Monaco led the ranking for countries with the highest population density in 2024, with nearly 26,000 residents per square kilometer. The Special Administrative Region of Macao came in second, followed by Singapore. The world’s second smallest country Monaco is the world’s second-smallest country, with an area of about two square kilometers and a population of only around 40,000. It is a constitutional monarchy located by the Mediterranean Sea, and while Monaco is not part of the European Union, it does participate in some EU policies. The country is perhaps most famous for the Monte Carlo casino and for hosting the Monaco Grand Prix, the world's most prestigious Formula One race. The global population Globally, the population density per square kilometer is about 60 inhabitants, and Asia is the most densely populated region in the world. The global population is increasing rapidly, so population density is only expected to increase. In 1950, for example, the global population stood at about 2.54 billion people, and it reached over eight billion during 2023.

In 2023, Washington, D.C. had the highest population density in the United States, with 11,130.69 people per square mile. As a whole, there were about 94.83 residents per square mile in the U.S., and Alaska was the state with the lowest population density, with 1.29 residents per square mile. The problem of population density Simply put, population density is the population of a country divided by the area of the country. While this can be an interesting measure of how many people live in a country and how large the country is, it does not account for the degree of urbanization, or the share of people who live in urban centers. For example, Russia is the largest country in the world and has a comparatively low population, so its population density is very low. However, much of the country is uninhabited, so cities in Russia are much more densely populated than the rest of the country. Urbanization in the United States While the United States is not very densely populated compared to other countries, its population density has increased significantly over the past few decades. The degree of urbanization has also increased, and well over half of the population lives in urban centers.

As of July 2023, Monaco is the country with the highest population density worldwide, with an estimated population of nearly ****** per square kilometer.

This dataset presents information on the top 10 countries with the highest population density, including variables such as country name, population, land area, and population density.

Mogadishu in Somalia led the ranking of cities with the highest population density in 2023, with ****** residents per square kilometer. When it comes to countries, Monaco is the most densely populated state worldwide.

Census data reveals that population density varies noticeably from area to area. Small area census data do a better job depicting where the crowded neighborhoods are. In this map, the yellow areas of highest density range from 30,000 to 150,000 persons per square kilometer. In those areas, if the people were spread out evenly across the area, there would be just 4 to 9 meters between them. Very high density areas exceed 7,000 persons per square kilometer. High density areas exceed 5,200 persons per square kilometer. The last categories break at 3,330 persons per square kilometer, and 1,500 persons per square kilometer.This dataset is comprised of multiple sources. All of the demographic data are from Michael Bauer Research with the exception of the following countries:Australia: Esri Australia and MapData ServicesCanada: Esri Canada and EnvironicsFrance: Esri FranceGermany: Esri Germany and NexigaIndia: Esri India and IndicusJapan: Esri JapanSouth Korea: Esri Korea and OPENmateSpain: Esri España and AISUnited States: Esri Demographics

Population data for a selection of countries, allocated to 1 arcsecond blocks and provided in a combination of CSV and Cloud-optimized GeoTIFF files. This refines CIESIN’s Gridded Population of the World using machine learning models on high-resolution worldwide Maxar satellite imagery. CIESIN population counts aggregated from worldwide census data are allocated to blocks where imagery appears to contain buildings.

Knowing where people are is crucial for policymakers, particularly for the efficient allocation of resources in their country and the development of effective, people-centred policies. However, rural population distribution maps suffer from biases related to the type of dataset used to predict population density, such as the use of nighttime lights datasets in areas without electricity. This renders widely used datasets irrelevant in rural areas and biases nationwide models towards urban areas. To compensate for such biases, we aim at understanding the importance and relationship between water-related covariates and population densities in a random forest model across the urban-rural gradient. By extending a recursive feature elimination framework, we show that commonly used covariates are only selected when modelling the whole country. However, once the highest density areas are removed, water-related characteristics (especially distance to boreholes) become important covariates of population density outside of densely populated areas. This has important implications for modelling population in rural areas, including for a better estimation of the size of remote communities. When seeking to produce country-level population maps, we encourage further studies to explicitly account for rural areas by considering the urban-rural gradient and encourage the use of water-related datasets.

When enterprises evolve to deploy hybrid cloud and run HPC workloads, high-density racks are a high-availability, energy-efficient, and scalable data center infrastructure. By line of the market, it is expected to reach USD 37.2 Billion by 2025 and reach USD 52.5 Billion by 2035 with a CAGR of 3.5% for the specified forecast period.

