In 2000, the population grid data of Heihe River Basin was generated based on 1:100000 land use data and population statistics data of each county in 2000. Using principal component analysis and factor analysis, four factors are extracted from 11 regionalization indexes, and the Heihe River Basin is divided into four population distribution characteristic regions by using factor scores for hierarchical clustering. The linear regression model between rural residential land, cultivated land area and rural population is established based on the population statistical data of each county in 2000. The total population of each district and county is controlled. The population coefficient is adjusted according to the principle of different population distribution characteristics. The cultivated land population distribution coefficient is modified in the middle green continent, and the grassland population distribution is increased in the upstream mountainous area and the downstream desert oasis area Coefficient. The spatial distribution of urban population density in river basin is simulated by using the exponential model. Based on the above methods, the population spatial distribution results of 25m grid in Heihe River Basin and the data of 1km grid on scale are finally obtained. At the township level, the accuracy of the results of population spatialization is verified, and compared with the population data of Heihe River Basin estimated by the existing databases (GPW 1995, UNEP / grid1995, landscan 2002 and cn2000pop). The results show that the methods and models used in this study can obtain more accurate spatial distribution data of population in the basin.
WANG Xuemei, MA Mingguo
The data set is the population data of countries along the "One Belt And One Road" from 1960 to 2017. Population is a social entity with complex contents and a variety of social relations. It has gender, age and natural composition, as well as a variety of social composition and social relations, as well as economic composition and economic relations. The birth, death and marriage of population are in family relations, ethnic relations, economic relations, political relations and social relations. All social activities, social relations, social phenomena and social problems are related to the process of population development. In the coordinated development of "One Belt And One Road" China and other countries, it can provide important references for the planning and implementation of national policies and programs, thus accelerating the economic development of all countries.
YIN Jun
This set of data mainly includes the demographic data of 12 counties in 6 prefecture-level cities of Qinghai, Gansu and Inner Mongolia in Heihe River Basin, covering the time period of 2000-2009. The data source is the local statistical yearbook, which mainly includes: Statistical Bureau of Suzhou District. Statistical Yearbook of Suzhou. 2004-2009; Yumen Statistical Bureau. Yumen Statistical Yearbook. 2000-2008; Jinta County Statistical Bureau. Jinta County Statistical Yearbook. 2004-2009; Gaotai Statistical Bureau. Gaotai Statistical Yearbook. 2000-2007; Shandan County Statistical Bureau. Shandan County Statistical Yearbook. 2000-2009; Sunan Yugur Statistical Bureau. Statistical Yearbook of Sunan Yugur Autonomous County. 2004-2009; Minle County Statistical Bureau. Minle County Statistical Yearbook. 2004-2009; Shandan County Statistical Bureau. Shandan County Statistical Yearbook. 2000-2009; Linze County Statistical Bureau. Linze County Statistical Yearbook. 2000-2009; Ejin Banner Statistical Bureau. Ejin Banner Statistical Yearbook. 1990-2005; Qilian County Statistical Bureau. Qilian County National Economic Statistics. 2004-2009; Part of the data of Zhangye City comes from the basic social and economic situation of townships of Zhangye City in 2005. Data of Jiayuguan City is derived from the CNKI statistical data database of China National Knowledge Infrastructure, and only contains some county-level data. Data Content Description: The data mainly includes three population indicators of 12 counties in the basin, including Ganzhou District, Gaotai County, Shandan County, Minle County, Linze County, Sunan Yugur Autonomous County, Jinta County, Sunzhou District and Yumen City, Jiayuguan City, Qilian County, and Ejin Banner. The population indicators are permanent population, agricultural population and non-agricultural population at the end of the year. It is divided into two levels: county level and township level. The statistics currently available are: County level: Ejina Banner: 2006-2009: resident population, agricultural population, non-agricultural population at the end of each year Ganzhou District: 2009: agricultural population, non-agricultural population of the year; Gaotai County: 2009: agricultural population, non-agricultural population of the year; Sunan: 2000-2009: permanent population, agricultural population, non-agricultural population at the end of each year; Minle County: 2009: permanent population, agricultural population, non-agricultural population at the end of the year; Linze: 