Maps

This map shows the country of birth of the largest minority group in the Nordic countries. This map shows the country of birth of the largest minority group in each municipality in each Nordic municipality in 2022. The different colours represent the largest minority group, defined as a specific country or a group of countries. Using country of birth as an identity marker reveals an interesting geographic pattern of minority populations at the municipal level. Even with the increase in migration, native-born populations remain the largest group in each municipality (i.e. Swedish-born people are the largest group in every municipality in Sweden). They also constitute the majority in each municipality, with the exception of one small municipality with a majority-minority population. For visual simplicity, countries of birth are grouped. The four large Nordic countries are shown separately. The EU15 countries and EU accession countries constitute separate groups. The countries of the former Soviet Union (minus the Baltic states) are another group. Afghanistan, Eritrea, Iran, Iraq, Somalia and Syria together constitute a group of countries from which many of the migrants to the Nordic countries came as refugees over the past decade. People born in Finland are the largest minority group in many regions near the Finnish border in northern Sweden, as well as a group of municipalities around Stockholm. In several border municipalities in Sweden, people born in Norway are the largest minority group. Swedish-born persons are the largest minority group in most municipalities in northern and western Finland (by percentage). People born in one of the EU15 countries form the largest minority group in southern Denmark, near the border with Germany, as well as a few other scattered municipalities in southern Sweden and Norway. Following several EU expansions starting in 2004, many people from the EU accession countries have…

This map shows the share of foreign-born of the total population in the Nordic countries. This map shows the share of foreign-born of the total population in Nordic municipalities (big map) and regions (small map), and municipalities (big map) in 2022. Iceland has the highest share of foreign-born residents in the Nordic Region, at 22%. Mýrdalshreppur, the municipality in the south containing the village of Vik, has the largest foreign-born population, at 58%. It is also the only municipality in the Nordic Region with a majority non-native population. Other municipalities in the south, some of which are quite small, also have significant foreign-born populations. Reykjanesbær, near Keflavik airport, is the largest municipality with a sizeable foreign-born population, at 29%. In Reykjavíkurborg, 20% of the population is foreign-born, about the same as the national average. Many municipalities with tiny populations in the Westfjords and the north also have small shares of foreign-born persons. In 2022, 17% of the population of Norway was foreign-born. Municipalities with high shares of foreign-born include Oslo (28%), several suburban municipalities near Oslo, and a few in the north – which have small overall populations but large numbers of foreign workers employed in the fishing industry. In Sweden, 20% of residents are foreign-born, with large differences in distribution by region and municipality. At the regional level, Stockholm has the highest share of foreign-born persons (27%), followed by Skåne, including the city of Malmö (24%). The percentage of foreign-born persons in Västra Götaland, which encompasses Gothenburg, is the same as that of Sweden as a whole. The regions with low shares of foreign-born persons are in the north of the country – Dalarna, Gävleborg, Västernorrland, Jämtland, Västerbotten, and Norrbotten – plus the island of Gotland, which has the lowest share (9%). There are no municipalities in which foreign-born…

This map shows the percentage-point change in foreign-born populations in the Nordic countries. This map shows the percentage-point change in foreign-born populations by region (small map) and municipality (big map) between 2000 and 2022. The blue shades indicate an increase in the number of foreign-born while the red shades indicate a decrease. The recent growth in foreign-born populations differs among the Nordic countries, regions, and municipalities. During the period 2000-2022, much of both the absolute and percentage-point increases in the foreign-born populations took place in suburbs around the capital cities and other large urban centres. However, with few exceptions, every municipality across the Nordic Region saw increases in foreign-born populations. In Iceland, the foreign-born population increased from 5% to 20%. The largest percentage-point increases in the foreign-born populations were in municipalities in the southwest, which had small populations and small foreign-born shares. Of the larger municipalities, Reykjanesbaer and the Capital Region had the largest absolute and percentage point increases. The foreign-born population in Norway grew from 7% to 17%. The municipalities with significant increases in foreign-born populations include several suburban areas near Oslo, as well as scattered municipalities elsewhere that had small foreign-born shares in 2000. The percentage of foreign-born residents in Oslo increased from 16% to 28% between 2000 and 2022. No municipalities experienced a decline in foreign-born population during this period.

This map shows the internal net migration in 2021 as a percentage of the total population. This map shows the internal net migration in 2021 as a percentage of the total population. The small map shows the result on a regional level, and the big map on the municipal level. Internal (sometimes referred to as domestic) net migration refers to migration between municipalities and regions within the same country. International migration is excluded. In 2021, internal net migration was positive (indicated by shades of blue) or at least balanced (shown in yellow) in many of the municipalities in central and northern Sweden and in central and eastern Finland – areas that traditionally were more likely to lose population due to internal migration. Conversely, several municipalities in the capital regions – such as Stockholm, Oslo, and Copenhagen – exhibited negative internal net migration. Iceland, Greenland, and Åland exhibited mixed internal migration flows, with some municipalities experiencing positive net migration while others faced negative net migration. The Faroe Islands stand as an exception, maintaining only positive internal migration at the municipal level for this year.

