In 2023, approximately 127.1 million people lived in Guangdong province in China. That same year, only about 3.65 million people lived in the sparsely populated highlands of Tibet. Regional differences in China China is the world’s most populous country, with an exceptional economic growth momentum. The country can be roughly divided into three regions: Western, Eastern, and Central China. Western China covers the most remote regions from the sea. It also has the highest proportion of minority population and the lowest levels of economic output. Eastern China, on the other hand, enjoys a high level of economic development and international corporations. Central China lags behind in comparison to the booming coastal regions. In order to accelerate the economic development of Western and Central Chinese regions, the PRC government has ramped up several incentive plans such as ‘Rise of Central China’ and ‘China Western Development’. Economic power of different provinces When observed individually, some provinces could stand an international comparison. Jiangxi province, for example, a medium-sized Chinese province, had a population size comparable to Argentina or Spain in 2023. That year, the GDP of Zhejiang, an eastern coastal province, even exceeded the economic output of the Netherlands. In terms of per capita annual income, the municipality of Shanghai reached a level close to that of the Czech Republik. Nevertheless, as shown by the Gini Index, China’s economic spur leaves millions of people in dust. Among the various kinds of economic inequality in China, regional or the so-called coast-inland disparity is one of the most significant. Posing as evidence for the rather large income gap in China, the poorest province Heilongjiang had a per capita income similar to that of Sri Lanka that year.

This statistic shows the population density in urban areas of China in 2023, by region. In 2023, cities in Heilongjiang province had the highest population density in China with around ***** people living on one square kilometer on average. However, as the administrative areas of many Chinese cities reach beyond their contiguous built-up urban areas - and this by varying degree, the statistical significance of the given figures may be limited. By comparison, the Chinese province with the highest overall population density is Jiangsu province in Eastern China reaching about 7956 people per square kilometer in 2023.

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.

Data and Code for Prediction of the COVID-19 Epidemic Trends Based on SEIR and AI Models.Data include the number of confirmed cases of COVID-19, local population density, capital GDP, distance to Wuhan, average annual temperature, average annual rainfall of Chinese provinces (Except for Hong Kong, Macao and Taiwan) and migration population in Wuhan. Code include SEIR, DNN, RNN for prediction.

This polygon shapefile represents provincial boundaries of China for 2010. This layer is part of the 2010 China Province Population Census Dataset. These data were primarily based on the "The Administrative Maps of the People's Republic of China, published by China Map Press.

Notes from product: II. Notes on China 2000 and 2010 Population Census Data In order to guide you to use the data correctly, provide you some explanations as follows: (l) Census time: 0:00AM of November 1, 2000 and 2010 as the reference time for the census. (2) The 2000 and 2010 population census covered all persons who hold the nationality of, and have permanent residing place in the People's Republic of China. During the census, each person was enumerated in his/her permanent residing place. The following persons should be enumerated in their permanent residing place: a) Those who reside in the townships, towns and street communities and have their permanent household registration there. b) Those who have resided in the townships, towns and street communities for more than 6 months but the places of their permanent household registration are elsewhere. c) Those who have resided in the townships, towns and street communities for less than 6 months but have been away from the place of their permanent household registration for more than 6 months. d) Those who live in the townships, towns and street communities during the population census while the places of their household registration have not yet settled. e) Those who used to live in the townships, towns and street communities but are working or studying abroad during the census and have no Permanent household registration for the time being. (3) Two types of questionnaires (long form and short form) were used for the 2000 and 2010 population census. The short form contains items that reflect the basic situation of the population, while the long form include all short form items plus other items such as migration, education, economic activities, marriage and family, fertility , housing , etc. . According to the National Bureau of Statistics of China, the households for the Long Form survey were selected by a random sampling program. The data included in this product are from 100% Short Form survey.(4) Results in this publication are based on the processing of data directly from enumeration without any adjustment. It is therefore worthwhile to notice the following: a. Data in the publication do not include population not enumerated in the Census. b. Data in the publication do not include the servicemen of the People's Liberation Army. c. The post-enumeration sample survey indicates an undercount of 1.81% in 2000 Census and 0.12% in 2010 Census. III. Notes on the China Province GIS Maps for the 2000 and 2010 Population Census Data (1) The China Province GIS map were developed for the 2000 and 2010 population Census data, which covered all 31 municipalities, provinces and autonomous regions of China, except for Taiwan, Hong Kong and Macao. (2) The population data came from the 5th and 6th China Population Census surveyed in 2000 and 2010. The GIS data is based on the national digital map (1:1 million) developed by the National Geographic Information Center of China (NGCC), including rives, roads, residential area and administrative boundaries.(3) The China province GIS maps are developed for matching 2000 and 2010 China population Census data, which should only be used as references for research or education instead of used as official maps. The distributor is not responsible for the accuracy of the those maps if the maps are used for business or other purposes.