2009: permanent population, agricultural population, non-agricultural population at the end of the year; Yumen City: 2000-2005: permanent population, agricultural population, non-agricultural population at the end of each year; Township level: Ejin Banner: 2000-2005: permanent population, agricultural population, non-agricultural population at the end of the year; Ganzhou District: 2000-2008: permanent population, agricultural population, non-agricultural population at the end of the year; 2009: resident population at the end of the year; Gaotai County: 2000-2004, 2006, 2007: permanent population, agricultural population, non-agricultural population at the end of the year; 2009: resident population at the end of the year; Shandan County: 2000-2007: permanent population, agricultural population, non-agricultural population at the end of the year; 2009: resident population at the end of the year; Minle County: 2000-2008: permanent population, agricultural population, non-agricultural population at the end of the year; Jinta County: 2004-2009: permanent population, agricultural population, non-agricultural population at the end of the year; Yumen City: 2006-2008: permanent population, agricultural population, non-agricultural population at the end of the year; Suzhou District 2004-2009: permanent population, agricultural population, non-agricultural population at the end of the year; Qilian County: 2004-2009: permanent population, agricultural population, non-agricultural population at the end of the year; Permanent population at the end of the year, agricultural population, non-agricultural population County level township level county level township level county level township level Ejin Banner:2006-2009 2000-2005 2006-2009 2000-2005 2006-2009 2000-2005 Ganzhou District 2000-2009 2009 2000-2008 2009 2000-2008 Gaotai County 2000-2004、 2006、2007、2009 2009 2000-2004、 2006、2007 2009 2000-2004、 2006、2007 Shandan County 2000-2007、2009 2000-2007 2000-2007 Sunan County 2000-2009 2000-2009 2000-2009 Minle County 2009 2000-2008 2009 2000-2008 2009 2000-2008 Linze County 2009 2009 2009 Jinta County 2004-2009 2004-2009 2004-2009 Sunzhou District 2004-2009 2004-2009 2004-2009 Qilian County 2004-2009 2004-2009 2004-2009 Yumen City 2000-2005 2006-2008 2000-2005 2006-2008 2000-2005 2006-2008
ZHAO Jun
The data set records the population of ethnic minorities in Qinghai province from 1952 to 2019. The data is divided by the total population of ethnic minorities, Tibetan, Hui, Tu, Salar, Mongolian and other ethnic groups, and the proportion of the total population in the province. The data are collected from qinghai Statistical Yearbook released by Qinghai Provincial Bureau of Statistics. The dataset contains 22 data tables, which are: Population of ethnic minorities in the province, 1952-1998. XLS Population of ethnic minorities in the province, 1952-1999. XLS Population of ethnic minorities in The province, 1952-2000. XLS Population of ethnic minorities in the province, 1952-2001. XLS Population of ethnic minorities 1952-2002. XLS Population of ethnic minorities 1952-2003. XLS Population of ethnic minorities in main years 1952-2004. XLS Population of ethnic minorities in main years 1952-2006. XLS Population of ethnic minorities in main years 1952-2008. XLS Population of ethnic minorities in main years 1952-2009. XLS Population of ethnic minorities in main years 1982-2010. XLS Population of ethnic minorities in main years 1985-2007. XLS Population of ethnic minorities in main years 1990-2005. XLS Population of ethnic minorities in main years 2000-2011. XLS Population of ethnic minorities in main years 2006-2013. XLS Population of ethnic minorities in main years 2006-2014. XLS Population of ethnic minorities in main years 2006-2015. XLS Population of ethnic minorities in main years 2006-2016. XLS Population of ethnic minorities in main years 2006-2019. XLS Population of ethnic minorities in main years 2005-2012. XLS Population of ethnic minorities, 2006-2017. XLS Population of ethnic minorities, 2006-2018. XLS data table structure is the same. For example, the data table of the population of ethnic minorities in the province from 1952 to 1998 has 8 fields: Field 1: ethnic group Field 2:1952 Field 3:1978 Field 4:1982 Field 5:1990 Field 6:1996 Field 7:1997 Field 8:1998
Qinghai Provincial Bureau of Statistics
The data set records the total socio-demographic data of five central Asian countries from 1991 to 2017.Population indicators including annual population, estimated life expectancy, total fertility rate (1000 people), and total mortality (1000 people), infant mortality, maternal mortality, the total marriage rates, the overall divorce rate, migration of all flow balance, the number of medical institutions, hospital beds (m), the number of preschool institutions (a), kindergarten school student number (m) number, number of middle school, high school students (m), the number of the university, the number of students, institutions of higher learning, the number of students of institutions of higher learning.The data are from the statistical yearbooks of five central Asian countries.
