Travel time by train from Copenhagen or Malmö
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…
Greater Copenhagen Region
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.
Local labour market areas in the Greater Copenhagen Region 2018
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.
Smart specialisation domains in Swedish regions
This map gives an overview of the S3 focus areas in the Swedish regions in 2019. The major S3 domains in Sweden shown in the map provide a good overview of the key specialisation areas in Sweden. It is possible, for example, to check which Swedish regions have “green”, “sustainable”, “environment” at their smart specialisation domains (marked in green in their respective infoboxes for the domains in the figure). The information illustrated in the map can assist Swedish regions when they are considering opportunities for S3 synergy and co-operation with each other. In Sweden, the Swedish Agency for Economic and Regional Growth (Tillväxtverket) is a central actor in assisting regions in their work with smart specialisation. Tillväxtverket promotes opportunities for cooperation between the Swedish regional S3 processes and provides relevant information and learning seminars related to S3. Read the digital publication here.
EU JRC S3 Platform 2019 in Nordic regions
This map shows the Nordic Regions that have registered on the EU JRC S3 platform, status as of October 2019. The regions that have registered on the S3 platform receive practical advice and broadened opportunities for international networking. In October 2019, there were 182 EU regions registered on the S3 platform, as well as 18 non-EU Member State regions. Of these regions, 38 are Nordic. It is worth noting that, as a non-EU member state, Norway has seven registered regions on the platform. Registration on the S3 platform is by no means a guarantee of success of a regional smart specialisation process, but it indicates the willingness of the region to learn more about S3 and to participate in international and interregional S3 cooperation through the possibilities provided by the S3 platform. The smart specialisation concept has been diffusing rapidly across Europe in the 2010s, as an increasing number of regions adopt it and design strategies departing from their own preconditions. The S3 platform in Seville, Spain, hosted by the Institute for Prospective Technological Studies (IPTS), was established in 2011 to assist EU countries and regions to develop, implement and review their smart specialisation strategies. The S3 platform provides information, methodologies, expertise and advice to national and regional policymakers, promotes mutual learning and transnational co-operation, and contributes to academic debates around the concept of smart specialisation. Read the digital publication here.
Regional innovation scoreboard 2019
This map shows the regional innovation scoreboard (RIS) in the European regions in 2019. The small map shows the innovation scoreboard at national level. The index shows the performance of innovation systems, classified into four main performance groups (leader, strong, moderate and modest). The European innovation scoreboard provides a comparative assessment of the research and innovation performance in European countries. It assesses the relative strengths and weaknesses of national innovation systems and helps countries identify areas they need to address. The Regional innovation scoreboard (RIS), a regional extension of the European innovation scoreboard, assesses the innovation performance of European regions on a limited number of indicators. The RIS 2019 covers 238 regions across 23 EU countries, as well as Norway, Serbia and Switzerland. Cyprus, Estonia, Latvia, Luxembourg and Malta are also included at country level. The RIS 2019 is a comparative assessment of regional innovation based on the European innovation scoreboard methodology, using 18 of the latter’s 27 indicators. It provides a more detailed breakdown of the performance groups with contextual data that can be used to analyse and compare structural economic, business and socio-demographic differences between regions. The Nordic regions are doing well in an overall RIS comparison regarding innovation performance. There are, however, considerable differences in innovation performance between the Nordic regions. For example, the capital regions have higher levels of innovation performance than more rural and peripheral regions, according to RIS 2019. This is often due to the critical mass of companies and the spatial significance of the proximity of firms and entrepreneurs, enabling knowledge-sharing and spill-over effects. Read the digital publication here.
Higher educational institutions in the Arctic
The map shows universities and other educational institutions on post-secondary and tertiary level located in the Arctic. The red circles indicate a location of a university, college, or campus areas within the Arctic. The size of the circle corresponds to the number of educational institutions in a specific location. There is a high density of educational education institutions around Anchorage (Alaska), in Iceland, the Faroe Islands and the Arctic Fennoscandia (see zoom-in maps). In the Yukon (Canada), the Yukon College is the main educational institution, which has several campus areas across the region. In the Russian Arctic the largest centres with higher educational institutions are in Murmansk, Naryan-Mar (Nenets), Nizhnevartovsk (Khanty-Mansi), Salekhard (Yamalo-Nenets), and Yakutsk (Sakha).
