Prague was the most populous city in Czechia with nearly *** million inhabitants as of the beginning of 2025. Brno was the second largest city in population with over ******* inhabitants, followed by Ostrava with a population of around *******.

Czech Republic CZ: Population in Largest City data was reported at 1,327,947.000 Person in 2024. This records an increase from the previous number of 1,323,339.000 Person for 2023. Czech Republic CZ: Population in Largest City data is updated yearly, averaging 1,191,732.000 Person from Dec 1960 (Median) to 2024, with 65 observations. The data reached an all-time high of 1,327,947.000 Person in 2024 and a record low of 1,000,830.000 Person in 1960. Czech Republic CZ: Population in Largest City data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Czech Republic – Table CZ.World Bank.WDI: Population and Urbanization Statistics. Population in largest city is the urban population living in the country's largest metropolitan area.;United Nations, World Urbanization Prospects.;;

In 2023, the largest city in Czechia was its capital, Prague, with a population of more than 1.3 million. Together with Brno and Ostrava, these were the only three cities with more than 200,000 people.

Czech Republic CZ: Population in Largest City: as % of Urban Population data was reported at 16.527 % in 2024. This records an increase from the previous number of 16.339 % for 2023. Czech Republic CZ: Population in Largest City: as % of Urban Population data is updated yearly, averaging 16.011 % from Dec 1960 (Median) to 2024, with 65 observations. The data reached an all-time high of 17.504 % in 1960 and a record low of 15.216 % in 1980. Czech Republic CZ: Population in Largest City: as % of Urban Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Czech Republic – Table CZ.World Bank.WDI: Population and Urbanization Statistics. Population in largest city is the percentage of a country's urban population living in that country's largest metropolitan area.;United Nations, World Urbanization Prospects.;Weighted average;

Actual value and historical data chart for Czech Republic Population In Largest City

Actual value and historical data chart for Czech Republic Population In The Largest City Percent Of Urban Population

About this dataset

Context

This list ranks the 1 cities in the Republic County, KS by Czech population, as estimated by the United States Census Bureau. It also highlights population changes in each city over the past five years.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:

• 2019-2023 American Community Survey 5-Year Estimates
• 2014-2018 American Community Survey 5-Year Estimates
• 2009-2013 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by Czech Population: This column displays the rank of city in the Republic County, KS by their Czech population, using the most recent ACS data available.
• City: The City for which the rank is shown in the previous column.
• Czech Population: The Czech population of the city is shown in this column.
• % of Total City Population: This shows what percentage of the total city population identifies as Czech. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Republic County Czech Population: This tells us how much of the entire Republic County, KS Czech population lives in that city. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: This column displays the rank trend across the last 5 years.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Participation is becoming not only a theoretical framework of EU and UN documents, but also a practical approach that many municipalities explore in order to build resilient, sustainable and smart cities. The paper presents a weighted Index of Geoparticipation for all municipalities in the Czech Republic (n = 6258). The index is an indicator-based value divided into three dimensions (communication, participation, transparency) that helps to evaluate the state of geoparticipation among Czech municipalities. The size of the municipality (measured by population) and the significance of the municipality are both highly related to the values of the Index of Geoparticipation. Regional capitals, major cities, and big towns that are part of the Healthy Cities Network all have higher values for the Index of Geoparticipation.

With 3.0 Million Businesses in Czech Republic , Techsalerator has access to the highest B2B count of Data/Business data in the country. .

Thanks to our unique tools and large data specialist team, we are able to select the ideal targeted dataset based on the unique elements such as sales volume of a company, the company's location, no. of employees etc...

Whether you are looking for an entire fill install, access to our API's or if you are just looking for a one-time targeted purchase, get in touch with our company and we will fulfill your international data need.

Techsalerator covers all regions, cities and provinces in the country. A few examples :

Regions :

Karlovy Vary Region, Liberec Region, Moravian- Silesian Region, The Pardubice Region, The Ústí Region, Vysočina Region, Zlín Region, South Bohemian Region, Hradec Králové Region, The Olomouc Region, The Pilsen Region, Central Bohemia Region and Southern Moravia Region.

