WorldPop produces different types of gridded population count datasets, depending on the methods used and end application.
Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset.
Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 30 arc-seconds (approximately 1km at the equator)
-Unconstrained individual countries 2000-2020: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding
Unconstrained individual countries 2000-2020 population count datasets by dividing the number of people in each pixel by the pixel surface area.
These are produced using the unconstrained top-down modelling method.
-Unconstrained individual countries 2000-2020 UN adjusted: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding
Unconstrained individual countries 2000-2020 population UN adjusted count datasets by dividing the number of people in each pixel,
adjusted to match the country total from the official United Nations population estimates (UN 2019), by the pixel surface area.
These are produced using the unconstrained top-down modelling method.
Data for earlier dates is available directly from WorldPop.
WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00674
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<ul style='margin-top:20px;'>
<li>Guatemala population density for 2021 was <strong>164.23</strong>, a <strong>1.39% increase</strong> from 2020.</li>
<li>Guatemala population density for 2020 was <strong>161.98</strong>, a <strong>1.48% increase</strong> from 2019.</li>
<li>Guatemala population density for 2019 was <strong>159.61</strong>, a <strong>1.53% increase</strong> from 2018.</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.
In 2021, the population density in Guatemala was estimated at around 159.7 people per square kilometer, up from 157.3 inhabitants per square kilometer registered a year earlier. Over the past decade, the population density of this Central American country increased by almost 18 percent.
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Population density (people per sq. km of land area) in Guatemala was reported at 167 sq. Km in 2022, according to the World Bank collection of development indicators, compiled from officially recognized sources. Guatemala - Population density (people per sq. km) - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.
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Guatemala GT: Population Density: People per Square Km data was reported at 157.834 Person/sq km in 2017. This records an increase from the previous number of 154.745 Person/sq km for 2016. Guatemala GT: Population Density: People per Square Km data is updated yearly, averaging 84.457 Person/sq km from Dec 1961 (Median) to 2017, with 57 observations. The data reached an all-time high of 157.834 Person/sq km in 2017 and a record low of 40.464 Person/sq km in 1961. Guatemala GT: 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 Guatemala – Table GT.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;
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Guatemala: Population density, in people per sq. mile: The latest value from is people per sq. mile, unavailable from people per sq. mile in . In comparison, the world average is 0 people per sq. mile, based on data from countries. Historically, the average for Guatemala from to is people per sq. mile. The minimum value, people per sq. mile, was reached in while the maximum of people per sq. mile was recorded in .
EN.POP.DNST. 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 World Bank’s ESG Data Draft dataset provides information on 17 key sustainability themes spanning environmental, social, and governance categories.
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.
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population of Guatemala. name, long name, population (source), population, constitutional form, drives on, head of state authority, Main continent, number of airports, Airports - with paved runways, Airports - with unpaved runways, Area, Birth rate, calling code, Children under the age of 5 years underweight, Current Account Balance, Death rate, Debt - external, Economic aid donor, Electricity consumption, Electricity consumption per capita, Electricity exports, Electricity imports, Electricity production, Exports, GDP - per capita (PPP), GDP (purchasing power parity), GDP real growth rate, Gross national income, Human Development Index, Health expenditures, Heliports, HIV AIDS adult prevalence rate, HIV AIDS deaths, HIV AIDS people living with HIV AIDS, Hospital bed density, capital city, Currency, Imports, Industrial production growth rate, Infant mortality rate, Inflation rate consumer prices, Internet hosts, internet tld, Internet users, Investment (gross fixed), iso 3166 code, ISO CODE, Labor force, Life expectancy at birth, Literacy, Manpower available for military service, Manpower fit for military service, Manpower reaching militarily age annually, is democracy, Market value of publicly traded shares, Maternal mortality rate, Merchant marine, Military expenditures percent of GDP, Natural gas consumption, Natural gas consumption per capita, Natural gas exports, Natural gas imports, Natural gas production, Natural gas proved reserves, Net migration rate, Obesity adult prevalence rate, Oil consumption, Oil consumption per capita, Oil exports, Oil imports, Oil production, Oil proved reserves, Physicians density, Population below poverty line, Population census, Population density, Population estimate, Population growth rate, Public debt, Railways, Reserves of foreign exchange and gold, Roadways, Stock of direct foreign investment abroad, Stock of direct foreign investment at home, Telephones main lines in use, Telephones main lines in use per capita, Telephones mobile cellular, Telephones mobile cellular per capita, Total fertility rate, Unemployment rate, Unemployment, youth ages 15-24, Waterways, valley, helicopter, canyon, artillery, crater, religion, continent, border, Plateau, marsh, Demonym
Density of nursing and midwifery personnel of Guatemala rocketed by 75.78% from 1.3 number per thousand population in 2018 to 2.3 number per thousand population in 2020. Since the 9.51% surge in 2014, density of nursing and midwifery personnel shot up by 141.42% in 2020.
