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 **** million inhabitants and was forecasted to reach around ***** million by 2020.

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: Usual Residence: Birth Rate: Shaanxi: Xian data was reported at 8.220 ‰ in 2023. This records a decrease from the previous number of 8.320 ‰ for 2022. Population: Usual Residence: Birth Rate: Shaanxi: Xian data is updated yearly, averaging 9.855 ‰ from Dec 2000 (Median) to 2023, with 24 observations. The data reached an all-time high of 13.070 ‰ in 2000 and a record low of 7.390 ‰ in 2001. Population: Usual Residence: Birth 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: Usual Residence: Natural Growth Rate. Birth rate,death rate and natural growth rate of population are estimated by Xi'an Bureau of Statistics on the basis of population censuses, the one percent sample survey on population, or annual sample surveys on population changes.

In 2021, around **** 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 **** 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 **** million in 2020, a nearly ** 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 ****** 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 ** and ** million, respectively, before 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.

Historical dataset of population level and growth rate for the Xian, Shaanxi, China metro area from 1950 to 2025.

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.

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 2022, the population of Cottonwood was 11, a 0.00% decrease year-by-year from 2021. Previously, in 2021, Cottonwood population was 11, an increase of 10.00% compared to a population of 10 in 2020. Over the last 20 plus years, between 2000 and 2022, population of Cottonwood increased by 5. In this period, the peak population was 11 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 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 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: Gaoling data was reported at 388.430 Person th in 2023. This records an increase from the previous number of 382.741 Person th for 2022. Population: Shaanxi: Xian: Gaoling data is updated yearly, averaging 326.175 Person th from Dec 2004 (Median) to 2023, with 20 observations. The data reached an all-time high of 388.430 Person th in 2023 and a record low of 234.000 Person th in 2004. Population: Shaanxi: Xian: Gaoling 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

1 Including NDVI data and LST data of Guanzhong region of China from 2001 to 2018, in TIF format.2 Including DEM; River; Pop ; GDP Traffic; City; Urbanization rate; Tourist AttractionsThe present study obtained data for NDVI from the MOD13A2 dataset of the United States Geological Survey (USGS) network (https://lpdaac.usgs.gov/) with a spatial resolution of 1,000 m. Data for population were obtained from the China Population Distribution Kilometer Grid Dataset of the Resource and Environmental Science Data Center of the Chinese Academy of Sciences (http://www.resdc.cn/). GDP data were obtained from the GDP China Spatial Distribution Kilometer Grid Dataset of the Resource and Environmental Science Data Center of the Chinese Academy of Sciences. Data for the transport network in the present study included national highway, provincial highway, county roads, and railway data. Population data used in the present study included data for residents of the municipal areas of Xi’an, Baoji, Xianyang, Tongchuan, and Weinan, as well as national-level population data. Vector data were obtained from the National Basic Geographic Information Center. Data for the distribution of popular tourist natural attractions were obtained the Department of Culture and Tourism, Shaanxi Province, including the 4A- and 5A-level natural tourist attractions, and were for the period prior to January, 2018. Data for rates of urbanization were obtained from statistical yearbooks of cities and counties.

This polygon dataset represents county boundaries and population data in China from the 2000 Census. This dataset also includes detailed demographic data such as: sex and age statistics, litteracy, employment, and professions, and birth and death rates. These data were primarily based on the "The Administrative Maps of the People's Republic of China, published by China Map Press.This dataset is intended for researchers, students, and policy makers for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production, or to provide a basemap to support graphical overlays and analysis with other spatial data.Read More

This point shapefile represents the prefecture city locations, with 2000 population census data, for the Jiangsu 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.

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.

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.

This study investigates the alarming rise of urban poverty in China; in particular the patterns of urban poverty and the institutional causes are examined. The researchers look for evidence of institutional innovations that have emerged as individuals and organisations seek to negotiate more secure access to vital civic goods and services. A case study approach was used due to the complexity of the issue and the size of the Chinese urban population. Six cities were chosen and four neighbourhoods in each city were investigated. These cities were distributed in the costal, central and western region respectively, including Guangzhou, Nanjing, Harbin, Wuhan, Kumin, and Xi’an.

Further information is available from the ESRC Award webpage.

The Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11 consists of estimates of human population density (number of persons per square kilometer) based on counts consistent with national censuses and population registers, for the years 2000, 2005, 2010, 2015, and 2020.�A proportional allocation gridding algorithm, utilizing approximately 13.5 million national and sub-national administrative Units, was used to assign population counts to 30 arc-second grid cells. The population density rasters were created by dividing the population count raster for a given target year by the land area raster. The data files were produced as global rasters at 30 arc-second (~1 km at the equator) resolution. To enable faster global processing, and in support of research commUnities, the 30 arc-second count data were aggregated to 2.5 arc-minute, 15 arc-minute, 30 arc-minute and 1 degree resolutions to produce density rasters at these resolutions.

An overview of Xi’an community home care facilities.

The world's population first reached one billion people in 1803, and reach eight billion in 2023, and will peak at almost 11 billion by the end of the century. Although it took thousands of years to reach one billion people, it did so at the beginning of a phenomenon known as the demographic transition; from this point onwards, population growth has skyrocketed, and since the 1960s the population has increased by one billion people every 12 to 15 years. The demographic transition sees a sharp drop in mortality due to factors such as vaccination, sanitation, and improved food supply; the population boom that follows is due to increased survival rates among children and higher life expectancy among the general population; and fertility then drops in response to this population growth. Regional differences The demographic transition is a global phenomenon, but it has taken place at different times across the world. The industrialized countries of Europe and North America were the first to go through this process, followed by some states in the Western Pacific. Latin America's population then began growing at the turn of the 20th century, but the most significant period of global population growth occurred as Asia progressed in the late-1900s. As of the early 21st century, almost two thirds of the world's population live in Asia, although this is set to change significantly in the coming decades. Future growth The growth of Africa's population, particularly in Sub-Saharan Africa, will have the largest impact on global demographics in this century. From 2000 to 2100, it is expected that Africa's population will have increased by a factor of almost five. It overtook Europe in size in the late 1990s, and overtook the Americas a decade later. In contrast to Africa, Europe's population is now in decline, as birth rates are consistently below death rates in many countries, especially in the south and east, resulting in natural population decline. Similarly, the population of the Americas and Asia are expected to go into decline in the second half of this century, and only Oceania's population will still be growing alongside Africa. By 2100, the world's population will have over three billion more than today, with the vast majority of this concentrated in Africa. Demographers predict that climate change is exacerbating many of the challenges that currently hinder progress in Africa, such as political and food instability; if Africa's transition is prolonged, then it may result in further population growth that would place a strain on the region's resources, however, curbing this growth earlier would alleviate some of the pressure created by climate change.

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