Actual value and historical data chart for Norway Population Density People Per Sq Km

Norway: Population density, people per square km: The latest value from 2021 is 15 people per square km, unchanged from 15 people per square km in 2020. In comparison, the world average is 456 people per square km, based on data from 196 countries. Historically, the average for Norway from 1961 to 2021 is 12 people per square km. The minimum value, 10 people per square km, was reached in 1961 while the maximum of 15 people per square km was recorded in 2018.

Historical dataset showing Norway population density by year from 1961 to 2022.

Norway NO: Population Density: People per Square Km data was reported at 14.462 Person/sq km in 2017. This records an increase from the previous number of 14.332 Person/sq km for 2016. Norway NO: Population Density: People per Square Km data is updated yearly, averaging 11.573 Person/sq km from Dec 1961 (Median) to 2017, with 57 observations. The data reached an all-time high of 14.462 Person/sq km in 2017 and a record low of 9.883 Person/sq km in 1961. Norway NO: Population Density: People per Square Km data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Norway – Table NO.World Bank.WDI: Population and Urbanization Statistics. Population density is midyear population divided by land area in square kilometers. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship--except for refugees not permanently settled in the country of asylum, who are generally considered part of the population of their country of origin. Land area is a country's total area, excluding area under inland water bodies, national claims to continental shelf, and exclusive economic zones. In most cases the definition of inland water bodies includes major rivers and lakes.; ; Food and Agriculture Organization and World Bank population estimates.; Weighted average;

Population density of Norway went up by 0.90% from 14.8 people per sq. km in 2021 to 15.0 people per sq. km in 2022. Since the 1.32% improve in 2012, population density jumped by 9.03% in 2022. Population density is midyear population divided by land area in square kilometers.

View yearly updates and historical trends for Norway Population Density. Source: World Bank. Track economic data with YCharts analytics.

In 2023, the region Viken was the most populated in Norway. The region, which contains large areas surrounding the capital Oslo, had a population of nearly 1.3 million people in 2023. Oslo had the second highest number of inhabitants with around 709,000, followed by Vestland. Meanwhile, the northern region of Nordland has the lowest number of inhabitants, counting 241,000 people. At the beginning of 2023, a total of 5.5 million people lived in Norway.

Comprehensive socio-economic dataset for Norway including population demographics, economic indicators, geographic data, and social statistics. This dataset covers key metrics such as GDP, population density, area, capital city, and regional classifications.

Density of physicians of Norway rose by 1.61% from 5.1 number per thousand population in 2020 to 5.2 number per thousand population in 2021. Since the 1.80% upward trend in 2011, density of physicians soared by 23.40% in 2021.

Associations* of sex, region, and population density with IOTF† overweight, obesity, and thinness from 8 to 13 years (n = 1852, 3317 observations).

With 450,295 square kilometers, Sweden is the largest Nordic country by area size, followed by Finland and Norway. This makes it the fifth largest country in Europe. Meanwhile, Denmark is the smallest of the five Nordic countries with only 43,094 square kilometers, however, the Danish autonomous region of Greenland is significantly larger than any of the Nordic countries, and is almost double the size of the other five combined.

Population

Sweden is also the Nordic country with the largest population. 10.45 million people live in the country. Denmark, Finland, and Norway all have between five and six million inhabitants, whereas only 370,000 people live in Iceland. Meanwhile, Denmark has the highest population density of the five countries. Greenland is the most sparsely populated permanently-inhabited country in the world, followed by the regions of Svalbard and Jan Mayen.

Geography

The five Nordic countries vary geographically. While Denmark is mostly flat, its highest point only stretching around 170 meters above sea level, Norway's highest peak is nearly 2,500 meters high. Moreover, Finland is known for its many lakes and is often called the land of a thousand lakes, whereas Iceland is famous for its volcanoes.

Associations* of sex, region, and population density with mean BMI IOTF z-score† from 8 to 13 years (n = 1852, 3317 observations).