HUANG Jinchuan, MA Haitao
This data set contains statistical tables on the community situation of each county in Three-River-Source National Park. The specific contents include: Table 1 includes: number of administrative villages, number of natural villages, number of households, population, number of rural labor force, total value of primary and secondary industries, net income per capita, and number of livestock. Table 2 includes: the ethnic composition of the population (population of each ethnic group), education-related statistics (number of primary and secondary schools and number of students), health-related statistics (number of hospitals, health rooms and medical personnel), and statistics on the education level of the population (number of people with different education levels); Table 3 includes: the grassland (total grassland area, usable grassland area, moderately degraded area and grassland vegetation coverage), woodland (total area, arbor forest area, shrub forest area and sparse forest area), water area (total area, river area, lake area, glacier area, snowy mountain area and wetland area). A total of four counties were designed: Maduo, Qumalai, Zaduo and Zhiduo. This data comes from statistics of government departments.
National Bureau of Statistics
This dataset is the population index, which includes the dataset of Qinghai Province and Tibet Autonomous Region. It can be used for the coupling coordination relationship between urbanization and eco-environment in Qinghai-Tibet Plateau. The time span in Tibet Autonomous Region is 1995-2016. Permanent residents is based on the population census and the annual population change sampling survey. In addition to the total permanent population, the data were also calculated by gender and urban and rural areas. The time span is from 1952 to 2015 in Qinghai Province, and the indices are resident population, birth, death and natural increase. All data is from the statistical yearbook.
DU Yunyan
The population data of Zhangye City from 2001 to 2012 include: annual population density and natural population growth rate, Data source: Statistical Bureau of Zhangye City. Statistical yearbook of Zhangye City. 2001-2012, Department of water resources of Gansu Province. Bulletin of water resources of Gansu Province. 2001-2012. Water Affairs Bureau of Zhangye City. Comprehensive annual report of water resources of Zhangye City, 1999-2011
ZHANG Dawei
This data set includes the urban distribution, urban population and built-up areas of the Qinghai Tibet Plateau from 2000 to 2015. The urban distribution data is the county-level vector boundary in 2015, and the urban population and built-up area data years are 2000, 2005, 2010 and 2015. Among them, the data of urban distribution and built-up areas are from the research team of Kuang Wenhui, Professor of Institute of geography and resources, Chinese Academy of Sciences, and the data of urban population are from the census data of each year, the statistical yearbook of each province in the Qinghai Tibet Plateau, etc. The data quality is excellent, which can be used to analyze the population growth trend, urban expansion and the impact of human activities on the surrounding environment of cities and towns in the Qinghai Tibet Plateau.