These maps depicts Small and medium sized enterprises (SMEs) with product innovation (left map) and process innovation (right map) in 2023. The data is displayed at the NUTS2 level and the data comes from the Regional Innovation Scoreboard 2023. The left map depicts SMEs introducing product innovations as a percentage of SMEs in the Nordic regions, calculated as the share of SMEs who introduced at least one product innovation. The values for the map are normalised from 0–10. In this context, a product innovation is defined as the market introduction of a good or service that is new or significantly improved with respect to its capabilities, user-friendliness, components, or sub-systems. Rural regions tend to have lower levels of SMEs with product innovations, while urban regions have the highest levels. In 2023, Åland (0.235) had the lowest number of SMEs with product innovations in the Nordic Region, while Oslo had the highest (1.0). Etelä-Suomi and Stockholm regions were slightly behind, with 0.954 and 0.948, respectively. In Denmark, the leading regions were the Capital Region (Hovedstaden) and Northern Jutland (Nordjylland), with 0.719 and 0.715, respectively. Southern Denmark (Syddanmark) had the lowest level in Denmark, at 0.545. In Norway, the lowest value was in Northern Norway (Nord-Norge), 0.67, while in Sweden it was Middle Norrland (Mellersta Norrland), with 0.53. Taken as an average across the Nordic countries, Norway has a significantly higher number of SMEs with product innovations than the other countries. The right map shows the share of SMEs introducing at least one business-process innovation, which includes process, marketing, and organisational innovations. In general, Nordic SMEs are more likely to innovate in products rather than processes. The highest shares of process-innovating SMEs are found in most of the Finnish regions ranging from 0,79 in Länsi-Suomi to 0,91 in Etelä-Suomi, except of Åland…

These maps shows the expenditure on Research and Development (R&D) in the public and business sectors as a percentage of regional GDP, along with non-R&D innovation expenditure in Small and Medium Enterprises (SMEs) as a percentage of turnover. Together, these metrics offer a comprehensive understanding of the innovation landscape and provide insights into governments’ and higher education institutions’ commitment to foundational research, as well as the competitiveness and dynamism of the business environment and SMEs’ innovation capacity. By considering investment in both R&D and non-R&D activities, these indicators illustrate a broad spectrum of innovation drivers, from basic research to market-driven initiatives, and underscore the diverse pathways through which innovation fosters economic growth and social progress First, the top left map showcases R&D expenditure in the public sector as a percentage of GDP in the Nordic countries in 2023. In that year, the European level of R&D expenditure in the public sector, as a percentage of GDP, was 0.78%. By comparison, the Nordic average was 0.9%. While the more urban regions, in general, lead the Nordic regions, this is not always the case, as shown by the variation between the frontrunners. The leading region is Trøndelag (including Norway’s third-largest city, Trondheim), with 2.30% of regional GDP. It is in third place in the EU as a whole. The next regions are Övre Norrland with 1.77%, Northern Jutland with 1.54%, Östra Mellansverige with 1.52%, and Hovedstaden with 1.49%. A common feature of most of the top-ranking regions is that they host universities and other higher education institutions known for innovation practices. Most Nordic regions have not seen significant increases or decreases in public R&D spending between 2016 and 2023. The top right map focuses on the private sector’s investment in research and development activities and depicts R&D expenditure in the business sector…

This map shows the municipal and regional borders of the Nordic Region as of 1 January 2023*, the names refer to the regions.  The Nordic Region is vast and has a diverse physical geography, stretching from the northern edge of the European mainland to north of the Arctic Circle. It consists of Denmark, Finland, Iceland, Norway and Sweden, as well as the three self-governing regions, the Faroe Islands and Greenland (both part of the Kingdom of Denmark) and Åland (part of the Republic of Finland). This map shows the municipal and regional borders of the Nordic Region as of 1 January 2023*, the names refer to the regions.  The Nordic Region is vast and has a diverse physical geography, stretching from the northern edge of the European mainland to north of the Arctic Circle. It consists of Denmark, Finland, Iceland, Norway and Sweden, as well as the three self-governing regions, the Faroe Islands and Greenland (both part of the Kingdom of Denmark) and Åland (part of the Republic of Finland). The table below summarises the administrative structure in each of the Nordic countries. These structures form the basis for the Nomenclature of Territorial Units for Statistics (NUTS) classification, a hierarchical system dividing European states into statistical units for research purposes. In general, the NUTS and Local Administrative Units (LAU) classifications follow existing divisions, but this may differ from country to country. Light grey frames represent the regional level presented In Nordregio’s map. As of 1 Jan 2023, there were 66 regions at this level. Dark grey frames show the local units represented in most of the municipal maps. As of 1 Jan 2023 there were 1,133 units at this level. *There are usually some changes in the administrative borders every year. Since 2023 there have for example been changes in…