Household access to high capacity fixed broadband 2016
This map shows the household access to high capacity fixed broadband for all Nordic municipalities in 2016. The blue shading indicates the percentage of household with access to high capacity fixed broadband speed of at least 30 mbit/s in 2016. The darker the blue the larger the percentage of household with access to high capacity fixed broadband speed in the municipality, while the brightest colours represent municipalities with a low share. The grey colour indicate municipality with no data. High capacity fixed broadband coverage enhances access to digital solutions in both rural and urban contexts across the Nordic Region, thus making these areas good places to live, work and run a business domestically and across national borders. At a municipal level the household coverage by high capacity fixed broadband shows a more varied picture than that at the regional level. The average figure for Nordic municipalities was 63% in 2016, with more homogeneous figures in Denmark and Sweden than in Norway and Finland. The variation between neighbouring municipalities reflects the decision at the municipal level to prioritise investments in broadband infrastructure development as well as the nurturing of a favourable climate for the establishment of data centres requiring fast broadband networks, among other things. Fifteen Nordic municipalities, located in Sweden and Norway, had already reached the 100% mark for household coverage by high capacity fixed broadband in 2016. In Sweden, these municipalities are located in both the capital city region and in Skåne. In Norway, they are found in the more remote and rural parts of Møre og Romsdal (e.g. Giske), Troms (i.e. Lavangen) and Finnmark regions (Båtsfjord). Municipalities having values above 90% are mostly located in capital city regions as well as in more rural contexts in Jylland (Denmark), southern Sweden and northern Finland and Norway. One explanation for…
Next Generation Access coverage 2016
This map shows the Next Generation Access (NGA) network coverage in European regions in 2016. The blue shading indicates the percentage of household covered by NGA broadband in European NUTS 3 regions. The darker the blue the larger the percentage of household covered by NGA broadband in the region, while the brightest colours represent regions with a low share. Regions with relatively small territories and important population densities stand out in terms of high NGA network coverage, e.g. urban regions in the Netherlands and Switzerland. Capital city regions also have high NGA network coverage scores, while the more rural regions continue to lag, e.g. in parts of France and Poland. The Nordic countries are characterised by having almost no differences within their territories, i.e. no large variation in terms of NGA network coverage, unlike the clear regional differences in countries such as France or Italy. All regions in the Nordic countries score in the range of 65% to 95% of households having NGA network coverage, except for Etelä-Pohjanmaa in Finland which has a coverage range of 35% to 65% and the Danish statistical region of Østjylland and the capital regions of Denmark and Iceland with scores between 95% and 100% respectively. The relatively high figures for the Nordic Region can in part be explained by the existence of national and regional digitalisation strategies over the last decade or so. In Denmark, as well as in the other Nordic countries, digitalisation has long been on the national agenda. One of the main goals of these strategies has been to increase the growth and productivity of the business community – and to make it easier and cheaper to establish digital infrastructure. The regional level has an important role to play in the development of digital infrastructure, hence the relevance of the elaboration…
Change of total R&D expenditure 2007-2015
This map shows the change in the expenditure in research and development (R&D) between 2007 and 2015 in the Nordic Region. The blue tones indicate regions with a positive change in the R&D expenditure between 2007 and 2015. The red tones indicate regions with a negative change in the R&D expenditure between 2007 and 2015. The darker the colour, the stronger the change. The grey colour indicates no data. The bars indicate the value of expenditure in R&D in million euros, the light brown for 2007 and the dark brown for 2015. The values of 2007 expenditures were adjusted to 2015 price level. High levels of Research and Development (R&D) expenditure are viewed as a vital enabling factor for innovation which is one of the key policy components of the Europe 2020 Strategy. At the regional level in Finland, most regions have shown a downward trend in R&D expenditures both in percentage and in real terms. This reflects the challenging fiscal policy and economic conditions experienced in Finland after the global financial crisis in 2008 and the difficulties faced by the ICT sector, where R&D is highly concentrated, as well as the inability of other industries to compensate for the decline of the ICT sector. Åland on the other hand has shown a positive trend in R&D expenditures, although having very low values in absolute numbers for both years. Sweden has experienced a dramatic decrease (< -6.1%) in R&D expenditures in Värmland, Blekinge and Gotland which was in large part, if not entirely, caused by the relocation of important R&D facilities/resources. Similarly, some major closures and redundancy notifications led to substantial cuts in R&D spending in Skåne in 2015, despite the increasing number of start-ups. For Iceland, available data for the 2013–2016 period indicates a steady and stable increase in…
European eco-innovation parks in 2014
This map shows the location of the European eco-innovation parks in the states of the European Union (EU) and Iceland in 2014. The eco-innovation parks are eco-industrial parks and eco-innovative areas combining residential and industrial activities. The establishment of eco-industrial parks is one way to promote eco-innovation, resource efficiency and the circular economy. They create new and innovative business opportunities and improve ecosystems. The blue colour indicates the EU-member states having at least one identified eco-innovation park in 2014. The circles indicate the location and the type of the eco-innovation parks (green, in use; yellow, under construction; brown, planned; red, stopped). The grey colour indicates no data. A clear spatial concentration of eco-innovation parks can be observed in the Ruhr area and around Leipzig (Germany), in southern Belgium, south-western and northern Netherlands, western Switzerland, along the “arch” stretching from Turin via Pisa to Udine in North-East Italy, around Barcelona as well as around some national borders in the industrialised parts of north-West Europe namely Germany-Netherlands-Belgium-France and Switzerland. Eco-innovation parks differ in many respects, for instance regarding energy and material flows (e.g. waste heat, steam, power; wood chips, bark, ash, pulping chemicals), number and size of companies involved and jobs created, public sector involvement and finally, in terms of (the drivers behind) their evolution. The latter means that some parks evolved and expanded around a few economic activities and companies (e.g. saw mills) to include further activities (e.g. pulp mills, power plants etc.), while others were intentionally planned and put into operation.
