This statistic shows the biggest cities in Thailand in 2019. In 2019, approximately 5.67 million people lived in Krung Thep, i.e. Bangkok, making it the biggest city in Thailand.

Population in largest city in Thailand was reported at 11233869 in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Thailand - Population in largest city - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.

Thailand TH: Population in Largest City: as % of Urban Population data was reported at 29.142 % in 2017. This records an increase from the previous number of 28.917 % for 2016. Thailand TH: Population in Largest City: as % of Urban Population data is updated yearly, averaging 35.514 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 40.429 % in 1969 and a record low of 28.054 % in 2010. Thailand TH: 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 Thailand – Table TH.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;

In 2023, Bangkok had the highest population density of all provinces in Thailand, with almost 3,500 people per square kilometer. Nonthaburi followed second, with a population density of around 2,100 people per square kilometer.

Chart and table of population level and growth rate for the Bangkok, Thailand metro area from 1950 to 2025.

Population in the largest city (% of urban population) in Thailand was reported at 28.86 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Thailand - Population in the largest city - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.

This statistic shows the degree of urbanization in Thailand from 2013 to 2023. Urbanization means the share of urban population in the total population of a country. In 2023, 53.61 percent of Thailand's total population lived in urban areas and cities. The migration of the Thai population to metropolises and urban areas Thailand is in the midst of transforming itself from a predominantly rural country to an increasingly urban one. Today, over half the population lives in urban areas, which is much higher than most bordering countries. While Thailand's urbanization rates are still low compared to more developed nations - which can reach levels over 90 percent, this transformation in Thailand is still significant, especially as most of this growth occurs and is expected to occur in the Krung Thep area, better known as Bangkok, capital and largest city in Thailand. Krung Thep is now home to more than 5.6 million people. The number of tourists and overnight visitors to the city is also on the rise, and Bangkok is usually among the ten most visited cities in each year, with over 20 million visitors in 2023. This development will place increasing demands on urban infrastructure, as the city grows and grows. The second largest city in Thailand is Nonthaburi, but it only has around one quarter of a million inhabitants, a significant difference. Despite the country’s rural but shifting population, Thailand's fertility rate is low and well below the natural replacement rate, and population growth in general is thus only minimal. Interestingly, despite this migration, agriculture has retained a stable share in GDP generation, actually increasing slightly over time, while the contributions of industry and services to GDP have also remained relatively the same.

Thailand TH: Population in Largest City data was reported at 9,898,653.000 Person in 2017. This records an increase from the previous number of 9,647,526.000 Person for 2016. Thailand TH: Population in Largest City data is updated yearly, averaging 5,707,377.000 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 9,898,653.000 Person in 2017 and a record low of 2,150,853.000 Person in 1960. Thailand TH: Population in Largest City data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Thailand – Table TH.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.; ;

Chart and table of population level and growth rate for the Khon-Kaen, Thailand metro area from 1950 to 2025.

The number of households in Thailand was forecasted to be approximately 18.2 million in 2021, compared to 18 million households in 2016.

Rural Population in Thailand
Thailand’s rural population mostly resides in the rice-growing regions, i.e. the central, northeastern, and northern regions. In 2018, approximately 34.75 million people lived in the rural area, which accounted for 50 percent of the total population in Thailand. Nevertheless, Thailand’s rural population is declining as it has been over the past nine years.

Urban population in Thailand
As Thailand has transformed into a more industrially orientated country, urban living and city life seemed to follow the development. Thai rural inhabitants started to migrate to urban areas and bigger cities such as Bangkok, as there were more job opportunities. Therefore, urbanization became a reality in Thailand, with the urban population accounting for 50.05 percent of the total population in 2019.

Chart and table of population level and growth rate for the Ratchaburi, Thailand metro area from 1950 to 2025.

Chart and table of population level and growth rate for the Nonthaburi, Thailand metro area from 1950 to 2025.