Cities: Prague, Czech Republic Brno, Czech Republic Ostrava, Czech Republic Plzen, Czech Republic Olomouc, Czech Republic Liberec, Czech Republic Ceske Budejovice, Czech Republic Hradec Kralove, Czech Republic Usti, Czech Republic Pardubice, Czech Republic Havirov, Czech Republic Zlin, Czech Republic Kladno, Czech Republic Most, Czech Republic Karvina, Czech Republic Frydek-mistek, Czech Republic Opava, Czech Republic Karlovy Vary, Czech Republic Decin, Czech Republic Chomutov, Czech Republic Teplice, Czech Republic Jihlava, Czech Republic Prerov, Czech Republic Prostejov, Czech Republic Jablonec, Czech Republic Jablonec nad Nisou, Czech Republic Mlada Boleslav, Czech Republic Ceska Lipa, Czech Republic Trinec, Czech Republic Trebic, Czech Republic Tabor, Czech Republic Pribram, Czech Republic Znojmo, Czech Republic Orlova, Czech Republic Cheb, Czech Republic

National Geographic's classic political map of Europe features country boundaries, thousands of place names, waterbodies, airports, major highways and roads, national parks, and much more. Includes the countries and major cities of Albania, Armenia, Austria, Azerbaijan, Belarus, Belgium, Bosnia & Herzegovina, Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Georgia, Germany, Greece, Hungary, Iceland, Ireland, Italy, Kosovo, Latvia, Liechtenstein, Lithuania, Luxembourg, Macedonia, Moldova, Montenegro, The Netherlands, Norway, Poland, Portugal, Romania, Russia, Serbia, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, Ukraine, and the United Kingdom.>> Order print map <<

Basic information

This dataset contains simulation results for the so-called Holešovičky domain, an area in the city of Prague, Czech Republic, expected to undergo major traffic infrastructure changes in the near future. Three scenarios were modelled: current infrastructure with traffic intensity projections for 2023 (C1), future outlook with a finished part of city inner ring-road in 2030 (C2) and effect of finishing the northern part of the Prague outer ring-road (C3), which will decrease heavy traffic in the domain. Note that all scenarios have slightly different landcover (trees, buildings, bridges, tunnels etc.), so there could be small areas containing NA values in the maps and GIS files. All times are in UTC (local time, CEST is UTC +02:00).

For more detailed description of the experiments see the TURBAN project website at https://www.project-turban.eu/">https://www.project-turban.eu/.

General organisation

Each scenario has two folders; post-processed results from the PALM model as averaged ASCII files that can be viewed in many GIS applications (output-gis) and maps in the PNG format (output-png). Each variable was averaged from original 10min values to 1, 3 and 24-hour averages. The C1 scenario was used as a baseline. In addition to that, also differences for all variables were calculated for the scenarios C2 and C3. In total, the C1 scenario has 3 subfolders with absolute values (prefix abs), the scenarios C2 and C3 have 6 (3 with absolute values and 3 with differences; prefix diff).

Modelled variables

Each subfolder includes 7 subfolders with variables. Variable bio_mrt is the Mean Radiant Temperature (MRT), bio_pet is the Physiological Equivalent Temperature (PET), bio_utci is the Universal Thermal Climate Index (UTCI), kc_PM10_02m is the concentration of PM10 at 2m above ground, theta_2m is the potential temperature at 2m above ground, tsurf is the surface temperature and wspeed_10m is the wind speed at 10m above ground.

File nomenclature

Each file (PRJ or ASC, PNG) has the same nomenclature. An example (bio_utci_abs-01h_20190724_1200-1300.png) could be parsed as: variable name (bio_utci), processed output (abs-01h), date (20190724) and averaged period (1200-1300). So, the result is a map with hourly averaged UTCI for 24 Jul 2019 between 12:00 and 13:00 UTC.

Important note

During the processing phase a few potentially important problems were identified and need to be analysed in detail. One of them are extremely overestimated concentrations due to stable conditions from boundary condition inputs. In certain situations it can happen that the best regional meteorological model can provide inappropriate input conditions for some episode. This needs to be checked in detail before any following interpretation.

Acknowledgements

The PALM simulations, and pre- and postprocessing were performed partially on the HPC infrastructure of the Institute of Computer Science of the Czech Academy of Sciences (ICS), supported by the long-term strategic development financing of the ICS (RVO:67985807) and partially on the IT4I HPC infrastructure supported by the Ministry of Education, Youth and Sports of the Czech Republic through the e-INFRA CZ (ID:90254). The work was performed within the project TURBAN (TO01000219; TURBAN – Turbulent-resolving urban modelling of air quality and thermal comfort) supported by Norway Grants and Technology Agency of the Czech Republic.

