As of 2024, Barbados was the most densely populated country in Latin America and the Caribbean, with approximately 652 people per square kilometer. In that same year, Argentina's population density was estimated at approximately 16.7 people per square kilometer.

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.

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 ****** inhabitants per square kilometer.

In 2022, El Salvador had the highest population density in Central America, with over 300 people per square kilometer. The second place was Guatemala, slightly over half the density in El Salvador. In 2022, Guatemala ranked as the most populated country in the region, with over 18 million inhabitants.

Historical dataset showing Latin America & Caribbean population density by year from 1961 to 2022.

Historical chart and dataset showing Latin America & Caribbean population density by year from 1961 to 2022.

As of 2021, Ecuador had a population density of 72 people per squared kilometer, the highest in South America. Colombia ranked second, with 42 people per km2 of land area. When it comes to total population in South America, Brazil had the largest number, with over 216 million inhabitants.

Our Population Density Grid Dataset for South America 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.

The Latin America and the Caribbean Population Time Series data set provides total population estimates using spatially consistent and comparable Units for Latin American municipalities or equivalent administrative Units for the years 1990 and 2000. The data set consists of two vector polygon layers: one layer displays population estimates for subnational administrative Units in 1990 and 2000, including population counts, density, and percent change, at the municipality level or equivalent (level 2); a second layer summarizes this information at the country level (level 0).

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).

This statistic shows the density of fintech startups in selected Latin American countries as of February 2019. Chile was the country with the highest number of fintechs among those selected, with more than **** fintech companies per *** million inhabitants.

• The variable names are used in Random Forest model output and throughout the text as reference to the specific data they were derived from. The first three letters are derived from the data type (e.g. “lan” indicates land cover) and the last three letters, if present, indicates what type of data each variable represents (e.g. “_cls” is a binary classification and “_dst” is a calculated Euclidean distance-to variable.† The default data for populated places is merged from several VMAP0 data sources. There are three VMAP0 data sets used: The point data pop/builtupp and pop/mispopp are buffered to 100 m and merged with the pop/builtupa polygons creating avector-based built layer. This layer is then converted to binary class and distance-to rasters for use in modeling.Country-specific data sources and variable names used for population density estimation used for dasymetric weights.

In 2025, approximately 23 million people lived in the São Paulo metropolitan area, making it the biggest in Latin America and the Caribbean and the sixth most populated in the world. The homonymous state of São Paulo was also the most populous federal entity in the country. The second place for the region was Mexico City with 22.75 million inhabitants. Brazil's cities Brazil is home to two large metropolises, only counting the population within the city limits, São Paulo had approximately 11.45 million inhabitants, and Rio de Janeiro around 6.21 million inhabitants. It also contains a number of smaller, but well known cities such as Brasília, Salvador, Belo Horizonte and many others, which report between 2 and 3 million inhabitants each. As a result, the country's population is primarily urban, with nearly 88 percent of inhabitants living in cities. Mexico City Mexico City's metropolitan area ranks sevenths in the ranking of most populated cities in the world. Founded over the Aztec city of Tenochtitlan in 1521 after the Spanish conquest as the capital of the Viceroyalty of New Spain, the city still stands as one of the most important in Latin America. Nevertheless, the preeminent economic, political, and cultural position of Mexico City has not prevented the metropolis from suffering the problems affecting the rest of the country, namely, inequality and violence. Only in 2023, the city registered a crime incidence of 52,723 reported cases for every 100,000 inhabitants and around 24 percent of the population lived under the poverty line.

In 2020, the total population of Mexico City reached 9.2 million and a population density of 6,163.3 residents by square kilometer. Population density has grown considerably in the country's capital during the past few decades, as it stood at 5,494 inhabitants per square meter in 1990.

Two different error assessment methods are presented: root mean square error (RMSE), also expressed as a percentage of the mean population size of the administrative level (% RMSE); and the mean absolute error (MAE).Accuracy assessment results for the RF, Afri/AsiaPop, GRUMP and GPW modeling methods for Cambodia, Vietnam and Kenya.

In 2020, Chile had *** technology-based startups per million population, the highest density in Latin America and the Caribbean. With a considerably higher population, Brazil reported a lower startup density, standing at *** businesses per million inhabitants. At least ** out of the ** countries depicted reported less than *** tech startup per million population in 2020.

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

In 2022, Puerto Rico reported the highest insurance density among Latin American countries. Insurance density is calculated as the ratio of total insurance premiums to the whole population of a given country. That year, insurance premiums amounted to over ***** U.S. dollars per capita in Puerto Rico. This was followed by Chile and Uruguay, with an insurance density of *** U.S. dollars and *** U.S. dollars per capita, respectively.

The earliest point where scientists can make reasonable estimates for the population of global regions is around 10,000 years before the Common Era (or 12,000 years ago). Estimates suggest that Asia has consistently been the most populated continent, and the least populated continent has generally been Oceania (although it was more heavily populated than areas such as North America in very early years). Population growth was very slow, but an increase can be observed between most of the given time periods. There were, however, dips in population due to pandemics, the most notable of these being the impact of plague in Eurasia in the 14th century, and the impact of European contact with the indigenous populations of the Americas after 1492, where it took almost four centuries for the population of Latin America to return to its pre-1500 level. The world's population first reached one billion people in 1803, which also coincided with a spike in population growth, due to the onset of the demographic transition. This wave of growth first spread across the most industrially developed countries in the 19th century, and the correlation between demographic development and industrial or economic maturity continued until today, with Africa being the final major region to begin its transition in the late-1900s.

Data from the Oak Ridge National Laboratory, LandScan Global Population 1998 Database. Estimates for rural population were obtained by excluding the Urban Population Areas. This was achieved by removing settled and partly settled grid cells from the Landcover Dataset and removing(limiting) propulation density figures to produce a net result which approximates the known rural population. Data-set has been exported as Binary format.