The statistic shows the population of Xi'an in China from 1980 to 2010, with forecasts up until 2035. In 2010, the population of Xi'an had amounted to about 5.53 million inhabitants and was forecasted to reach around eight million by 2020.

Chart and table of population level and growth rate for the Xian, Shaanxi, China metro area from 1950 to 2025. United Nations population projections are also included through the year 2035.

Population: Shaanxi: Xian: Changan data was reported at 1,367.726 Person th in 2023. This records an increase from the previous number of 1,347.796 Person th for 2022. Population: Shaanxi: Xian: Changan data is updated yearly, averaging 1,049.490 Person th from Dec 2004 (Median) to 2023, with 20 observations. The data reached an all-time high of 1,367.726 Person th in 2023 and a record low of 926.000 Person th in 2004. Population: Shaanxi: Xian: Changan data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GJ: Population: County Level Region.

In 2021, around 27.8 million people were estimated to be living in the urban area of Shanghai. Shanghai was the largest city in China in 2021, followed by Beijing, with around 20.9 million inhabitants.

The rise of the new first-tier cities

The past decades have seen widespread and rapid urbanization and demographic transition in China. While the four first-tier megacities, namely Beijing, Shanghai, Guangzhou, and Shenzhen, are still highly attractive to people and companies due to their strong ability to synergize the competitive economic and social resources, some lower-tier cities are already facing declining populations, especially those in the northeastern region. Below the original four first-tier cities, 15 quickly developing cities are sharing the cake of the moving population with improving business vitality and GDP growth potential. These new first-tier cities are either municipalities directly under the central government, such as Chongqing and Tianjin, or regional central cities and provincial capitals, like Chengdu and Wuhan, or open coastal cities in the economically developed eastern regions.

From urbanization to metropolitanization

As more and more Chinese people migrate to large cities for better opportunities and quality of life, the ongoing urbanization has further evolved into metropolitanization. Among those metropolitans, Shenzhen's population exceeded 17.6 million in 2020, a nearly 70 percent increase from a decade ago, compared to eight percent in the already densely populated Shanghai. However, with people rushing into the big-four cities, the cost of housing, and other living standards, are soaring. As of 2020, the average sales price for residential real estate in Shenzhen exceeded 56,800 yuan per square meter. As a result, the fast-growing and more cost-effective new first-tier cities would be more appealing in the coming years. Furthermore, Shanghai and Beijing have set plans to control the size of their population to 25 and 23 million, respectively, before 2035.

Population: Usual Residence: Urbanization Rate: Shaanxi: Xian data was reported at 79.880 % in 2023. This records an increase from the previous number of 79.590 % for 2022. Population: Usual Residence: Urbanization Rate: Shaanxi: Xian data is updated yearly, averaging 74.470 % from Dec 2005 (Median) to 2023, with 19 observations. The data reached an all-time high of 79.880 % in 2023 and a record low of 63.280 % in 2005. Population: Usual Residence: Urbanization Rate: Shaanxi: Xian data remains active status in CEIC and is reported by Xian Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GE: Population: Prefecture Level City: Urbanization Rate.

Population: Shaanxi: Xian: Zhouzhi data was reported at 694.992 Person th in 2023. This records a decrease from the previous number of 698.388 Person th for 2022. Population: Shaanxi: Xian: Zhouzhi data is updated yearly, averaging 682.385 Person th from Dec 2004 (Median) to 2023, with 20 observations. The data reached an all-time high of 699.374 Person th in 2020 and a record low of 630.000 Person th in 2005. Population: Shaanxi: Xian: Zhouzhi data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GJ: Population: County Level Region.

Population: Shaanxi: Xian: Household Registration data was reported at 10,145.921 Person th in 2022. This records an increase from the previous number of 9,994.529 Person th for 2021. Population: Shaanxi: Xian: Household Registration data is updated yearly, averaging 7,816.700 Person th from Dec 1996 (Median) to 2022, with 27 observations. The data reached an all-time high of 10,145.921 Person th in 2022 and a record low of 6,548.700 Person th in 1996. Population: Shaanxi: Xian: Household Registration data remains active status in CEIC and is reported by Xian Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GE: Population: Prefecture Level City.