Major immigration flows to Finland 2010-2016
Average annual flows above 1000 people by country of origin Migration flows by country of origin are of growing interest in the Nordic Region due to the recent unprecedented inflows of migrants. There are also interesting differences between the Nordic countries with respect to the dominant countries of origin of migrants and the size of inflows. Finland had only four inflows exceeding annual averages of 1000 people during the measured period. The inflow from Estonia was by far the largest, an annual average of around 5000 people, flowed by inflows from Sweden and Russia (just under 3000), and the United Kingdom (around 1000).
Major immigration flows to Denmark 2010-2016
Average annual flows above 1000 people by country of origin Migration flows by country of origin are of growing interest in the Nordic Region due to the recent unprecedented inflows of migrants. There are also interesting differences between the Nordic countries with respect to the dominant countries of origin of migrants and the size of inflows. During the measured period, there were more than 23 average annual inflows to Denmark that exceeded 1000 people. However, none of these inflows were as large as the dominant inflows to Norway and Sweden during the same period. The largest inflows to Denmark were around 5000 people each from U.S., Sweden, Germany and Poland. Due to historic and political connections, Denmark, unlike Norway, Finland and Sweden, had substantial annual inflows from the Faroe Islands, Greenland and Iceland (around 1000 or 2000 each). These numbers are particularly notable in the context of the small populations of
Major immigration flows to the Nordic Region 2010-2016
Average annual flows above 3000 people by country of origin Migration flows by country of origin are of growing interest in the Nordic Region due to the recent unprecedented inflows of migrants. There are also interesting differences between the Nordic countries with respect to the dominant countries of origin of migrants and the size of inflows. The map shows some clear spatial patterns regarding the dominant countries of origin of migrants and the size of inflows to each of the Nordic countries. Finland had only one average annual inflow of over 3000 people during the measured period, namely from Estonia. Compared to the other Nordic countries, Sweden had by far the largest immigrant flows, with average annual arrivals of nearly 19 000 immigrants from Syria, around 5000 from both Somalia and Poland, about 4000 from Iraq and Eritrea, and circa 3000 from Afghanistan, India, China and Iran. For Norway, inflows above 3000 people were all from nearby countries: Sweden, Lithuania, Denmark, and Poland. Inflows from Poland were particularly high – an annual average of almost 11 000 people. Although Denmark experienced a similar number of inflows above 3000 people, these inflows were smaller and more evenly distributed than in Norway and Sweden. The largest inflows were around 5000 people and included migrants from the U.S., Sweden, Germany and Poland.
Major immigration flows to the Faroe Islands, Greenland and Iceland 2010-2016
Average annual flows above 1000 people by country of origin Migration flows by country of origin are of growing interest in the Nordic Region due to the recent unprecedented inflows of migrants. There are also interesting differences between the Nordic countries with respect to the dominant countries of origin of migrants and the size of inflows. The Faroe Islands and Greenland each had one average annual inflow greater than 1000 people during the measured period, in both cases from Denmark (around 2000 to Greenland and around 1000 to the Faroe Islands). Iceland had average annual inflows just above 1000 people from two countries, Denmark and Poland.
Major immigration flows to Sweden 2010-2016
Average annual flows above 1000 people by country of origin Migration flows by country of origin are of growing interest in the Nordic Region due to the recent unprecedented inflows of migrants. There are also interesting differences between the Nordic countries with respect to the dominant countries of origin of migrants and the size of inflows. During the measured period, Sweden had by far had the largest immigrant flows compared to of all the other Nordic countries – Denmark, Finland, Iceland and Norway. An annual average of nearly 19 000 immigrants came from Syria, around 5000 from both Somalia and Poland, about 4000 from Iraq and Eritrea, and circa 3000 each from Afghanistan, India, China and Iran. Many of the largest immigration flows to Sweden originated from countries in East Africa, the Middle-East, and mainland Asia. Alongside the large inflows from Poland, Sweden also experienced large inflows from its other European neighbours: Finland, Germany, Denmark and Norway (over 2000 people at the annual average).
Major immigration flows to Norway 2010-2016
Average annual flows above 1000 people by country of origin Migration flows by country of origin are of growing interest in the Nordic Region due to the recent unprecedented inflows of migrants. There are also interesting differences between the Nordic countries with respect to the dominant countries of origin of migrants and the size of inflows. During the measured period, the largest average annual inflows to Norway were from nearby countries: Sweden, Lithuania, Denmark, and, most notably, Poland (annual average of almost 11 000 people). This specific pattern for Norway can largely be explained by the rich job opportunities that have existed in in the country over the past decade.