Maps

A map portrays a new urban-rural typology based on the grid-level data. New Nordic urban-rural typology is a grid-based classification of areas developed by the Nordic Thematic groups 2021-2024 to enable more accurate cross-Nordic statistical comparisons. The seven classes are defined based on population density, proximity measures and land cover parameters. Read more about the typology here . Inner urban area is the most densely populated part of the urban core. Urban cores are clustered cells summing up to at least 15 000 inhabitants, and these are divided into Inner and Outer urban areas based on density criterion (population density and building floor space). Outer urban area is the least densely populated part of the urban core. Urban core areas are clustered cells with at least 15 000 inhabitants, and these are divided into Inner and Outer urban areas based on density criterions (population density and building floorspace). Peri-urban area is the intermediate zone between urban core and the rural. It is based on generalized travel-time estimates from the edges of outer urban areas (6 min travel-time zones) and smaller urban settlement (4,5 min travel-time zones). Local centers in rural areas are population centers located outside urban areas, small towns and large parish villages where population is between 5000-14999 inhabitants. Rural areas close to urban areas have a rural character that are functionally connected and close to urban areas. In average this means 20-30 of minutes’ drive time from the edge of outer urban area. This class overwrites the area classes ‘Rural heartland’ and ‘Sparsely populated rural areas’.  Rural heartland. Rural areas with intensive land use, with a relatively dense population and a diverse economic structure at the local level. Most of the agricultural land is in this class. Sparsely populated rural areas. Sparsely populated areas with dispersed small settlements that are located at a distance from each other.…

A map portrays a new urban-rural typology based on the grid-level data. New Nordic urban-rural typology is a grid-based classification of areas developed by the Nordic Thematic groups 2021-2024 to enable more accurate cross-Nordic statistical comparisons. The seven classes are defined based on population density, proximity measures and land cover parameters. Read more about the typology here . Inner urban area is the most densely populated part of the urban core. Urban cores are clustered cells summing up to at least 15 000 inhabitants, and these are divided into Inner and Outer urban areas based on density criterion (population density and building floor space). Outer urban area is the least densely populated part of the urban core. Urban core areas are clustered cells with at least 15 000 inhabitants, and these are divided into Inner and Outer urban areas based on density criterions (population density and building floorspace). Peri-urban area is the intermediate zone between urban core and the rural. It is based on generalized travel-time estimates from the edges of outer urban areas (6 min travel-time zones) and smaller urban settlement (4,5 min travel-time zones). Local centers in rural areas are population centers located outside urban areas, small towns and large parish villages where population is between 5000-14999 inhabitants. Rural areas close to urban areas have a rural character that are functionally connected and close to urban areas. In average this means 20-30 of minutes’ drive time from the edge of outer urban area. This class overwrites the area classes ‘Rural heartland’ and ‘Sparsely populated rural areas’.  Rural heartland. Rural areas with intensive land use, with a relatively dense population and a diverse economic structure at the local level. Most of the agricultural land is in this class. Sparsely populated rural areas. Sparsely populated areas with dispersed small settlements that are located at a distance from each other.…

The map portrays the urban-rural typology based on the municipal level data.

The map shows the population change by component 2010-2019. The map is related to the same map showing regional and municipal patterns in population change by component in 2020. Regions are divided into six classes of population change. Those in shades of blue or green are where the population has increased, and those in shades of red or yellow are where the population has declined. At the regional level (see small inset map), all in Denmark, all in the Faroes, most in southern Norway, southern Sweden, all but one in Iceland, all of Greenland, and a few around the capital in Helsinki had population increases in 2010-2019. Most regions in the north of Norway, Sweden, and Finland had population declines in 2010-2019. Many other regions in southern and eastern Finland also had population declines in 2010-2019, mainly because the country had more deaths than births, a trend that pre-dated the pandemic. In 2020, there were many more regions in red where populations were declining due to both natural decrease and net out-migration. At the municipal level, a more varied pattern emerges, with municipalities having quite different trends than the regions of which they form part. Many regions in western Denmark are declining because of negative natural change and outmigration. Many smaller municipalities in Norway and Sweden saw population decline from both negative natural increase and out-migration despite their regions increasing their populations. Many smaller municipalities in Finland outside the three big cities of Helsinki, Turku, and Tampere also saw population decline from both components. A similar pattern took place at the municipal level in 2020 of there being many more regions in red than in the previous decade.