About this dataset

Context

The dataset tabulates the Cottonwood population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Cottonwood across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Cottonwood was 11, a 0% decrease year-by-year from 2022. Previously, in 2022, Cottonwood population was 11, a decline of 8.33% compared to a population of 12 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Cottonwood increased by 5. In this period, the peak population was 12 in the year 2021. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Cottonwood is shown in this column.
• Year on Year Change: This column displays the change in Cottonwood population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

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/.

Recommended for further research

This dataset is a part of the main dataset for Cottonwood Population by Year. You can refer the same here

Population: Shaanxi: Xian: Lantian data was reported at 654.342 Person th in 2023. This records a decrease from the previous number of 656.918 Person th for 2022. Population: Shaanxi: Xian: Lantian data is updated yearly, averaging 651.970 Person th from Dec 2004 (Median) to 2023, with 20 observations. The data reached an all-time high of 657.632 Person th in 2021 and a record low of 630.000 Person th in 2005. Population: Shaanxi: Xian: Lantian data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GJ: Population: County Level Region.

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Occupied dwelling

UNITS IDENTIFIED: - Dwellings: Yes - Households: Yes - Individuals: Yes - Group quarters: Not available in microdata sample

UNIT DESCRIPTIONS: - Group quarters: Building used to shelter people for reasons of assistance, health, education, religion, confinement or service

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: INEGI. Constructed from the 100% microdata file

SAMPLE DESIGN: Systematic sample of private dwellings. Geographically sorted by population size (municipality and locality) to increase precision. Samples executed independently for each federal entity.

SAMPLE UNIT: Dwellings

SAMPLE FRACTION: 10%

SAMPLE SIZE (person records): 8,118,242

Mode of data collection

Face-to-face [f2f]

Research instrument

Separate enumeration form for each dwelling

Response rate

UNDERCOUNT: No official estimates

An overview of Xi’an community home care facilities.

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Dwelling

UNITS IDENTIFIED: - Dwellings: No (dwellings in original sample are interpreted as households in IPUMS) - Vacant units: Yes - Households: Yes - Individuals: Yes - Group quarters: Yes

UNIT DESCRIPTIONS: - Households: Structurally independent living quarters, consisting of one or more rooms with a private entrance. - Group quarters: Group living together under relations of administrative subordination.

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: Instituto Brasileiro de Geografia e Estatística

SAMPLE UNIT: Household (called "dwelling" in original sample)

SAMPLE FRACTION: 6.0% (approx.)

SAMPLE SIZE (person records): 10,136,022

Mode of data collection

Face-to-face [f2f]

Response rate

COVERAGE: No official estimates, UNDERCOUNT: No official estimates

In 2022, India overtook China as the world's most populous country and now has almost 1.46 billion people. China now has the second-largest population in the world, still with just over 1.4 billion inhabitants, however, its population went into decline in 2023. Global population As of 2025, the world's population stands at almost 8.2 billion people and is expected to reach around 10.3 billion people in the 2080s, when it will then go into decline. Due to improved healthcare, sanitation, and general living conditions, the global population continues to increase; mortality rates (particularly among infants and children) are decreasing and the median age of the world population has steadily increased for decades. As for the average life expectancy in industrial and developing countries, the gap has narrowed significantly since the mid-20th century. Asia is the most populous continent on Earth; 11 of the 20 largest countries are located there. It leads the ranking of the global population by continent by far, reporting four times as many inhabitants as Africa. The Demographic Transition The population explosion over the past two centuries is part of a phenomenon known as the demographic transition. Simply put, this transition results from a drastic reduction in mortality, which then leads to a reduction in fertility, and increase in life expectancy; this interim period where death rates are low and birth rates are high is where this population explosion occurs, and population growth can remain high as the population ages. In today's most-developed countries, the transition generally began with industrialization in the 1800s, and growth has now stabilized as birth and mortality rates have re-balanced. Across less-developed countries, the stage of this transition varies; for example, China is at a later stage than India, which accounts for the change in which country is more populous - understanding the demographic transition can help understand the reason why China's population is now going into decline. The least-developed region is Sub-Saharan Africa, where fertility rates remain close to pre-industrial levels in some countries. As these countries transition, they will undergo significant rates of population growth

This point shapefile represents the locations of townships with 2000 Population Census Data, 9.95% Long Form data, table L1-L6) for the Qinghai Sheng province of China for 2000. These data are represented at 1:1,000,000 scale. This layer is part of the China 2000 township population census dataset.The 2000 China township maps are developed for matching 2000 China population Census data, which should only be used as references for research or education instead of used as official maps.