KUANG Wenhui
The data set contains three tables: demographic data for Tibet, demographic data for each county in Tibet, and data on rural workers. These time series data include the year-end total population, the number of men, the number of women, urban population, rural population, and statistics on workers in various rural industries in Tibet from 1967 to 2016. The data were derived from the Tibet Society and Economics Statistical Yearbook and Tibet Statistical Yearbook. The accuracy of the data is consistent with that of the statistical yearbooks. Table 1: The table of demographic data for Tibet contains 10 fields. Field 1: Year Field 2: Year-end total population, unit: 10,000 Field 3: Total number of men, unit: 10,000 Field 4: Male proportion, unit: % Field 5: Total number of women, unit: 10,000 Field 6: Female proportion, unit: % Field 7: Urban population, unit: 10,000 Field 8: Urban population proportion, unit: % Field 9: Rural population, unit 10,000 Field 10: Rural population proportion, unit: %. Table 2: The table of demographic data for each county contains 7 fields. Field 1: Districts and counties Field 2: Year Field 3: Year-end total number of households Field 4: Number of rural households Field 5: Year-end total population, unit: 10,000 Field 6: Rural population, unit: 10,000 Field 7: Year-end number of workers, unit: 10,000 Table 3: The table of rural workers contains 7 fields Field 1: Year Field 2: Districts and counties Field 3: Number of rural workers Field 4: Number of workers in the agricultural, forestry, animal husbandry and fishery sectors Field 5: Number of workers in the industrial sector Field 6: Number of workers in the construction sector Field 7: Number of other non-agricultural workers
Tibet Autonomous Region Provincial Bureau of Statistics
According to the characteristics of the Qinghai Tibet Plateau and the principles of scientificity, systematization, integrity, operability, measurability, conciseness and independence, the human activity intensity evaluation index system suitable for the Qinghai Tibet Plateau has been constructed, which mainly includes the main human activities such as agricultural and animal husbandry activities, industrial and mining development, urbanization development, tourism activities, major ecological engineering construction, pollutant discharge, etc, On the basis of remote sensing data, ground observation data, meteorological data and social statistical yearbook data, the positive and negative effects of human activities are quantitatively evaluated by AHP, and the intensity and change characteristics of human activities are comprehensively evaluated. The data can not only help to enhance the understanding of the role of human activities in the vegetation change in the sensitive areas of global change, but also provide theoretical basis for the sustainable development of social economy in the Qinghai Tibet Plateau, and provide scientific basis for protecting the ecological environment of the plateau and building a national ecological security barrier.
ZHANG Haiyan, XIN Liangjie, FAN Jiangwen, YUAN Xiu
"Total population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship. The values shown are midyear estimates.This dataset includes demographic data of 22 countries from 1960 to 2018, including Sri Lanka, Bangladesh, Pakistan, India, Maldives, etc. Data fields include: country, year, population ratio, male ratio, female ratio, population density (km). Source: ( 1 ) United Nations Population Division. World Population Prospects: 2019 Revision. ( 2 ) Census reports and other statistical publications from national statistical offices, ( 3 ) Eurostat: Demographic Statistics, ( 4 ) United Nations Statistical Division. Population and Vital Statistics Reprot ( various years ), ( 5 ) U.S. Census Bureau: International Database, and ( 6 ) Secretariat of the Pacific Community: Statistics and Demography Programme. Periodicity: Annual Statistical Concept and Methodology: Population estimates are usually based on national population censuses. Estimates for the years before and after the census are interpolations or extrapolations based on demographic models. Errors and undercounting occur even in high-income countries. In developing countries errors may be substantial because of limits in the transport, communications, and other resources required to conduct and analyze a full census. The quality and reliability of official demographic data are also affected by public trust in the government, government commitment to full and accurate enumeration, confidentiality and protection against misuse of census data, and census agencies' independence from political influence. Moreover, comparability of population indicators is limited by differences in the concepts, definitions, collection procedures, and estimation methods used by national statistical agencies and other organizations that collect the data. The currentness of a census and the availability of complementary data from surveys or registration systems are objective ways to judge demographic data quality. Some European countries' registration systems offer complete information on population in the absence of a census. The United Nations Statistics Division monitors the completeness of vital registration systems. Some developing countries have made progress over the last 60 years, but others still have deficiencies in civil registration systems. International migration is the only other factor besides birth and death rates that directly determines a country's population growth. Estimating migration is difficult. At any time many people are located outside their home country as tourists, workers, or refugees or for other reasons. Standards for the duration and purpose of international moves that qualify as migration vary, and estimates require information on flows into and out of countries that is difficult to collect. Population projections, starting from a base year are projected forward using assumptions of mortality, fertility, and migration by age and sex through 2050, based on the UN Population Division's World Population Prospects database medium variant."