This map illustrates the projected change in the working-age population across Nordic municipalities (large map) and regions (small map) from 2023 to 2040. The working-age population is defined here as individuals aged 20 to 64. The blue areas on the maps represent municipalities and regions where the working-age population is expected to increase during this period. In contrast, the red areas indicate a projected decline in the working-age population. These projections are based on data from Nordic statistical institutes, though it’s important to note that the underlying assumptions may vary between Nordic countries. In most of the Western world, the working-age population is decreasing. In the EU, this age group is expected to decrease by 6.5% between 2023 and 2040. Only five EU countries – Malta, Luxembourg, Ireland, Sweden and Belgium – are expected to enjoy growth in the working-age population during this period. However, in the Nordic Region as a whole, the working-age population is expected to grow slightly, with an average increase of 1.9%. As the map shows, the distribution is quite varied, with considerable differences both between and within the countries. The biggest increase is expected in Iceland (28%), followed by Sweden (5.8%), Åland (3.9%) and Norway (0.6%). Decreases are expected in Finland (-0.5%), the Faroe Islands (-2.6%), Denmark (-3.2%) and Greenland (-11.4%). This development is in addition to the decreases already experienced by Finland since 2013.  In general, the trend of growing populations in cities and decreasing populations in rural areas is expected to continue. The regions that are expected to have the highest working-age population growth include Höfuðborgarsvæðið in Iceland, Uppsala (+13%), Stockholm (+12%), Skåne (+9%), Halland (+7%) and Västra Götaland (+6%) in Sweden, Uusimaa (+8%) and Pirkanmaa (+5%) in Finland, and Oslo and Viken in Norway (+5%). In addition, Copenhagen municipality (+5%), Rødovre (+9%)…

Members of NATO (North Atlantic Treaty Organization) and non-NATO members as of March 2024. Countries that joined after 2015: Montenegro (2017), North Macedonia (2020), Finland (2023) and Sweden (2024). 

Members of NATO (North Atlantic Treaty Organization) and non-NATO members as of April 2023. Countries that joined after 2015: Montenegro (2017), North Macedonia (2020), and Finland (2023). 

The map shows all routes in our sample with significant travel time benefit for electric aviation. They are 203 in total. A route has a significant travel time benefit if the travel time for both car and public transportation exceeded 1,5 times the travel time for electric aviation. I.e., if one of the existing transport modes is faster or up to 1,5 times the travel time for electric aviation, electric aviation does not have the potential to improve accessibility between the two destinations, according to our analysis.

The map shows all routes between urban and rural areas where electric aviation has significant time benefits compared to other traffic modes. Yellow lines are already served by aviation, while blue color indicates non-existent routes where electric flight would reduce the travel time between destinations. Our motivation for focusing on urban-rural routes was based on the assumption that electric aviation can increase the access for rural areas to public facilities and job opportunities, as well as the possibility of connecting remote areas with national and international transport systems. The result, though, can only be understood in terms of travel time benefits between the areas, and thus reveals little about accessibility to mentioned opportunities. The following are examples of themes to be investigated further within the main project. Identify regional hubs Among others, the project FAIR (2022) has addressed the need to update the flight system to a more flexible aviation network, that meet travelers’ needs with smart mobility. This can be done by identifying demands and establishing regional hubs for electric aviation, which can serve remote and regional areas. The potential of Hamar and Bodö in Norway as regional hubs should be studied more closely.

The map shows all routes between urban areas separated by water, and where electric aviation has significant time benefits compared to the fastest traffic mode. Yellow lines are already served by aviation, while red color indicates non-existent routes where electric flight would reduce the travel time between destinations. The result is in line with our assumptions, that there is a lack of fast connections between potential labor markets in urban areas, which are geographically close but separated by open water.

The map visualizes all routes with significant travel time benefit, which are already served with commercial flights. Information on existing routes has been obtained from the report Nordic Sustainable Aviation (Ydersbond et al, 2020) and applies to the year 2019. Since then, routes may have been added or removed, which is important to bear in mind in future investigations. However, choosing a later year risk giving equally misleading results, as flights decreased drastically during the pandemic. Statistics for 2019 provide a picture of the demand that existed before the pandemic, which is the latest stable levels that can be obtained. Whether air traffic will ever return to the same levels as before the pandemic is too early to say.   The majority of routes are found in Norway, along the coastline, which confirms earlier knowledge that Norway has a more extensive and coherent aviation network than the rest of the Nordic region.

