized as a neighboring locality of another larger urban region.

If the distance from the border of a neighboring locality is less than three kilometers to the border of an urban locality, it is invariably included in an urban region.

If the distance from the neighboring locality to the functional center of the urban locality is more than three kilometers, but less than 40 kilometers, and at least 20% of the working population is commuting to the urban locality, the area is included in the urban region. However, in these cases, there has to be also a continuous residential area, with more than 45 residential buildings per km² between the urban locality and the neighboring locality. There must also be direct road access between the urban and neighboring locality. If these criteria are met, the area is included in the urban region.

A neighboring locality can be connected to only one urban locality at a time. In conflict situations the locality in question is joined to the largest of the urban regions. The urban fringe area is a continuous area surrounding urban regions. It extends five kilometers from the border of the urban locality and three kilometers from the border of the neighboring locality. The urban fringe area does not include water areas, areas outside Finnish national borders or localities outside urban regions.

The Finnish title of the dataset is YKR Kaupunkiseudut.

This dataset belongs to SYKE’s open data collection (CC BY 4.0).

Syke’s open information service delivers the most current version of the dataset, which is updated at five year intervals. For the internal use in environmental administration the data is available at five year intervals from 1990 onwards with the exception of 1995.

Urban regions are always formed using the most current YKR-data available. In some cases (e.g. YKR-commuting data) YKR-data is outdated compared to the year that the urban regions represent. This results from the delays in the data production processes.

Purpose of use: The urban regions dataset is used internally in Finnish Environmental Institute for tasks related to the monitoring of urban changes.

More information: http://www.ymparisto.fi/en-US/Living_environment_and_planning/Community_structure/Information_about_the_community_structure/Delineation_of_densely_populated_areas

Kaupunkiseutu rajauksen lähtöaineistona on SYKEssa muodostettu saman vuoden YKR-taajama rajaus, joka perustuu 250 x 250 metrin ruudukkoon. Rajauksessa huomioidaan asukasluvun lisäksi, rakennusten lukumäärä, kerrosala ja keskittyneisyys.

Prosessointihistoria: Kriteerit lyhyesti:
1. Etäisyys keskustaajamaan alle 3 kilometriä TAI
2. Työssäkäynti keskustaajamaan yli 20 % taajaman työllisistä JA
3. Keskustaajaman ja lähitaajaman välillä yhtenäinen alue, jossa talotiheys kilometrin säteellä yli 45 JA 4. Lähitaajaman reuna alle 40 kilometrin päässä keskustaajaman toiminnallisesta keskipisteestä JA
5. Keskustaajama, lähitaajamat ja lievealue muodostavat yhtenäisen kokonaisuuden
a. Keskustaajaman ja lähitaajaman välillä suora tieyhteys
b.Kaupunkiseutuun ei muodostu erillisiä saarekkeita

Menetelmä lyhyesti: Kaupunkiseuduille on muodostettu keskustaajamat hakemalla taajama-aineistosta ne taajamat, joiden väestömäärä oli yli 15000 vuoden 2000 taajamarajauksessa. Kaksoiskaupungit muodostetaan näistä tekemällä taajamille viiden kilometrin etäisyysvyöhyke ja vertaamalla tähän vyöhykkeeseen osuvien taajamien väestömääriä keskenään. Jos väestömäärien ero on alle 100 000 asukasta, muodostuvat keskustaajamat kaksoiskaupungiksi. Ensimmäisessä vaiheessa merkitään ne taajamat, jotka ovat alle kolmen kilometrin päässä keskustaajamasta

(1). Seuraavassa vaiheessa menetelmässä lasketaan työssäkäynti kustakin lähitaajamasta keskustaajamiin. Uusin 250x250 metrin ruutukohtainen työssäkäyntiaineisto yhdistetään työllisen asuinruudun perusteella taajamiin ja lasketaan kuinka suuri osuus taajaman työllisistä käy töissä kussakin keskustaajamassa. Taajamat, joista yli 20 % käy töissä keskustaajamassa täyttävät kriteerin

(2). Kolmannessa vaiheessa muodostetaan alueet, jotka kuvaavat taajamien välistä rakentamisyhteyttä YKR:n rakennustietojen perusteella

(3). Pistemäinen aineisto muutetaan ensin 250 metrin rasteriksi ja yleistetään focal-sum menetelmällä, jossa jokaiseen ruutuun summataan rakennusten määrä 1km:n säteeltä. Aineisto luokitellaan vielä niin, että kriteerin (45 rakennusta) täyttävät ruudut saavat arvon 1 ja kriteerin alle jäävät saavat arvoksi NoData. Neljännessä vaiheessa merkitään ne taajamat, joiden reuna on alle 40 kilometrin päässä keskustaajaman toiminnallisesta keskipisteestä

(4). Viimeisessä vaiheessa muodostetaan varsinaiset kaupunkiseudut kriteerien perusteella valitsemalla kullekin keskustaajamalle ensin ne taajamat, jotka toteuttavat ensimmäisen kriteerin. Tämän jälkeen valitaan ne taajamat, jotka toteuttavat kriteerit kaksi, kolme ja neljä ja yhdistetään ensimmäisen kriteerin toteuttaviin taajamiin. Tästä aineistosta poistetaan vielä toisten kaupunkiseutujen keskustaajamat sekä tarkastetaan, että suoran tieyhteyden kriteeri toteutuu. Lopuksi kaupunkiseudut yhdistetään, mahdolliset päällekkäisyydet poistetaan ja muodostetaan lievealue laskemalla keskustaajamille viiden kilometrin ja lähitaajamille kolmen kilometrin etäisyysvyöhyke, joista poistetaan vesialueet ja Suomen ulkopuoliset alueet. Lopuksi tarkastetaan vielä, että kaupunkiseudut muodostavat lievealueen kanssa yhtenäisiä kokonaisuuksia.

The urban regions dataset is a spatial delineation process produced on the basis of the Monitoring System of Spatial Structure and Urban Form (YKR). YKR is is a spatial grid-based information system maintained annually by the Finnish Environment institute (SYKE).The urban region delineation process applies the delineation of densely populated areas (localities) on a statistical 250m x 250 m grid as the source data. The delineation of the urban regions is carried out based on the number