English description below. Reprezentativní sociologický průzkum na cílové populaci osob ve věku 18 a více let ČR je opakované, tzv. omnibusové šetření, jehož cílem je postihnout obraz města Brna v očích obyvatel ČR (tzv. vnější image). První vlna se uskutečnila v roce 2009, druhá vlna v roce 2013 a třetí vlna, která je předmětem této datové sady, v roce 2017. Hlavní výzkumné okruhy jsou: 1. Identifikace intenzity znalosti města Brna v dospělé populaci ČR, 2. Zjištění úrovně sympatií k městu Brnu, 3. Analýza image města Brna, 4. Analýza asociací obyvatel ČR spojených s městem Brnem. Výzkum byl realizován jako terénní dotazníkové šetření na reprezentativním vzorku populace Česka ve věku 18 a více let. Sběr byl realizován na základě kvótního výběru. Stanovenými kvótními znaky byly pohlaví, věk, nejvyšší dosažené vzdělání, velikost sídla a kraj bydliště respondenta. Velikost výběrového souboru: 1013 dotazníků. Datovou matici a dotazník najdete zde.A representative sociological survey of the target population of adults aged 18 and over in the Czech Republic is a repeated, so-called omnibus survey, the aim of which is to capture the image of the city of Brno in the eyes of the Czech population (the so-called external image). The first wave took place in 2009, the second wave in 2013 and the third wave, which is the subject of this data set, in 2017. The main research areas are: 1. Identification of the intensity of knowledge of the city of Brno in the adult population of the Czech Republic, 2. Determination of sympathy to the city of Brno, 3. Analysis of the image of the city of Brno. 4. Analysis of associations of the population of the Czech Republic conected with the city of Brno. The research was carried out as a field questionnaire survey on a representative sample of the Czech population aged 18 and over. The collection was carried out on the basis of quota selection. The set quota characteristics were gender, age, highest education, size of residence and region of residence of the respondent. Method: CAPI standardized F2F interviews (electronic questionnaire), • interviews took place in respondents' households • Data collection tool: questionnaire containing closed and open questions • Data collection deadline: 11 - 24 May 2017 • Sample size: 1013 questionnaires • Completion time: average 14 minutes. Data matrix and questionnaire used for the survey can be downloaded here.

Abstract

Polluted air is a major health hazard in developing countries. Improvements in pollution monitoring and statistical techniques during the last several decades have steadily enhanced the ability to measure the health effects of air pollution. Current methods can detect significant increases in the incidence of cardiopulmonary and respiratory diseases, coughing, bronchitis, and lung cancer, as well as premature deaths from these diseases resulting from elevated concentrations of ambient Particulate Matter (Holgate 1999).

Scarce public resources have limited the monitoring of atmospheric particulate matter (PM) concentrations in developing countries, despite their large potential health effects. As a result, policymakers in many developing countries remain uncertain about the exposure of their residents to PM air pollution. The Global Model of Ambient Particulates (GMAPS) is an attempt to bridge this information gap through an econometrically estimated model for predicting PM levels in world cities (Pandey et al. forthcoming).

The estimation model is based on the latest available monitored PM pollution data from the World Health Organization, supplemented by data from other reliable sources. The current model can be used to estimate PM levels in urban residential areas and non-residential pollution hotspots. The results of the model are used to project annual average ambient PM concentrations for residential and non-residential areas in 3,226 world cities with populations larger than 100,000, as well as national capitals.

The study finds wide, systematic variations in ambient PM concentrations, both across world cities and over time. PM concentrations have risen at a slower rate than total emissions. Overall emission levels have been rising, especially for poorer countries, at nearly 6 percent per year. PM concentrations have not increased by as much, due to improvements in technology and structural shifts in the world economy. Additionally, within-country variations in PM levels can diverge greatly (by a factor of 5 in some cases), because of the direct and indirect effects of geo-climatic factors.

The primary determinants of PM concentrations are the scale and composition of economic activity, population, the energy mix, the strength of local pollution regulation, and geographic and atmospheric conditions that affect pollutant dispersion in the atmosphere.