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Comprehensive socio-economic dataset for Guatemala 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.
The share of urban population in Guatemala saw no significant changes in 2023 in comparison to the previous year 2022 and remained at around 53.1 percent. Nevertheless, 2023 still represents a peak in the share in Guatemala with 53.1 percent. A population may be defined as urban depending on the size (population or area) or population density of the village, town, or city. The urbanization rate then refers to the share of the total population who live in an urban setting. International comparisons may be inconsistent due to differing parameters for what constitutes an urban center.Find more key insights for the share of urban population in countries like Panama and Belize.
The share of urban population in Guatemala stood at 53.1 percent in 2023. In a steady upward trend, the share rose by 21.98 percentage points from 1960.
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The raster dataset consists of a 500 m score grid for the crop storage location, produced under the scope of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis for value chain infrastructure location.
The location score is achieved by processing sub-model outputs that characterize considered factors for crop warehouse location:
• Supply: Maize.
• Demand: Human population density, Major cities population (national and bordering countries).
• Infrastructure/accessibility: main transportation infrastructure.
• Socio-economic/poverty: Figueroa, Marsicovetere & Peñate (2020).
It consists of an arithmetic weighted sum of normalized grids (0 to 100):
("Crop Production" * 0.4) + ("Human Population Density" * 0.2) + (”Poverty” * 0.1) + (“Major Cities Accessibility” * 0.1) + (“Regional Cities Accessibility” * 0.1) + (“Port Accessibility” * 0.1).
Data publication: 2022-11-24
Contact points:
Metadata Contact: FAO-Data
Resource Contact: Justeen De Ocampo
Data lineage:
Major data sources, FAO GIS platform Hand-in-Hand and OpenStreetMap (open data) including the following datasets:
Resource constraints:
Creative Commons Attribution-NonCommercial-ShareAlike 3.0 IGO (CC BY-NC- SA 3.0 IGO)
Online resources:
Zipped raster TIF file for Crop Storage Location Score: Maize (Guatemala - ~ 500m)
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GT:人口密度:每平方公里人口在12-01-2017达157.834Person/sq km,相较于12-01-2016的154.745Person/sq km有所增长。GT: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84.457Person/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157.834Person/sq km,而历史最低值则出现于12-01-1961,为40.464Person/sq km。CEIC提供的GT: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危地马拉 – 表 GT.世行.WDI:人口和城市化进程统计。
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Synthetic populations for regions of the World (SPW) | Guatemala
Dataset information
A synthetic population of a region as provided here, captures the people of the region with selected demographic attributes, their organization into households, their assigned activities for a day, the locations where the activities take place and thus where interactions among population members happen (e.g., spread of epidemics).
License
Acknowledgment
This project was supported by the National Science Foundation under the NSF RAPID: COVID-19 Response Support: Building Synthetic Multi-scale Networks (PI: Madhav Marathe, Co-PIs: Henning Mortveit, Srinivasan Venkatramanan; Fund Number: OAC-2027541).
