In 2023, there were around ***** inhabitants per square kilometer living in Singapore. In comparison, there were approximately two inhabitants per square kilometer living in Mongolia that year.

As of 2025, Asia was the most densely populated region of the world, with nearly 156 inhabitants per square kilometer, whereas Oceania's population density was just over five inhabitants per square kilometer.

Our Population Density Grid Dataset for Southern Asia offers detailed, grid-based insights into the distribution of population across cities, towns, and rural areas. Free to explore and visualize, this dataset provides an invaluable resource for businesses and researchers looking to understand demographic patterns and optimize their location-based strategies.

By creating an account, you gain access to advanced tools for leveraging this data in geomarketing applications. Perfect for OOH advertising, retail planning, and more, our platform allows you to integrate population insights with your business intelligence, enabling you to make data-driven decisions for your marketing and expansion strategies.

Historical dataset showing East Asia & Pacific population density by year from 1961 to 2022.

Historical chart and dataset showing South Asia population density by year from 1961 to 2022.

Population density (people per sq. km of land area) in South Asia was reported at 405 sq. Km in 2022, according to the World Bank collection of development indicators, compiled from officially recognized sources. South Asia - Population density (people per sq. km) - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.

In 2022, the estimated population density of China was around 150.42 people per square kilometer. That year, China's population size declined for the first time in decades. Although China is the most populous country in the world, its overall population density is not much higher than the average population density in Asia. Uneven population distribution China is one of the largest countries in terms of land area, and its population density figures vary dramatically from region to region. Overall, the coastal regions in the East and Southeast have the highest population densities, as they belong to the more economically developed regions of the country. These coastal regions also have a higher urbanization rate. On the contrary, the regions in the West are covered with mountain landscapes which are not suitable for the development of big cities. Populous cities in China Several Chinese cities rank among the most populous cities in the world. According to estimates, Beijing and Shanghai will rank among the top ten megacities in the world by 2030. Both cities are also the largest Chinese cities in terms of land area. The previous colonial regions, Macao and Hong Kong, are two of the most densely populated cities in the world.

Historical chart and dataset showing East Asia & Pacific population density by year from 1961 to 2022.

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.

The Asian administrative boundaries and population database is part of an ongoing effort to improve global, spatially referenced demographic data holdings. Such databases are useful for a variety of applications including strategic-level agricultural research and applications in the analysis of the human dimensions of global change.

 This project (which has been carried out as a cooperative activity
 between NCGIA, CGIAR and UNEP/GRID between Oct. 1995 and present) has
 pooled available data sets, many of which had been assembled for the
 global demography project. All data were checked, international
 boundaries and coastlines were replaced with a standard template, the
 attribute database was redesigned, and new, more reliable population
 estimates for subnational units were produced for all countries. From
 the resulting data sets, raster surfaces representing population
 distribution and population density were created in collaboration
 between NCGIA and GRID-Geneva.

A database (NDP-068) was generated from estimates of geographically referenced carbon densities of forest vegetation in tropical Southeast Asia for 1980. A geographic information system (GIS) was used to incorporate spatial databases of climatic, edaphic, and geomorphological indices and vegetation to estimate potential (i.e., in the absence of human intervention and natural disturbance) carbon densities of forests. The resulting map was then modified to estimate actual 1980 carbon density as a function of population density and climatic zone. The database covers the following 13 countries: Bangladesh, Brunei, Cambodia (Campuchea), India, Indonesia, Laos, Malaysia, Myanmar (Burma), Nepal, the Philippines, Sri Lanka, Thailand, and Vietnam.

The data sets within this database are provided in three file formats: ARC/INFOTM exported integer grids; ASCII (American Standard Code for Information Interchange) files formatted for raster-based GIS software packages; and generic ASCII files with x, y coordinates for use with non-GIS software packages.

The database includes ten ARC/INFO exported integer grid files (five with the pixel size 3.75 km x 3.75 km and five with the pixel size 0.25 degree longitude x 0.25 degree latitude) and 27 ASCII files. The first ASCII file contains the documentation associated with this database. Twenty-four of the ASCII files were generated by means of the ARC/INFO GRIDASCII command and can be used by most raster-based GIS software packages. The 24 files can be subdivided into two groups of 12 files each.

The files contain real data values representing actual carbon and potential carbon density in Mg C/ha (1 megagram = 10^6 grams) and integer-coded values for country name, Weck's Climatic Index, ecofloristic zone, elevation, forest or non- forest designation, population density, mean annual precipitation, slope, soil texture, and vegetation classification. One set of 12 files contains these data at a spatial resolution of 3.75 km, whereas the other set of 12 files has a spatial resolution of 0.25 degree. The remaining two ASCII data files combine all of the data from the 24 ASCII data files into 2 single generic data files. The first file has a spatial resolution of 3.75 km, and the second has a resolution of 0.25 degree. Both files also provide a grid-cell identification number and the longitude and latitude of the centerpoint of each grid cell.