The objective of this study was to estimate and compare the occurrence of AMR in wild red foxes in relation to human population densities. Samples from wild red foxes (n = 528) included in the Norwegian monitoring programme on antimicrobial resistance in bacteria from food, feed and animals were included. All samples were divided into three different groups based on population density in the municipality where the foxes were hunted. Of the 528 samples included, 108 (20.5%), 328 (62.1%) and 92 (17.4%) originated from areas with low, medium and high population density, respectively. A single faecal swab was collected from each fox. All samples were plated out on a selective medium for Enterobacteriaceae for culturing followed by inclusion and susceptibility testing of one randomly selected Escherichia coli to assess the overall occurrence of AMR in the Gram-negative bacterial population. Furthermore, the samples were subjected to selective screening for detection of E. coli displaying resistance towards extended-spectrum cephalosporins and fluoroquinolones. In addition, a subset of samples (n = 387) were subjected to selective culturing to detect E. coli resistant to carbapenems and colistin, and enterococci resistant to vancomycin. Of these, 98 (25.3%), 200 (51.7%) and 89 (23.0%) originated from areas with low, medium and high population density, respectively. Overall, the occurrence of AMR in indicator E. coli from wild red foxes originating from areas with different human population densities in Norway was low to moderate (8.8%). The total occurrence of AMR was significantly higher; χ2 (1,N = 336) = 6.53, p = 0.01 in areas with high population density compared to areas with medium population density. Similarly, the occurrence of fluoroquinolone resistant E. coli isolated using selective detection methods was low in areas with low population density and more common in areas with medium or high population density. In conclusion, we found indications that occurrence of AMR in wild red foxes in Norway is associated with human population density. Foxes living in urban areas are more likely to be exposed to AMR bacteria and resistance drivers from food waste, garbage, sewage, waste water and consumption of contaminated prey compared to foxes living in remote areas. The homerange of red fox has been shown to be limited thereby the red fox constitutes a good sentinel for monitoring antimicrobial resistance in the environment. Continuous monitoring on the occurrence of AMR in different wild species, ecological niches and geographical areas can facilitate an increased understanding of the environmental burden of AMR in the environment. Such information is needed to further assess the impact for humans, and enables implementation of possible control measures for AMR in humans, animals and the environment in a true “One Health” approach.

Description of the Norwegian Youth Growth Study sample (max N = 1852)*.

Rupertina stabilis occupies a depth restricted biotope of suspension feeding animals situated at the Norwegian continental margin. It extends from the Voring plateau northwards for at least 200 - 300 km, in depths between 600 and 800 m. This slope position is known for relatively strong bottom currents and shifting watermass boundaries. - The species is attached to hard substrates, mainly stones or hydroid stalks and obviously prefers an elevated position. It is building a permanent cyst of sponge spicules and debris at the apertural region. The spicules are used to support a pseudopodial network similar to that described from Halyphysema (LIPPS 1983). It is believed to serve as a filter apparatus. - A review of known occurences in the Atlantic is given, suggesting a temperature adaption of the species ranging from 0°C to a maximum of 8°C. Specimens were successfully cultured for about 2-3 weeks.

After centuries of intense persecution, several large carnivore species in Europe and North America have experienced a rebound. Today's spatial configuration of large carnivore populations has likely arisen from the interplay between their ecological traits and current environmental conditions, but also from their history of persecution and protection. Yet, due to the challenge of studying population-level phenomena, we are rarely able to disentangle and quantify the influence of past and present factors driving the spatial distribution and density of these controversial species. Using spatial capture-recapture models and a data set of 742 genetically identified wolverines Gulo gulo collected over ½ million km2 across their entire range in Norway and Sweden, we identify landscape-level factors explaining the current population density of wolverines in the Scandinavian Peninsula. Distance from the relict range along the Swedish-Norwegian border, where the wolverine population survived a long history of persecution, remains a key determinant of wolverine density today. However, regional differences in management and environmental conditions also played an important role in shaping spatial patterns in present-day wolverine density. Specifically, we found evidence of slower recolonization in areas that had set lower wolverine population goals in terms of the desired number of annual reproductions. Management of transboundary large carnivore populations at biologically relevant scales may be inhibited by administrative fragmentation. Yet, as our study shows, population-level monitoring is an achievable prerequisite for a comprehensive understanding of the distribution and density of large carnivores across an increasingly anthropogenic landscape. Methods Details on wolverine Gulo gulo data are provided by Moqanaki, E. et al. (here and here) and additional references are given. In brief, this dataset include wolverine noninvasive genetic sampling data extracted from the Scandinavian large carnivore monitoring database (Rovbase 3.0; www.rovbase.no and www.rovbase.se). Wildlife authorities and volunteers conducted both structured searches and opportunistic sampling of putative wolverine scats and hair on snow throughout the species’ range in Norway and Sweden. The structured search tracks and locations of noninvasive samples were GPS recorded. Samples were then processed and analyzed by two dedicated DNA labs using a number of control measures to minimize genotyping errors. First, samples were analyzed with a Single Nucleotide Polymorphism (SNP)-chip with 96 markers. Second, all individuals were analyzed with 19 microsatellite markers to determine species and identity of wolverine individuals as well as their sex. The dataset contains noninvasive genetic sampling data of the wolverine collected between 1 December 2018 and 30 June 2019, which consists of individual identity, sex, collection date, and coordinates associated with each wolverine sample. More information about the additional filtering steps can be found here and here.