Contact information
Henning.Mortveit@virginia.edu
Identifiers
Region name | Guatemala |
Region ID | gtm |
Model | coarse |
Version | 0_9_0 |
Statistics
Name | Value |
---|---|
Population | 14137968.0 |
Average age | 22.8 |
Households | 3107786.0 |
Average household size | 4.6 |
Residence locations | 3107786.0 |
Activity locations | 650298.0 |
Average number of activities | 7.2 |
Average travel distance | 53.2 |
Sources
Description | Name | Version | Url |
---|---|---|---|
Activity template data | World Bank | 2021 | https://data.worldbank.org |
Administrative boundaries | ADCW | 7.6 | https://www.adci.com/adc-worldmap |
Curated POIs based on OSM | SLIPO/OSM POIs | http://slipo.eu/?p=1551 https://www.openstreetmap.org/ | |
Household data | DHS | https://dhsprogram.com | |
Population count with demographic attributes | GPW | v4.11 | https://sedac.ciesin.columbia.edu/data/set/gpw-v4-admin-unit-center-points-population-estimates-rev11 |
Files description
Base data files (gtm_data_v_0_9.zip)
Filename | Description |
---|---|
gtm_person_v_0_9.csv | Data for each person including attributes such as age, gender, and household ID. |
gtm_household_v_0_9.csv | Data at household level. |
gtm_residence_locations_v_0_9.csv | Data about residence locations |
gtm_activity_locations_v_0_9.csv | Data about activity locations, including what activity types are supported at these locations |
gtm_activity_location_assignment_v_0_9.csv | For each person and for each of their activities, this file specifies the location where the activity takes place |
Derived data files
Filename | Description |
---|---|
gtm_contact_matrix_v_0_9.csv | A POLYMOD-type contact matrix constructed from a network representation of the location assignment data and a within-location contact model. |
Validation and measures files
Filename | Description |
---|---|
gtm_household_grouping_validation_v_0_9.pdf | Validation plots for household construction |
gtm_activity_durations_{adult,child}_v_0_9.pdf | Comparison of time spent on generated activities with survey data |
gtm_activity_patterns_{adult,child}_v_0_9.pdf | Comparison of generated activity patterns by the time of day with survey data |
gtm_location_construction_0_9.pdf | Validation plots for location construction |
gtm_location_assignement_0_9.pdf | Validation plots for location assignment, including travel distribution plots |
gtm_gtm_ver_0_9_0_avg_travel_distance.pdf | Choropleth map visualizing average travel distance |
gtm_gtm_ver_0_9_0_travel_distr_combined.pdf | Travel distance distribution |
gtm_gtm_ver_0_9_0_num_activity_loc.pdf | Choropleth map visualizing number of activity locations |
gtm_gtm_ver_0_9_0_avg_age.pdf | Choropleth map visualizing average age |
gtm_gtm_ver_0_9_0_pop_density_per_sqkm.pdf | Choropleth map visualizing population density |
gtm_gtm_ver_0_9_0_pop_size.pdf | Choropleth map visualizing population size |
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Predicted rates of dengue fever (DF) incidence rate with an increase in temperature of 1–2°C for the three municipalities with the lowest minimum annual temperature, three with the highest minimum temperature, and for the municipality of Guatemala, which contains the capital Guatemala City.
1.3 (number per thousand population) in 2020.
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Number of dengue fever cases for 2017–2018 for each municipality in Guatemala.
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Arbovirus frequency among cases; viral and bacterial infections among diarrheal controls, Santa Rosa, Guatemala, 2011–2018.
WorldPop produces different types of gridded population count datasets, depending on the methods used and end application.
Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset.
Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 30 arc-seconds (approximately 1km at the equator)
-Unconstrained individual countries 2000-2020: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding
Unconstrained individual countries 2000-2020 population count datasets by dividing the number of people in each pixel by the pixel surface area.
These are produced using the unconstrained top-down modelling method.
-Unconstrained individual countries 2000-2020 UN adjusted: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding
Unconstrained individual countries 2000-2020 population UN adjusted count datasets by dividing the number of people in each pixel,
adjusted to match the country total from the official United Nations population estimates (UN 2019), by the pixel surface area.
These are produced using the unconstrained top-down modelling method.
Data for earlier dates is available directly from WorldPop.
WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00674