The 3.75-km data in this numeric data package yield an actual total carbon estimate of 42.1 Pg (1 petagram = 10^15 grams) and a potential carbon estimate of 73.6 Pg; whereas the 0.25-degree data produced an actual total carbon estimate of 41.8 Pg and a total potential carbon estimate of 73.9 Pg.

Fortran and SASTM access codes are provided to read the ASCII data files, and ARC/INFO and ARCVIEW command syntax are provided to import the ARC/INFO exported integer grid files. The data files and this documentation are available without charge on a variety of media and via the Internet from the Carbon Dioxide Information Analysis Center (CDIAC).

In 2024, the population density of Vietnam was around 306 people per square kilometer of land area. In that year, Vietnam's total population reached over 100 million. The country is among those with the highest population density in the Asia Pacific region, ranking 11 in 2020. Population density in Vietnam In comparison, Vietnam’s population density is roughly twice as much as China and Indonesia. The average population density in the world is at 59 inhabitants per square kilometer. The largest population within the country can be found in the Red River Delta and the Mekong River Delta. The most populated city is Ho Chi Minh City with roughly nine million inhabitants. Population growth in Vietnam Vietnam’s total population was forecast to surpass 109 million by 2050. Traditionally, Vietnamese families had an average of six children, while today, the birth rate is at two children per woman. This is due to an improving economy and higher living standards. In 2020, the population growth in Vietnam reached 0.90 percent, down from about three percent in the 1960s.

India's total population reached nearly **** billion people as of 2023, making the country by far the most populous throughout the Asia-Pacific region. Contrastingly, Micronesia had a total population of around *** thousand people in the same year. The demographics of APAC Asia-Pacific, made up of many different countries and regions, is the most populated region across the globe. Being home to a significant number of megacities, and with the population ever-increasing, the region is unsurprisingly expected to have the largest urban population by 2050. However, as of 2021, the majority of Asia-Pacific countries had rural populations greater than ** percent.  Population densities Despite China being the most populated country across the region, it fell in the middle of Asia-Pacific regions in terms of population density. On the other hand, Macao, Singapore, and Hong Kong all had the highest population densities across the Asia-Pacific region. These three Asia-Pacific regions also ranked among the top four densest populations worldwide.   

Estimated density of people per grid-cell, approximately 1km (0.008333 degrees) resolution. The units are number of people per Km² per pixel, expressed as unit: "ppl/Km²". The mapping approach is Random Forest-based dasymetric redistribution. The WorldPop project was initiated in October 2013 to combine the AfriPop, AsiaPop and AmeriPop population mapping projects. It aims to provide an open access archive of spatial demographic datasets for Central and South America, Africa and Asia to support development, disaster response and health applications. The methods used are designed with full open access and operational application in mind, using transparent, fully documented and peer-reviewed methods to produce easily updatable maps with accompanying metadata and measures of uncertainty. Acknowledgements information at https://www.worldpop.org/acknowledgements

population density for 2021 was 132.09, a 0.25% increase from 2020.

<ul style='margin-top:20px;'>

<li> population density for 2020 was <strong>131.76</strong>, a <strong>0.47% increase</strong> from 2019.</li>
<li> population density for 2019 was <strong>131.14</strong>, a <strong>0.57% increase</strong> from 2018.</li>
<li> population density for 2018 was <strong>130.40</strong>, a <strong>0.66% increase</strong> from 2017.</li>
</ul>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.

The Latin America population database is part of an ongoing effort to improve global, spatially referenced demographic data holdings. Such databases are useful for a variety of applications including strategic-level agricultural research and applications in the analysis of the human dimensions of global change.

 This documentation describes the Latin American Population Database, a
 collaborative effort between the International Center for Tropical
 Agriculture (CIAT), the United Nations Environment Program (UNEP-GRID,
 Sioux Falls) and the World Resources Institute (WRI). This work is
 intended to provide a population database that compliments previous
 work carried out for Asia and Africa. This data set is more detailed
 than the Africa and Asia data sets. Population estimates for 1960,
 1970, 1980, 1990 and 2000 are also provided. The work discussed in the
 following paragraphs is also related to NCGIA activities to produce a
 global database of subnational population estimates (Tobler et
 al. 1995), and an improved database for the Asian continent (Deichmann
 1996a).

In the middle of 2023, about 60 percent of the global population was living in Asia.The total world population amounted to 8.1 billion people on the planet. In other words 4.7 billion people were living in Asia as of 2023. Global populationDue to medical advances, better living conditions and the increase of agricultural productivity, the world population increased rapidly over the past century, and is expected to continue to grow. After reaching eight billion in 2023, the global population is estimated to pass 10 billion by 2060. Africa expected to drive population increase Most of the future population increase is expected to happen in Africa. The countries with the highest population growth rate in 2024 were mostly African countries. While around 1.47 billion people live on the continent as of 2024, this is forecast to grow to 3.9 billion by 2100. This is underlined by the fact that most of the countries wit the highest population growth rate are found in Africa. The growing population, in combination with climate change, puts increasing pressure on the world's resources.