The map shows the annual average internal net migration in 2010-2019. The map is related to the same map showing net internal migration in 2020. The maps show several interesting patterns, suggesting that there may be an increasing trend towards urban-to-rural countermigration in all the five Nordic countries because of the pandemic. In other words, there are several rural municipalities – both in sparsely populated areas and areas close to major cities – that have experienced considerable increases in internal net migration. In Finland, for instance, there are several municipalities in Lapland that attracted return migrants to a considerable degree in 2020 (e.g., Kolari, Salla, and Savukoski). Swedish municipalities with increasing internal net migration include municipalities in both remote rural regions (e.g., Åre) and municipalities in the vicinity of major cities (e.g., Trosa, Upplands-Bro, Lekeberg, and Österåker). In Iceland, there are several remote municipalities that have experienced a rapid transformation from a strong outflow to an inflow of internal migration (e.g., Ásahreppur, Tálknafjarðarhreppurand, and Fljótsdalshreppur). In Denmark and Norway, there are also several rural municipalities with increasing internal net migration (e.g., Christiansø in Denmark), even if the patterns are somewhat more restrained compared to the other Nordic countries. Interestingly, several municipalities in capital regions are experiencing a steep decrease in internal migration (e.g., Helsinki, Espoo, Copenhagen and Stockholm). At regional level, such decreases are noted in the capital regions of Copenhagen, Reykjavík and Stockholm. At the same time, the rural regions of Jämtland, Kalmar, Sjælland, Nordjylland, Norðurland vestra, Norðurland eystra and Kainuu recorded increases in internal net migration. While some of the evolving patterns of counterurbanisation were noted before 2020 for the 30–40 age group, these trends seem to have been strengthened by the pandemic. In addition to return migration, there may be a larger share of young adults who…

The map shows the annual average international net migration from 2010 to 2019. The map is related to the same map showing net migration in 2020. At regional level, there are only minor changes between the net migration in 2010-2019 and 2020. All regions of Norway, all regions of Sweden except Gotland and Uppsala, and the regions of Österbotten in Finland, Midtjylland in Denmark and Norðurland eystra in Iceland experienced a slight decrease in international net migration I 2020 compared to 2010-2019. There is a more marked increase in net migration in the Faroe Islands, Greenland and the region of Norðurland vestra in Iceland, and a slight increase in the region of Austurland in Iceland. At municipal level, the maps show more changing patterns. In Denmark, Norway and Sweden, several municipalities – both in the capital, intermediate, and rural regions – had lower levels of international net migration in 2020 compared to 2010-2019. In Iceland and Finland, the picture is more balanced, with some municipalities showing a decrease, others an increase. In the Faroe Islands and Greenland, several municipalities/regions had an increase in international net migration.

The map shows the geographical delimitation of cross-border regions and committees financed by the Nordic Council of Ministers as of December 2021.

The map shows annual average immigration flows above 3,000 people, and the growing diversity in their countries of origin Sweden and Denmark, in particular, experienced large inflows from non-Nordic countries during the period 2010-2019, with Sweden standing out as the Nordic country with by far the largest immigrant in-flows. A large portion of these arrivals were from war-torn Syria (an annual average of almost 15,000), followed by Poland (approximately 4,500), United Kingdom, Iraq, India and Iran (around 4,000 each). Denmark experienced a smaller number of inflows above 3,000 people, compared to Sweden. The largest non-Nordic inflows to Denmark were around 5,000 people (per sending country) and included migrants from the U.S., Germany, Romania and Poland. For Norway, large non-Nordic in-flows were limited to Lithuania and Poland. Similarly, Finland had only one major inflow, from Estonia.