Panel data of indicators in 30 provinces of China from 2000 to 2021, including: resident population, gross domestic product, transportation industry output value, transportation energy consumption, passenger/goods turnover, etc., a total of 18 indicators.

The GIS map layer include the province map with comparable variables from 2000 and 2010 population Census data.

Population: This dataset contains 65-years’ time serial data of whole China (unit: million persons), each provinces (unit: 10000 persons), and each county. The source data are originally collected from China Statistical Yearbook from 1949 to 2013. The county data covers 2000, 2006, 2007, and 2009. In addition, 4 years (1995, 2000, 2005, 2010) population distributions cover the whole land region in China are also included in this dataset. Such data is expressed as raster format with 1 km resolution and a projection of Albers. Attribute information mainly includes population density (unit: number of person per square kilometer). The source data are originally provided by Data Center for Resources and Environmental Sciences, Chinese Academy of Sciences (RESDC) (http://www.resdc.cn) and Data Sharing Infrastructure of Earth System Science (http://www.geodata.cn).These data are not intended for demarcation.

This dataset is about cities in China. It has 748 rows. It features 3 columns: country, and population.

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.

Social pull-push factors mainly fall into six categories: food, traffic, education, technology, health and medical conditions and human living conditions. Indicators of total grain product (Million tons), number of health agencies (units), number of beds in health care agencies (1000 beds), length of railways (10000 km), length of highways (10000 km), length of navigable inland waterways (10000 km), number of regular primary schools (units), number of higher education institutions (units), number of patent applications (units), per capita annual income of urban households (yuan), per capita annual income of rural households (yuan), Engel's coefficient of urban households (-), Engel's coefficient of rural households(-).Time serial data from 1949 to 2013 of whole China and all the provinces are included. All of data were collected from the China Statistical Yearbook from 1981 to 2014 and China Compendium of Statistics from 1949 to 2008.These data are not intended for demarcation.

This point shapefile represents the provincial capitals, with 2000 population census data, for the Hebei 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.

About this dataset

Context

This list ranks the 184 cities in the Utah by Chinese 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 Chinese Population: This column displays the rank of city in the Utah by their Chinese population, using the most recent ACS data available.
• City: The City for which the rank is shown in the previous column.
• Chinese Population: The Chinese population of the city is shown in this column.
• % of Total City Population: This shows what percentage of the total city population identifies as Chinese. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Utah Chinese Population: This tells us how much of the entire Utah Chinese 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/.

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

Time period CV values of 31 provinces (municipalities/autonomous regions) in Mainland China.

V1 dataset:Under the global framework of Shared Socioeconomic Pathways (SSPs), based on localized population and economic parameters, a Population Development Environment (PDE) model is adopted to construct population grid data for SSPs from 2020 to 2100; Using the Cobb Douglas model, construct economic data for SSPs from 2020 to 2100.The v1 dataset includes:Population grid data of the world, The Belt and Road region, and China, with a spatial resolution of 0.5°GDP grid data of the world, The Belt and Road region, and China, with a spatial resolution of 0.5 °Grid data on the output value of three industries in the Chinese region, with a spatial resolution of 0.1 °V2 dataset:Based on the data from the 7th National Population Census of China, starting from 2020, the parameters such as fertility rate, mortality rate, migration rate, and education level in the Population Development Environment (PDE) model were updated. Under the Shared Socioeconomic Pathways (SSP1-5), a new version (v2) of the total population and age and gender specific population projection dataset for China and its provinces from 2020 to 2100 was created. Based on the data from the 7th National Population Census and the 4th Economic Census of China, with 2020 as the starting year, the parameters of total factor productivity, capital stock, labor input, and capital elasticity coefficient in the Cobb Douglas model were updated. Under the shared SSP1-5, a new version (v2) of China and its provincial GDP projectiondataset from 2020 to 2100 was created.The v2 (2024 version) dataset includes:Total Population Data of China and Provinces (2020-2100)Population data by age and gender in China (2020-2100)China and Provincial GDP Data (2020-2100)

The age structure of the population in China varies greatly across different regions. In 2023, only around 9.6 percent of the population in Shanghai municipality was aged 14 years or younger, while this share amounted to 24.4 percent in Tibet.

This statistic illustrates the population of the Guangdong - Hong Kong - Macao Greater Bay Area cities in 2024. That year, the population of Guangzhou amounted to approximately ***** million people, making it the largest city by population in the region.

The population proportion in the provinces of western China residing in potential high-risk areas.