Global patterns of current and future road infrastructure - Supplementary spatial data

Authors: Johan Meijer, Mark Huijbregts, Kees Schotten, Aafke Schipper

Research paper summary: Georeferenced information on road infrastructure is essential for spatial planning, socio-economic assessments and environmental impact analyses. Yet current global road maps are typically outdated or characterized by spatial bias in coverage. In the Global Roads Inventory Project we gathered, harmonized and integrated nearly 60 geospatial datasets on road infrastructure into a global roads dataset. The resulting dataset covers 222 countries and includes over 21 million km of roads, which is two to three times the total length in the currently best available country-based global roads datasets. We then related total road length per country to country area, population density, GDP and OECD membership, resulting in a regression model with adjusted R2 of 0.90, and found that that the highest road densities are associated with densely populated and wealthier countries. Applying our regression model to future population densities and GDP estimates from the Shared Socioeconomic Pathway (SSP) scenarios, we obtained a tentative estimate of 3.0–4.7 million km additional road length for the year 2050. Large increases in road length were projected for developing nations in some of the world's last remaining wilderness areas, such as the Amazon, the Congo basin and New Guinea. This highlights the need for accurate spatial road datasets to underpin strategic spatial planning in order to reduce the impacts of roads in remaining pristine ecosystems.

Contents: The GRIP dataset consists of global and regional vector datasets in ESRI filegeodatabase and shapefile format, and global raster datasets of road density at a 5 arcminutes resolution (~8x8km). The GRIP dataset is mainly aimed at providing a roads dataset that is easily usable for scientific global environmental and biodiversity modelling projects. The dataset is not suitable for navigation. GRIP4 is based on many different sources (including OpenStreetMap) and to the best of our ability we have verified their public availability, as a criteria in our research. The UNSDI-Transportation datamodel was applied for harmonization of the individual source datasets. GRIP4 is provided under a Creative Commons License (CC-0) and is free to use. The GRIP database and future global road infrastructure scenario projections following the Shared Socioeconomic Pathways (SSPs) are described in the paper by Meijer et al (2018). Due to shapefile file size limitations the global file is only available in ESRI filegeodatabase format.

Regional coding of the other vector datasets in shapefile and ESRI fgdb format:

• Region 1: North America
• Region 2: Central and South America
• Region 3: Africa
• Region 4: Europe
• Region 5: Middle East and Central Asia
• Region 6: South and East Asia
• Region 7: Oceania

Road density raster data:

• Total density, all types combined
• Type 1 density (highways)
• Type 2 density (primary roads)
• Type 3 density (secondary roads)
• Type 4 density (tertiary roads)
• Type 5 density (local roads)

Keyword: global, data, roads, infrastructure, network, global roads inventory project (GRIP), SSP scenarios

The population density in Bangladesh reached its highest in 2020, amounting to approximately 1.27 thousand people per square kilometer. The South Asian country was the tenth most densely populated country in the world in 2019. Within the Asia Pacific region, Bangladesh’s population density was only exceeded by Macao, Singapore, Hong Kong, and the Maldives. Overall, Asia had the highest population density in the world in 2018.

Population growth in Bangladesh

In 1971, Bangladesh gained its independence from Pakistan. Bangladesh’s birth rate and mortality rate had declined significantly in the past years with a life expectancy of 72.59 years in 2019. In general, the population in Bangladesh had been growing at a slow pace, slightly fluctuating around an annual rate of one percent. This growth was forecasted to continue, although it was estimated to halve by 2040. As of today, Dhaka is the largest city in Bangladesh.

Population density explained

According to the source, “population density is the mid-year population divided by land area in square kilometers.” Further, “population is based on the de facto definition of population, which counts all residents.” Bangladesh’s population reached an estimated number of 164.69 million inhabitants in 2020. In 2018, the country’s land area amounted 130.2 thousand square kilometers.

Whereas the population is expected to decrease somewhat until 2100 in Asia, Europe, and South America, it is predicted to grow significantly in Africa. While there were 1.5 billion inhabitants on the continent at the beginning of 2024, the number of inhabitants is expected to reach 3.8 billion by 2100. In total, the global population is expected to reach nearly 10.4 billion by 2100. Worldwide population In the United States, the total population is expected to steadily increase over the next couple of years. In 2024, Asia held over half of the global population and is expected to have the highest number of people living in urban areas in 2050. Asia is home to the two most populous countries, India and China, both with a population of over one billion people. However, the small country of Monaco had the highest population density worldwide in 2021. Effects of overpopulation Alongside the growing worldwide population, there are negative effects of overpopulation. The increasing population puts a higher pressure on existing resources and contributes to pollution. As the population grows, the demand for food grows, which requires more water, which in turn takes away from the freshwater available. Concurrently, food needs to be transported through different mechanisms, which contributes to air pollution. Not every resource is renewable, meaning the world is using up limited resources that will eventually run out. Furthermore, more species will become extinct which harms the ecosystem and food chain. Overpopulation was considered to be one of the most important environmental issues worldwide in 2020.