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.

A description of the modelling methods used for age and sex structures can be found in "https://pophealthmetrics.biomedcentral.com/articles/10.1186/1478-7954-11-11" target="_blank"> Tatem et al and Pezzulo et al. Details of the input population count datasets used can be found here, and age/sex structure proportion datasets here.
Both top-down 'unconstrained' and 'constrained' versions of the datasets are available, and the differences between the two methods are outlined here. The datasets represent the outputs from a project focused on construction of consistent 100m resolution population count datasets for all countries of the World structured by male/female and 5-year age classes (plus a <1 year class). These efforts necessarily involved some shortcuts for consistency. The unconstrained datasets are available for each year from 2000 to 2020.
The constrained datasets are only available for 2020 at present, given the time periods represented by the building footprint and built settlement datasets used in the mapping.
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/WP00646

Allopatric divergence is often initiated by geological uplift and restriction to sky-islands, climate oscillations, or river capture. However, it can be difficult to establish which mechanism was the most likely to generate the current phylogeographic structure of a species. Recently, genomic data in conjunction with a model testing framework have been applied to address this issue in animals. To test whether such an approach is also likely to be successful in plants we used population genomic data of the Rheum palmatum complex from the Eastern Asiatic Region, in conjunction with biogeographical reconstruction and demographic model selection to identify the potential mechanism(s) which have led to the current level of divergence. Our results indicate that the R. palmatum complex originated in the central Hengduan Mts. and possibly in regions further to the east, and then dispersed westward and eastward resulting in genetically distinct lineages. Populations are likely to have diverged in refugia during climate oscillations followed by subsequent expansion and secondary contact. However, model simulations within the western lineage of the R. palmatum complex cannot reject a restriction to sky-islands as a possible mechanism of diversification due to the genetically ambiguous position of one population. This highlights that genetically mixed populations might introduce ambiguity regarding the best diversification model in some cases. Although it might be possible to resolve this ambiguity using other data, sometimes this could prove to be difficult in complex biogeographic areas.

About this dataset

Context

The dataset tabulates the Champ population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Champ across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2022, the population of Champ was 11, a 0.00% decrease year-by-year from 2021. Previously, in 2021, Champ population was 11, a decline of 0.00% compared to a population of 11 in 2020. Over the last 20 plus years, between 2000 and 2022, population of Champ decreased by 1. In this period, the peak population was 18 in the year 2003. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2022

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2022)
• Population: The population for the specific year for the Champ is shown in this column.
• Year on Year Change: This column displays the change in Champ population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

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/.

Recommended for further research

This dataset is a part of the main dataset for Champ Population by Year. You can refer the same here

This data contains a geospatial population raster layer in GeoTIFF format with 1*1 km resolution for 31 provincial regions (2851 counties) of China in 2018 (pop2018.tif). It also provides the Tencent positioning data in 2018 (TN_hSum2018.tif), the table of statistical population of 2851 counties (statistical_population_2018_china_county.xls) and its vector map (statisitcal_pop.shp) and codes (code.docx).

Population: Household Registration: Male: Shaanxi: Xian data was reported at 5,030.056 Person th in 2022. This records an increase from the previous number of 4,962.121 Person th for 2021. Population: Household Registration: Male: Shaanxi: Xian data is updated yearly, averaging 4,025.200 Person th from Dec 2000 (Median) to 2022, with 23 observations. The data reached an all-time high of 5,030.056 Person th in 2022 and a record low of 3,551.800 Person th in 2000. Population: Household Registration: Male: Shaanxi: Xian data remains active status in CEIC and is reported by Xian Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GE: Population: Prefecture Level City: Household Registration: By Sex.

About this dataset

Context

The dataset tabulates the Eagle Point township population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Eagle Point township across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2022, the population of Eagle Point township was 11, a 0.00% decrease year-by-year from 2021. Previously, in 2021, Eagle Point township population was 11, a decline of 0.00% compared to a population of 11 in 2020. Over the last 20 plus years, between 2000 and 2022, population of Eagle Point township decreased by 22. In this period, the peak population was 33 in the year 2000. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2022

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2022)
• Population: The population for the specific year for the Eagle Point township is shown in this column.
• Year on Year Change: This column displays the change in Eagle Point township population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

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/.

Recommended for further research

This dataset is a part of the main dataset for Eagle Point township Population by Year. You can refer the same here