The US Census Bureau defines Asian as "A person having origins in any of the original peoples of the Far East, Southeast Asia, or the Indian subcontinent, including, for example, Cambodia, China, India, Japan, Korea, Malaysia, Pakistan, the Philippine Islands, Thailand, and Vietnam. This includes people who reported detailed Asian responses such as: Indian, Bangladeshi, Bhutanese, Burmese, Cambodian, Chinese, Filipino, Hmong, Indonesian, Japanese, Korean, Laotian, Malaysian, Nepalese, Pakistani, Sri Lankan, Taiwanese, Thai, Vietnamese, Other Asian specified, Other Asian not specified.". 2020 Census block groups for the Wichita / Sedgwick County area, clipped to the county line. Features were extracted from the 2020 State of Kansas Census Block Group shapefile provided by the State of Kansas GIS Data Access and Support Center (https://www.kansasgis.org/index.cfm).Change in Population and Housing for the Sedgwick County area from 2010 - 2020 based upon US Census. Census Blocks from 2010 were spatially joined to Census Block Groups from 2020 to compare the population and housing figures. This is not a product of the US Census Bureau and is only available through City of Wichita GIS. Please refer to Census Block Groups for 2010 and 2020 for verification of all data Standard block groups are clusters of blocks within the same census tract that have the same first digit of their 4-character census block number. For example, blocks 3001, 3002, 3003… 3999 in census tract 1210.02 belong to Block Group 3. Due to boundary and feature changes that occur throughout the decade, current block groups do not always maintain these same block number to block group relationships. For example, block 3001 might move due to a change in the census tract boundary. Even if the block is no longer in block group 3, the block number (3001) will not change. However, the identification string (GEOID20) for that block, identifying block group 3, would remain the same in the attribute information in the TIGER/Line Shapefiles because block identification strings are always built using the decennial geographic codes.Block groups delineated for the 2020 Census generally contain between 600 and 3,000 people. Local participants delineated most block groups as part of the Census Bureau's Participant Statistical Areas Program (PSAP). The Census Bureau delineated block groups only where a local or tribal government declined to participate or where the Census Bureau could not identify a potential local participant.A block group usually covers a contiguous area. Each census tract contains at least one block group and block groups are uniquely numbered within census tract. Within the standard census geographic hierarchy, block groups never cross county or census tract boundaries, but may cross the boundaries of county subdivisions, places, urban areas, voting districts, congressional districts, and American Indian, Alaska Native, and Native Hawaiian areas.Block groups have a valid range of 0 through 9. Block groups beginning with a zero generally are in coastal and Great Lakes water and territorial seas. Rather than extending a census tract boundary into the Great Lakes or out to the 3-mile territorial sea limit, the Census Bureau delineated some census tract boundaries along the shoreline or just offshore.

This dataset is about countries, has 1 rows. and is filtered where the country includes Thailand. It features 5 columns: country, currency, capital city, continent, and land area. The preview is ordered by population (descending).

Chart and table of population level and growth rate for the Lamphun, Thailand metro area from 1950 to 2025.

Poor management of dog populations causes many problems in different countries, including rabies. To strategically design a dog population management, certain sets of data are required, such as the population size and spatial distribution of dogs. However, these data are rarely available or incomplete. Hence, this study aimed to describe the characteristics of dog populations in Thailand, explore their spatial distribution and relevant factors, and estimate the number of dogs in the whole country. First, four districts were selected as representatives of each region. Each district was partitioned into grids with a 300-m resolution. The selected grids were then surveyed, and the number of dogs and related data were collected. Random forest models with a two-part approach were used to quantify the association between the surveyed dog population and predictor variables. The spatial distribution of dog populations was then predicted. A total of 1,750 grids were surveyed (945 grids with dog presence and 805 grids with dog absence). Among the surveyed dogs, 86.6% (12,027/13,895) were owned. Of these, 51% were classified as independent, followed by confined (25%), semi-independent (21%), and unidentified dogs (3%). Seventy-two percent (1,348/1,868) of the ownerless dogs were feral, and the rest were community dogs. The spatial pattern of the dog populations was highly distributed in big cities such as Bangkok and its suburbs. In owned dogs, it was linked to household demographics, whereas it was related to community factors in ownerless dogs. The number of estimated dogs in the entire country was 12.8 million heads including 11.2 million owned dogs (21.7 heads/km2) and 1.6 million ownerless dogs (3.2 heads/km2). The methods developed here are extrapolatable to a larger area and use much less budget and manpower compared to the present practices. Our results are helpful for canine rabies prevention and control programs, such as dog population management and control and rabies vaccine allocation.

Year, administrative region, the number of new immigrants in the current month _ statistical values, male statistical values of mainland China including Hong Kong and Macau, female statistical values of mainland China including Hong Kong and Macau, male statistical values of Vietnam, female statistical values of Vietnam, male statistical values of Malaysia, female statistical values of Malaysia, male statistical values of Indonesia, female statistical values of Indonesia, male statistical values of Thailand, female statistical values of Thailand, male statistical values of the Philippines, female statistical values of the Philippines, male statistical values of other nationalities, female statistical values of other nationalities

Chart and table of population level and growth rate for the Lampang, Thailand metro area from 1950 to 2025.

Chart and table of population level and growth rate for the Chanthaburi, Thailand metro area from 1950 to 2025.

Chart and table of population level and growth rate for the Phuket, Thailand metro area from 1950 to 2025.