DONG Wen
This data set contains demographic structure and quantity statistics of Qinghai from 1952 to 2016. The data were derived from the Qinghai Society and Economics Statistical Yearbook and Qinghai Statistical Yearbook. The accuracy of the data is consistent with that of the statistical yearbooks. Table 1: The table of rural grassroots organizations contains 10 fields. Field 1: Year of the data Field 2: Number of townships and towns Field 3: Number of townships Field 4: Number of towns Field 5: Number of villagers’ committees Field 6: Number of households in rural areas, unit: 10,000 Field 7: Population of rural areas, unit: 10,000 Field 8: Number of workers in rural areas, unit: 10,000 Field 9: Number of male workers, unit: 10,000 Field 10: Number of female workers, unit: 10,000 Table 2: The table of demographic statistics in Qinghai contains 8 fields. Field 1: Year of the data Field 2: Total population Field 3: Male population, unit: 10,000 Field 4: Female population, unit: 10,000 Field 5: Urban population, unit: 10,000 Field 6: Rural population, unit: 10,000 Field 7: Agricultural population, unit: 10,000 Field 8: Non-agricultural population, unit: 10,000 Table 3: The table describing the structure of rural workers contains 9 fields. Field 1: Year of the data Field 2: Number of workers in agricultural, forestry, animal husbandry and fishery sectors, unit: 10,000 Field 3: Number of workers in industry, unit: 10,000 Field 4: Number of workers in the construction sector, unit: 10,000 Field 5: Number of workers in the transportation, storage industry and post trade sectors, unit: 10,000 Field 6: Number of workers in the information industry, unit: 10,000 Field 7: Number of workers in commerce, unit: 10,000 Field 8: Number of workers in the accommodation and catering industry, unit: 10,000 Field 9: Number of workers in other industries Table 4: The table of demographic statistics for each county contains 9 fields. Field 1: Districts and counties Field 2: Year Field 3: Year-end total household number Field 4: Rural household number Field 5: Year-end total population Field 6: Rural total population Field 7: Year-end workers Field 8: Rural workers Field 9: Agriculture, forestry, animal husbandry and fishery
Qinghai Provincial Bureau of Statistics
By applying Supply-demand Balance Analysis, the water resource supply and demand of the whole river basin and each county or district were calculated, based on which the vulnerability of the water resources system of the basin was evaluated. The IPAT equation was used to set a future water resource demand scenario, setting variables such as future population growth rate, economic growth rate, and unit GDP water consumption to establish the scenario. By taking 2005 as the base year and using assorted forecasting data of population size and economic scale, the future water demand scenarios of various counties and cities from 2010 to 2050 were forecast. By applying the basic structure of the HBV conceptual hydrological model of the Swedish Hydrometeorological Institute, a model of the variation tendency of the basin under climate change was designed. The glacial melting scenario was used as the model input to construct the runoff scenario under climate change. According to the national regulations of the water resources allocation of the basin, a water distribution plan was set up to calculate the water supply comprehensively. Considering of the supply and demand situation, the water resource system vulnerability was evaluated by the water shortage rate. By calculating the (grain production) land pressure index of the major counties and cities in the basin, the balance of supply and demand of land resources under the climate change, glacial melt and population growth scenarios was analyzed, and the vulnerability of the agricultural system was evaluated. The Miami formula and HANPP model were used to calculate the human appropriation of net primary biomass and primary biomass in the major counties and cities for the future, and the vulnerability of ecosystems from the perspective of supply and demand balance was assessed.