Geographic coverage

The database covers the following countries: Afghanistan Albania Algeria Andorra Angola
Antigua and Barbuda Argentina
Armenia Australia
Austria Azerbaijan
Bahamas, The
Bahrain Bangladesh
Barbados
Belarus Belgium Belize
Benin
Bhutan
Bolivia Bosnia and Herzegovina
Brazil
Brunei
Bulgaria
Burkina Faso
Burundi Cambodia
Cameroon
Canada
Cayman Islands
Central African Republic
Chad
Chile
China
Colombia
Comoros Congo, Dem. Rep.
Congo, Rep. Costa Rica
Cote d'Ivoire
Croatia Cuba
Cyprus
Czech Republic
Denmark Dominica
Dominican Republic
Ecuador Egypt, Arab Rep.
El Salvador Eritrea Estonia Ethiopia
Faeroe Islands
Fiji
Finland France
Gabon
Gambia, The Georgia Germany Ghana
Greece
Grenada Guatemala
Guinea
Guinea-Bissau
Guyana
Haiti
Honduras
Hong Kong, China
Hungary Iceland India
Indonesia
Iran, Islamic Rep.
Iraq
Ireland Israel
Italy
Jamaica Japan
Jordan
Kazakhstan
Kenya
Korea, Dem. Rep.
Korea, Rep. Kuwait
Kyrgyz Republic Lao PDR Latvia
Lebanon Lesotho Liberia Liechtenstein
Lithuania
Luxembourg
Macao, China
Macedonia, FYR
Madagascar
Malawi
Malaysia
Maldives
Mali
Mauritania
Mexico
Moldova Mongolia
Morocco Mozambique
Myanmar Namibia Nepal
Netherlands Netherlands Antilles
New Caledonia
New Zealand Nicaragua
Niger
Nigeria Norway
Oman
Pakistan
Panama
Papua New Guinea
Paraguay
Peru
Philippines Poland
Portugal
Puerto Rico Qatar
Romania Russian Federation
Rwanda
Sao Tome and Principe
Saudi Arabia
Senegal Sierra Leone
Singapore
Slovak Republic Slovenia
Solomon Islands Somalia South Africa
Spain
Sri Lanka
St. Kitts and Nevis St. Lucia
St. Vincent and the Grenadines
Sudan
Suriname
Swaziland
Sweden
Switzerland Syrian Arab Republic
Tajikistan
Tanzania
Thailand
Togo
Trinidad and Tobago Tunisia Turkey
Turkmenistan
Uganda
Ukraine United Arab Emirates
United Kingdom
United States
Uruguay Uzbekistan
Vanuatu Venezuela, RB
Vietnam Virgin Islands (U.S.)
Yemen, Rep. Yugoslavia, FR (Serbia/Montenegro)
Zambia
Zimbabwe

Kind of data

Observation data/ratings [obs]

Mode of data collection

Other [oth]

最大城市人口在12-01-2024达1,327,947.000人，相较于12-01-2023的1,323,339.000人有所增长。最大城市人口数据按年更新，12-01-1960至12-01-2024期间平均值为1,191,732.000人，共65份观测结果。该数据的历史最高值出现于12-01-2024，达1,327,947.000人，而历史最低值则出现于12-01-1960，为1,000,830.000人。CEIC提供的最大城市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捷克共和国 – Table CZ.World Bank.WDI: Population and Urbanization Statistics。

Related publication: Souverijns, N. et al. (in review). 100m climate and heat stress information up to 2100 for 142 cities around the globe. Scientific Data.

Related dashboard: https://climate-risk-dashboard.climateanalytics.org/

A zip archive of decadal climate, heat stress and impact indicators for 142 cities around the world obtained using the UrbClim model. Information is available at 100m resolution for each decade up to 2100 for three future clilmate scenarios (including climate model uncertainty):

• Current Policies
• Shifting Pathways
• Delayed Action / Gradual Strengthening

The cities are listed in the table below and are offered in separate zip archives per country.

The scripts to process the model data can be found in python_scripts.zip

The data is provided in both Geotiff and NetCDF format. A zip archive for each city is generated. Each zip file contains two folder:

• Geotiffs
• Netcdfs

Each file has the following file structure: [indicator_filename]_[decade]_[climate_scenario]_[uncertainty]_[projection].[format]

Indicator name (a defintion for each indicator can be found in the publication above):

Decade:

2011-2020; 2021-2030;...;2091-2100

Climate scenario:

Uncertainty:

Projection:

The Geotiffs and NetCDFs are always provided in a local projection depending on the country / continent (This can be retrieved from the metadata of the files). Furthermore, the Geotiffs are also provided in EPSG:4326 which is then denoted in the