The map shows the share of cross border commuters in the total employees with residence in a NUTS2 Nordic Region in 2015. The darker the blue, the higher the share. For the most NUTS2 regions in the Nordic, the percent is lower than 0,5%, indicating the commuting workers are the absolute minority in the total employed people. Åland (2,6%) and the South Sweden region (2,7%) stand out with more than 2% of employees in the region commuting cross-border for work. The destination country for Åland workers is Sweden, while for Swedish workers living in the south is Denmark. The commuting pattern is also apparent for the Swedish NUTS2 regions along the border line with Norway, with relatively higher percent of cross border workers commuting to Norway compared with other Nordic NUTS2 regions. At a finer scale (e.g., NUTS3) would show higher percentages in a number of regions, e.g., by taking only the NUTS 3 region – Skåne instead of the NUTS 2 region South Sweden (Skåne+Blekinge) or the border regions between NO and SE.

The map builds on statistics of cross-border commuters with residence in a NUTS2 Nordic region commute for work in 2015. For each NUTS2 region, the map shows the total number of commuters who commute to other Nordic countries for work. The number of commuters is categorised into three groups visualised in different shades: the darker, the higher the number of commuters. In addition, the most common country these commuters commute to from each region is identified by specific colours. For example, the darkest red indicates a region with at least 2,000 commuters working in another Nordic country, of which the largest group number of commuters works in Denmark. The most commuters were from the region of South Sweden (16 543) in 2015, and the majority of them commuted to Denmark for work. Norway is the most popular destination for work commuters in the Nordic Region, e.g., all Swedish regions except for the South Sweden region, all the regions in Denmark except for the Copenhagen region, and Iceland. Sweden is more attractive for work commuters living in Finland, Copenhagen region, and bordering regions in Norway.

The map shows the geographical delimitation of cross-border regions and committees financed by the Nordic Council of Ministers.

The travel times indicate the fastest morning connection outbound from Copenhagen Central Station or Malmö Central Station, departing after 6:30AMand arriving before 9:00AM. The station catchments are calculated by bicycle travel time for any time remaining beyond train travel. For instance, a 35-minute train ride and a 10-minute cycle ride results in a 45-minute total travel time. The shades of green indicate the travel time to other train stations and their surrounding areas in four main classes: up to 15 minutes, 16 to 30 minutes, 31 to 45 minutes and 46 to 60 minutes. The areas not highlighted in green on the map are further than one hour by train from either Copenhagen or Malmö main train stations. The map clearly shows that the vast majority of areas within the Capital Region of Denmark, a number of stations and areas which are part of the region of Zealand, for instance Slagelse and Næstved, as well as areas located along four main train corridors in Skåne (Malmö-Helsingborg, Malmö-Hässleholm, Malmö-Trelleborg and Malmö-Ystad) are within the one-hour travel time by train from/to Copenhagen and/or Malmö, thanks to the different train types (Öresund trains, regional trains and intercity trains). Areas of the GCR which are beyond the one-hour travel condition are the most northern part of the Capital Region of Denmark, the southern and western parts of Zealand (e.g. Kalundborg and Vordingborg) as well as most of the eastern half part of Skåne. In terms of population, the current situation provides this possibility to almost 3 million out of 4.3 million inhabitants, corresponding to 69% of the total population living in the Greater Copenhagen Region in 2020. The proportion of the total population increases to 75% when the region of Halland is excluded (as this was not initially part of the GCR when the…

This map shows the Greater Copenhagen Region, which constists of 85 municipalities and four regional authorities: the Capital Region of Denmark and Region Zealand on the Danish side, and the regions of Skåne and Halland on the Swedish side.

This map shows both the location of the four case studies of the Triborder activity 3 in the Greater Copenhagen Region and the local labour market areas in this cross-border region.

The map shows the proportion of households within each municipality that did not have access to a fixed-line broadband connection with a download speed above 30 Mbps in 2018. Put another way, the map shows the proportion of households which only had access to basic broadband. In Danish, Icelandic and Swedish municipalities, the proportion of households which only have basic broadband is rather small. In contrast, more than half of all households rely on basic broadband in many Norwegian and Finnish municipalities. The situation in Finland is particularly striking, with several municipalities in which over 75% of households have only basic Internet access. The average coverage by municipality type shows a clear digital divide between urban and rural municipalities. On average, fast broadband is available to all but 4% of households in urban municipalities. In contrast, approximately one third of households in rural municipalities do not have access to any faster broadband than 30 Mbps. The largest urban-rural digital divide is to be found in Norway and Finland. However, the pace of fibre development has never been higher. Particularly noteworthy is the strong growth in fibre-based broadband taking place outside of the densely populated areas.