Metric	Value
Market Size (2025E)	USD 37.2 Billion
Market Value (2035F)	USD 52.5 Billion
CAGR (2025 to 2035)	3.5%

Country-wise Analysis

Country	CAGR (2025 to 2035)
USA	3.7%

Country	CAGR (2025 to 2035)
UK	3.3%

Country	CAGR (2025 to 2035)
European Union (EU)	3.4%

Country	CAGR (2025 to 2035)
Japan	3.6%

Country	CAGR (2025 to 2035)
South Korea	3.7%

Competitive Outlook

Company Name	Estimated Market Share (%)
Vertiv Group Corp.	12-17%
Schneider Electric SE	10-14%
Rittal GmbH & Co. KG	8-12%
Eaton Corporation	7-11%
Hewlett Packard Enterprise (HPE)	5-9%
Other Companies (combined)	45-55%

The average for 2021 based on 12 countries was 25 people per square km. The highest value was in Ecuador: 72 people per square km and the lowest value was in Guyana: 4 people per square km. The indicator is available from 1961 to 2021. Below is a chart for all countries where data are available.

BY USING THIS WEBSITE OR THE CONTENT THEREIN, YOU AGREE TO THE TERMS OF USE.

This GIS shapefile, "density_contours," describes 1) a bison study area at Tallgrass Prairie National Preserve, Kansas, and 2) 25%, 50%, 75%, and 99% kernel density contours for locations of bison marked with GPS collars during 2021-2023. Percentages associated with contours describe nominal coverage, i.e., proportions of observations they are expected to encompass, and approximate the distribution of bison activity within the study area. Each contour encompasses lower-coverage contours: the 75% contour, for example, encompasses the 50% and 25% contours but not the 99% contour. An accompanying child item, "quantile_bands," is a GIS shapefile that describes quantile bands corresponding with intervals between contours in "density_contours." Each of the first 4 bands encompasses approximately 25% of bison locations. Percentages associated with contours describe nominal coverage, i.e., quantiles the bands are expected to encompass. Bands comprise a partition of the bison study area an ...

The population density picture of Boston is generally a story of two Bostons: the high density central and northern neighborhoods, and the low density southern neighborhoods.The highest density areas of Boston are particularly concentrated in Brighton, Allston, and the Fenway area, areas of the city with large numbers of college students and young adults. There is also high population density in areas such as the Back Bay, the South End, Charlestown, the North End, and South Boston. These are all relatively small areas geographically, but have housing stock conducive to population density (e.g. multi-family dwelling units, row housing, large apartment buildings). The southern neighborhoods, specifically Hyde Park and West Roxbury, have significant numbers of people living in them, but lots sizes tend to be much larger. These areas of the city also tend to have more single family dwelling units. In that, there are fewer people per square mile than places north in the city. Census data reveals that population density varies noticeably from area to area. Small area census data do a better job depicting where the crowded neighborhoods are. In this map, areas of highest density exceed 30,000 persons per square kilometer. Very high density areas exceed 7,000 persons per square kilometer. High density areas exceed 5,200 persons per square kilometer. The last categories break at 3,330 persons per square kilometer, and 1,500 persons per square kilometer.How to make this map for your city

Mauritius had the highest population density level in Africa as of 2023, with nearly 630 inhabitants per square kilometer. The country has also one of the smallest territories on the continent, which contributes to the high density. As a matter of fact, the majority of African countries with the largest concentration of people per square kilometer have the smallest geographical area as well. The exception is Nigeria, which ranks among the largest territorial countries in Africa and is very densely populated at the same time. After all, Nigeria has also the largest population on the continent.

As of 2023, the top five most densely populated cities in Latin America and the Caribbean were in Colombia. The capital, Bogotá, ranked first with over 18,241 inhabitants per square kilometer.

The high density Geosat/GM altimeter data south of 30 S have finally arrived. In addition, ERS-1 has completed more than 6 cycles of its 35-day repeat track. These data provide a dramatically improved view of the marine gravity field.

Uncover Market Research Intellect's latest High-Density Servers Market Report, valued at USD 12.5 billion in 2024, expected to rise to USD 25.3 billion by 2033 at a CAGR of 8.6% from 2026 to 2033.

The High-Density Packaging Market is segmented by Packaging Technique (MCM, MCP, SIP, 3D-TSV), by Applications ( Consumer Electronics, Aerospace & Defense, Medical Devices, IT & Telecom, Automotive, Energy and Utility), and Geography.

High-Density Polyethylene Market is anticipated to grow at a CAGR of around 5% during the forecast period 2021-26, says MarkNtel Advisors.

Within a Bayesian retrospective framework, we present a way of examining the distribution of changepoints through a novel set estimator. For a given level, α, we aim at smallest sets that cover all changepoints with a probability of at least 1 − α. These so-called smallest simultaneous credible regions, computed for certain values of α, provide parsimonious representations of the possible changepoint locations. In addition, combining them for a range of different α’s enables very informative yet condensed visualisations. Therewith we allow for the evaluation of model choices and the analysis of changepoint data to an unprecedented degree. This approach exhibits superior sensitivity, specificity and interpretability in comparison with highest density regions, marginal inclusion probabilities and confidence intervals inferred by stepR. Whilst their direct construction is usually intractable, asymptotically correct solutions can be derived from posterior samples. This leads to a novel NP-complete problem. Through reformulations into an Integer Linear Program we show empirically that a fast greedy heuristic computes virtually exact solutions.