This map shows the travel time calculations for electric aviation versus travelling by public transportation. Routes represented by any nuance of green, are routes with significant travel time benefits for electric aviation in comparison with public transportation. The darker the nuance of green, the larger time benefit for electric aviation. The beige color represents routes where the travel time for public transportation is the same or up to 1,5 times the travel time for electric aviation. The red color represents routes where public transportation is faster than electric aviation. Purple lines represent routes where no public transportation is available.  These were also routes where we could see significant time benefits for electric aviation. The number of changes when commuting with public transport may have a negative impact on perceived accessibility. In this accessibility analysis, however, we stay with the same criteria for public transport as for travel by car. For future research, the number of changes when commuting by public transport could be considered in the comparison.

This map shows the travel time calculations for electric aviation versus traveling by car. Routes represented by any nuance of green, are routes with significant travel time benefits for electric aviation in comparison with car. The darker the nuance of green, the larger time benefit for electric aviation. The beige color represents routes where the travel time for car is the same or up to 1,5 times the travel time for electric aviation. The red color represents routes where car is faster than electric aviation.

The map shows all routes with a maximum distance of 200 km divided into three categories, based on the airports’ degree of urbanization: Routes between two rural airports, routes between one rural and one urban airport and routes between two urban airports. The classification is based on the new urban-rural typology. We restricted the analysis to routes between rural and urban areas as well as routes between urban areas that are separated by water. Those are 426 in total. We based our criteria on the assumption that accessibility gains to public services and job clusters can be made for rural areas, if better connected to areas with a high degree of urbanization. Because of possible potential to link labor markets between urban areas on opposite sides of water urban to urban areas that cross water are also included. This is based on previous research which has shown the potential for electric aviation to connect important labor markets which are separated by water, particularly in the Kvarken area (Fair, 2022). Our choice of selection criteria means that we intentionally ignore routes where electric aviation may have a potential to reduce travel times significantly. There might also be other important reasons for the implementation of electric aviation between the excluded routes. Between rural areas, for example, tourism or establishing a comprehensive transport system in the Nordic region, constitute reasons for implementing electric aviation. Regarding routes between urban areas over mainland, the inclusion of more routes with the same rationale as above – that significant time travel benefits could be gained between labor markets with electric aviation (for example between two urban areas in mountainous regions where travel times can be long) – can be motivated. Some of those routes can be important to investigate at a later stage but are outside the…

This map classifies all airports by a degree of urbanisation. The classification is based on the new urban-rural typology. We classified all airports localized within any of the top five urbanization classes (Inner urban area, Local center in rural area, Outer urban area, peri-urban area, or Rural area close to close to urban) as Urban. All other airports, localized within the bottom two classes (Rural heartland or Sparsely populated rural area) were classified as Rural. No adjustments were made based on the proximity of the airports to urban areas. During the process we considered adjustments in the categorization based on the airports’ potential catchment area from a close urban area. For example, one can assume that Gällivare Lappland airport in the north of Sweden, has its main catchment area from Gällivare which is classified as a local center in rural area (i.e. Urban). The airport, though, is localized within the category Rural heartland. Yet, we decided to let the typology determine to which category each airport belong.

This map shows all possible electric aviation routes of a maximum distance of 200 kilometres within the Nordic region. First generation electric aviation will have a limited range due to battery capacity. According to the report Nordic Sustainable Aviation, routes up to 400 kilometers constitute an initial market for electric airplanes in the Nordic region. However, also shorter distance routes under 200 km, where cruise speed is less important and in sparsely populated regions where passenger volumes are very small, will be the focus (Ydersbond et al, 2020). The first generation of aircrafts that rely solely on electric power have a defined maximum range of 200 km (Heart Areospace, 2022). For this accessibility study, we only included routes of a maximum distance of 200 kilometers. This selection gave us 1001 possible routes in total.

This map shows all airports within the geographical scope which may be operated with commercial flight. To limit our selection of airports, we used a combination of two official airport code systems: IATA (International Air Transport Association) and ICAO (International Civil Aviation Organization). IATA-codes specify the airport as a part of a commercial flight route. However, the IATA system, is not solely limited to airports. Other locations, such as bus or ferry stations can also apply for an IATA location code, as long it is included in an airline travel chain. The ICAO-code, on the other hand, indicates that the location is an airport, but not necessarily for commercial flights In order to obtain a selection of airports that met our criteria, an airport was included only if it had both an IATA-code and an ICAO-code.  Three different sources are used: 1) Swedavia (lists all airports in the Nordics that Swedavia traffics today). This is our main source, but it does not include all existing airports in the Nordic countries. Therefore, we also use two other sources: 2) Avcodes: Airport code database, from which other airports, that are not served by Swedavia, are obtained. 3) Wikipedia. Finally, the listed airports are checked against Wikipedia, to verify if any airports have been missed through the other sources. This selection gave us 186 airports in total.