In 2023, Bring Frigo expanded its cold storage facilities near Oslo to meet growing demand from e-commerce grocery and healthcare clients. The cities of Oslo, Bergen, and Trondheim emerged as critical cold chain hubs due to their logistics connectivity, population density, and access to major food production and healthcare facilities. The Norway cold chain market was valued at NOK 8.5 billion in 2023, driven by the growing need for temperature-sensitive storage and transportation solutions in industries such as pharmaceuticals, seafood exports, and frozen food. The market is characterized by key players such as Bring Frigo, Thermo-Transit, Nor Lines, DB Schenker, and DHL Supply Chain. These companies are known for their robust infrastructure, advanced cold storage capabilities, and compliance with European and Norwegian temperature control regulations. Norway Cold Chain Market Overview and Size

Minimum inhibitory concentrations (MICs) and antimicrobial resistance in indicator Escherichia coli (n = 434) isolated from faecal swab samples from wild red foxes in Norway in 2016.

No：人口密度：每平方公里人口在12-01-2017达14.462Person/sq km，相较于12-01-2016的14.332Person/sq km有所增长。No：人口密度：每平方公里人口数据按年更新，12-01-1961至12-01-2017期间平均值为11.573Person/sq km，共57份观测结果。该数据的历史最高值出现于12-01-2017，达14.462Person/sq km，而历史最低值则出现于12-01-1961，为9.883Person/sq km。CEIC提供的No：人口密度：每平方公里人口数据处于定期更新的状态，数据来源于World Bank，数据归类于全球数据库的挪威 – Table NO.World Bank.WDI：人口和城市化进程统计。

The data for this study and represented in this file were obtained from several sources. Data on reindeer populations throughout Norway were obtained from annual reports submitted by herders for 78 populations covering a majority of the Norwegian reindeer herding area (Tveraa et al., 2007). Reindeer populations were grouped into ten management regions as in Tveraa et al. (2014). Population density was included as an area-adjusted predictor, calculated as a herd’s population size divided by the area of that herd’s summer pasture land in square kilometres. The previous autumn/winter average juvenile slaughter weight was used as a measure of herd body condition previous to birth, as per Tveraa et al. (2014). Plant productivity was measured by the normalized difference vegetation index (NDVI) for locations within the herds’ summer grazing land, data for which were collected by the Advanced Very High Resolution Radiometer (AVHRR) instrument deployed on a satellite system and available for full years since 1982. Average altitudes of the areas from which NDVI values were taken were also recorded. NDVI values were recorded twice a month, and the average NDVI value for all pixels (each pixel is 1km2) within a herd’s summer pasture was calculated for each time point. The average altitude, latitude, and longitude of the summer pastures were calculated for each herd using the GRASS GIS software. Availability of high-quality forage for reindeer was measured by the day of the year (DOY) when the maximum NDVI value first occurred for each herd’s location and each year. Spring onset for each year and each herd’s location was considered as the DOY when NDVI first reached 50% of its yearly maximum. Both the DOY when maximum NDVI occurred and spring onset were calculated from the AVHRR data. Daily snow depth (mm) for each of the herding districts from 1984 to 2013 were obtained from the Norwegian Meteorological Institute. The area under the spline curve (AUC) of ground snow depth was calculated for each year at the summer grazing pastures using daily snow depth values from September to September. The onset of winter for a given year was defined as the first DOY which had at least two consecutive weeks of snow on the ground (snow depth > 0 mm). References Cited: Tveraa, T., Fauchald, P., Gilles Yoccoz, N., Anker Ims, R., Aanes, R., and Arild Høgda, K. (2007). What regulate and limit reindeer populations in Norway? Oikos, 116(4):706–715. Tveraa, T., Stien, A., Brøseth, H., and Yoccoz, N. G. (2014). The role of predation and food limitation on claims for compensation, reindeer demography and population dynamics. Journal of Applied Ecology, 51(5):1264–1272.