The map shows the “at-risk-of-poverty” (AROP) rate in the Nordic Region. For the period from 2004 to 2018, the AROP rate increased in all Nordic countries except Iceland. This trend was strongest in Sweden. In Finland the AROP rate has been decreasing during the past few years, in line with what has previously been indicated – namely, on account of economic turmoil. This points to one of the weaknesses of using the AROP rate alongside several other measures of inequality. That is, while people have become poorer due to the economic crisis, the at-risk-of-poverty rate has paradoxically gone down. In addition, the AROP rate for Finland is higher in 2018 than it was in 2004. Looking at these trends on a regional level over a period of time (between 2011 and 2018), we can see that the AROP rate has decreased in almost all areas of Finland, whereas the pattern is rath er more varied in the other Nordic countries (we can also see a cohesive area in the south of Denmark where the AROP rate has decreased.) Again, Sweden has the most regions displaying increases in the AROP rate. Finland and Sweden contain the largest differences between the regions with the highest and lowest AROP rate. Hence the greatest regional differences are to be found in Sweden and Finland. Sweden also has the highest average AROP rate. About the At-risk-of-poverty The at-risk-of-poverty rate is a common measure of relative poverty and social inclusion. Most notably, it has been used for monitoring the EU2020 goal of inclusive growth. The at-risk-of-poverty rate is normally defined as “the share of people with an equivalised disposable income (after social transfer) below the at-risk-of-poverty threshold, which is set at 60% of the national median equivalised disposable income after social transfer.” (Eurostat). The indicator is…

This map shows a typology that divides the Nordic municipalities and regions into four migration categories: positive net migration for both males and females (green on the map), positive male net migration (blue on the map), positive female net migration (yellow on the map), and negative net migration for both males and females (red on the map). These migration flows on 30 to 39-year-olds are of particular interest since it is often assumed that the future of rural regions is dependent upon their capability both to retain their populations and to attract newcomers, returning residents and second home owners. In this context, the map provides a rather positive picture, because a considerable proportion of rural municipalities have experienced positive net migration among females, males, or both sexes across all the Nordic countries. Even so, there is negative net migration among both females and males in many municipalities in northern Sweden, north-eastern Norway and eastern Finland, in addition to several inland municipalities within these countries. Interestingly, there is negative net migration among both sexes across all the capital city municipalities of the Nordic Region. According to the regional map, the capital city regions of Denmark, Iceland and Norway all experienced negative net migration of young people aged 30-39 years between 2010 and 2019. The capital city region of Sweden experienced positive net migration of males and negative net migration of females while the capital city region of Finland experienced positive net migration overall. Despite the majority of peripheral regions experiencing negative net migration of 30 to 39-year-olds during the time period studied, there are also several interesting examples of rural regions which experienced positive female net migration, for example Nordjylland (Denmark), Pohjois-Savo (Finland), Austurland (Iceland), Møre og Romsdal (Norway), and Jämtland (Sweden).