English description below. Reprezentativní sociologický průzkum na cílové populaci osob ve věku 18 a více let ČR je opakované, tzv. omnibusové šetření, jehož cílem je postihnout obraz města Brna v očích obyvatel ČR (tzv. vnější image). Vlny výzkumu se uskutečnily v letech 2009, 2013, 2017, 2022 a 2025. Hlavní výzkumné okruhy jsou: 1. Identifikace intenzity znalosti města Brna v dospělé populaci ČR, 2. Zjištění úrovně sympatií k městu Brnu, 3. Analýza image města Brna, 4. Analýza asociací obyvatel ČR spojených s městem Brnem. Sběr byl realizován na základě kvótního výběru. Stanovenými kvótními znaky byly pohlaví, věk, nejvyšší dosažené vzdělání, velikost sídla a kraj bydliště respondenta. Velikost výběrového souboru: 1033 dotazníků. Datovou matici a dotazník najdete zde.A representative sociological survey of the target population of people aged 18 and over in the Czech Republic is a repeated, so-called omnibus survey, the aim of which is to capture the image of the city of Brno in the eyes of the inhabitants of the Czech Republic (the so-called external image). The waves of the research took place in the years 2009, 2013, 2017, 2022 and 2025. The main research areas are: 1. Identification of the intensity of knowledge of the city of Brno in the adult population of the Czech Republic, 2. Determination of the level of sympathy for the city of Brno, 3. Analysis of the image of the city of Brno, 4. Analysis of associations of the inhabitants of the Czech Republic associated with the city of Brno. The data collection was carried out on the basis of quota selection. The quota characteristics set were gender, age, highest education achieved, size of the settlement and region of residence of the respondent. Size of the sample: 1033 questionnaires. The data matrix and questionnaire can be found here.

English description below. Reprezentativní sociologický průzkum na cílové populaci osob ve věku 18 a více let ČR je opakované, tzv. omnibusové šetření, jehož cílem je postihnout obraz města Brna v očích obyvatel ČR (tzv. vnější image). První vlna se uskutečnila v roce 2009, druhá vlna v roce 2013, třetí vlna v roce 2017 a čtvrtá vlna, která je předmětem této datové sady, v roce 2022. Hlavní výzkumné okruhy jsou: 1. Identifikace intenzity znalosti města Brna v dospělé populaci ČR, 2. Zjištění úrovně sympatií k městu Brnu, 3. Analýza image města Brna, 4. Analýza asociací obyvatel ČR spojených s městem Brnem. Výzkum byl realizován jako terénní dotazníkové šetření na reprezentativním vzorku populace Česka ve věku 18 a více let. Sběr byl realizován na základě kvótního výběru. Stanovenými kvótními znaky byly pohlaví, věk, nejvyšší dosažené vzdělání, velikost sídla a kraj bydliště respondenta. Velikost výběrového souboru: 1023 dotazníků. Datovou matici (ve formátu .sav) najdete zde.A representative sociological survey of the target population of adults aged 18 and over in the Czech Republic is a repeated, so-called omnibus survey, the aim of which is to capture the image of the city of Brno in the eyes of the Czech population (the so-called external image). The first wave took place in 2009, the second wave in 2013, the third wave in 2017, and the forth wave, which is the subject of this data set, in 2022. The main research areas are: 1. Identification of the intensity of knowledge of the city of Brno in the adult population of the Czech Republic, 2. Determination of sympathy to the city of Brno, 3. Analysis of the image of the city of Brno. 4. Analysis of associations of the population of the Czech Republic conected with the city of Brno. The research was carried out as a field questionnaire survey on a representative sample of the Czech population aged 18 and over. The collection was carried out on the basis of quota selection. The set quota characteristics were gender, age, highest education, size of residence and region of residence of the respondent. Method: CAPI standardized F2F interviews (electronic questionnaire), • interviews took place in respondents' households • Data collection tool: questionnaire containing closed and open questions • Data collection deadline: Spring of the year 2022 • Sample size: 1023 questionnaires • Data matrix (.sav) can be downloaded here.

English description below. Cílem výzkumu Vnímání image města Brna v zahraničí bylo popsat aktuální stav znalosti a vnímání Brna v okolních zemích, vyhodnotit asociace spojované s městem Brnem v zahraničí a porovnat je s asociacemi ostatních českých měst, a definovat zdroje informací o městě. Výzkum byl realizován ve čtyřech státech (Slovensko, Polsko, Německo a Rakousko) na vzorku 1 500 respondentů prostřednictvím on-line dotazování na reprezentativním panelu. Cílovou skupinou šetření byli zahraniční turisté všech věkových kategorií (ve věku 15+), kteří alespoň jednou v posledních 3 letech navštívili ČR, a to na 1 nebo více dní anebo uvažují nad návštěvou v příštích 12 měsících. Datovou matici, tabulky a dotazník najdete zde.Main goals of the research on the perception of the image of the city of Brno abroad - describe the current state of knowledge and perception of Brno in neighboring countries, analyze the current perception of the image of the city abroad, evaluate associations with the city of Brno and compare them with associations of other Czech cities. The research was conducted in four countries (Slovakia, Poland, Germany and Austria) on a sample of 1,500 respondents through online surveys on a representative panel. The target group of the survey were foreign tourists of all ages (aged 15+) who visited the Czech Republic at least once in the last 3 years, for 1 or more days or are considering a visit in the next 12 months. Data matrix, questionnaire and tables can be found here.