This map shows a typology that divides the Nordic municipalities and regions into four migration categories: positive net migration for both males and females (green on the map), positive male net migration (blue on the map), positive female net migration (yellow on the map), and negative net migration for both males and females (red on the map). These migration flows of 20 to 29-year-olds are of interest since there is a particularly high level of internal migration among young adults across the Nordic countries compared to other EU countries. While the map shows that the great majority of municipalities experience negative net migration of young adults in favour of a few functional urban areas and some larger towns, it is possible to observe a number of exceptions to this general rule. The rural municipalities of Utsira, Moskenes, Valle, Smøla, Ballangen and Lierne in Norway have the highest positive net migration rates both for men and women. There are also positive net migration rates for males and females in the peripheral municipalities of Jomala, Kittilä, Lemland and Finström in Finland and Åland. There is positive male net migration but negative female net migration in Gratangen, Loppa, Gamvik, Drangedal and a few other Norwegian rural municipalities, plus Mariehamn in Åland, while several municipalities in remote areas of Finland have positive female net migration but negative male net migration. Some of these patterns may be related to specialised local labour markets, such as fisheries in Loppa, or recreational tourism in Kittilä. In general, the pattern of net migration among young adults is more diverse in Finland (where 72.0% of all municipalities have negative net migration), compared with 84.6% in Norway, 88.9% in Denmark and 89.0% in Sweden. However, it is important to remember that Danish, Finnish and Norwegian municipalities are smaller in size…

This map depicts the community impact (CI) of second home users in 2018[1] The indicator illustrates the impact of occasional second home visitors to the municipality. CI is defined as the ratio between annual inhabitants (AI) and regular population (CI= AI/Regular population). AI is a statistical variable that estimates the overall population of the municipalities, both the permanent inhabitants but also the seasonal second home visitors that also utilize the local infrastructure, welfare and planning resources.  AI is defined as three times the number of second homes plus the regular population. (AI= Regular population + 3 x number of second homes). Number three represents the estimate of average household size that visits the second home. Dark orange tones indicate high impact of seasonal inhabitants and light orange indicates lower impact of the seasonal variation. In populous municipalities with few recreational homes the two population measures (AI & regular population) will be almost identical, yielding a ratio approaching 1. The ratio between the regular population and the calculated annual population is large in municipalities with relatively few inhabitants and a high number of second homes. Nordic average for community impact by second home users was 1.2. Southern Savonia in Finland was the region with highest regional community impact. From other Nordic countries, the regions of Oppland in Norway, Suðurland in Iceland, and Jämtland Härjedalen in Sweden also stood out with higher ratios. On a municipal level the highest community impact can be found from Skorradalshreppur (30.0) in Iceland. Moreover, Grímsnes- og Grafningshreppur (19.0) (IS) and Kustavi (11.2) (FI) were the municipalities where the community impact also exceeded the ratio of 10. A large amount of second homes implies that there is a significant flow of people who are not permanently registered in these areas. This flow of people has both highly…

This map shows annual average internal net migration rate at the municipal and regional level in 2010-2018. The map shows the percentage change from internal migration for the period 2010 to 2018. Internal or domestic migration refers to migration between municipalities and regions within the same country. The blue areas on the map show municipalities/regions with positive internal net migration (i.e. more people arriving than departing), the red areas show municipalities/regions with negative internal net migration (i.e. more people departing than arriving) and the yellow areas show municipalities/regions with balanced internal net migration rates (i.e. comparable numbers of people arriving and departing). The trend revealed is that internal migration movements are directed towards larger city regions, with many rural periphery regions losing people. The loss of people in some of these regions is felt especially acutely because of the age selectivity of migration, with young people leaving in large numbers, accelerating the ageing of the population structure in regions with high out-migration. Read the digital publication here.

This map shows the change in household disposable income at the municipal level during the period 2011-2017. The blue colours indicate an increase in average household disposable income and the red colours indicate a decrease in average household disposable income. Household disposable income is defined as the sum of the income of a household (i.e. income from employment, net property income, social transfers and social benefits) minus direct taxes and social contributions, with dividends and net interest taken into consideration. The map reveals that a striking difference between the trends in Finland and Åland and those in the rest of the Nordic Region. The average household disposable income has fallen in almost half of the municipalities in Finland and Åland, but increased in all municipalities in Denmark, Greenland, Iceland, Norway and Sweden. Vimpeli, Rautjärvi and Pukkila, all in Finland, are the municipalities which experienced the largest drop in average household income between 2011 and 2017. This negative trend in municipalities in Finland was largely the consequence of a prolonged recession in the early 2010s, when the manufacturing sector was hit by a structural crisis. The situation was exacerbated by out-migration to urban areas and a rise in the unemployment rate in Finland, which peaked in 2015. Read the digital publication here.