YANG Linsheng, ZHONG Fanglei
Gridded population with 100m spaital resolution of the 34 key areas along One Belt One Road in 2015, which indicates that the population count per pixel (i.e., grid). This data is derived from geodata institute of Southampton University, UK. The prejection transform and extraction processes were done to generate the gridded population with 100m spaital resolution of the 8 key areas along One Belt One Road in 2015. The original gridded popution is spatially downscaled from census data and multisource data by the random forest method. Accurate population data at finer scale are fundamental for a broad range of applications by governments, nongovernmental organizations, and companies, including the urban planing, election, risk estimation, disaster rescue, disease control, and poverty reduction.
GE Yong, LING Feng
This data is the distribution data of the prehistoric era sites on the Qinghai-Tibet Plateau and surrounding areas, which is derived from the Supplementary Maps of the paper: Chen, F.H., Dong, G.H., Zhang, D.J., Liu, X.Y., Jia, X., An, C.B., Ma, M.M., Xie, Y.W., Barton, L., Ren, X.Y., Zhao, Z.J., & Wu, X.H. (2015). Agriculture facilitated permanent human occupation of the Tibetan Plateau after 3600 BP. SCIENCE, 347, 248-250. The Qinghai-Tibet Plateau, with an average altitude of more than 4000m, is the highestand largest plateau all around the world, and also is one of the most unsuitable areas for human life with long-term on the earth. The remains at the archaeological site are direct evidences left behind the ancient human activities. The original data of this data is digitized from the results of the Qinghai-Tibet Plateau high-textual census and archaeological survey (Qinghai Volume and Tibet Volume of the Chinese Cultural Relics Atlas). The map was digitized mainly based on the distribution maps of the sites, and the latitude and longitude coordinates and altitude were obtained. a total of 6,950 sites, most of which are distributed in the northern part of the plateau. The age range of the site is between 7000BP and 2300BP. This data set is of reference value for the research on the process and power of human diffusion to the Tibetan Plateau in the prehistoric era and other studies related to human activities in the Tibetan Plateau and the prehistoric era.
DONG Guanghui , LIU Fengwen
The data includes 30 items of data in four categories: basic information, comprehensive economy, agriculture and industry, education, health and social security in Qinghai Province and Tibet Autonomous Region. It covers the basic data reflecting human activities, such as population, employees, industrial output value, agricultural machinery power, facility agriculture, etc. of the main county administrative units of the Qinghai Tibet Plateau. The data are sorted out according to the statistical yearbook data of China's counties from 2001 to 2018. For the convenience of application, the data of Qinghai and Tibet are independently tabulated and included in the data of each year. The data can be used to analyze human activities and social and economic development in the county, as well as agricultural and rural development and change process.
The data set includes: population and GDP data of the arctic (1990-2015) and county-level population and GDP data of the third pole region (gansu, qinghai and Tibet) (1970-2016). Socio-economic statistical attributes include: population (ten thousand), GDP (ten thousand yuan), total industrial and agricultural output (ten thousand yuan), total agricultural output (ten thousand yuan), and total industrial output (ten thousand yuan). The arctic population data are mainly derived from the world populationProspects: 2017 revision by the Department of economic and social affairs, which divides the total population by region and country. The data of the third pole mainly refer to the statistical yearbook of gansu province, qinghai province and Tibet autonomous region.County records of gansu, qinghai and Tibet autonomous regions.
Department of Economic and Social Affairs, National Bureau of Statistics, Qinghai Provincial Bureau of Statistics
It is summarized that the agricultural and socio-economic status of the five Central Asian countries (Kazakhstan, Kyrgyzstan, Tajikistan, Uzbekistan and Turkmenistan) in 2016. This data comes from the statistical yearbook of five Central Asian countries, including six elements: total population, cultivated land area, grain production area, GDP, proportion of agricultural GDP to total GDP, proportion of industrial GDP to total GDP, and forest area. Detailed statistics of the six socio-economic elements of the five Central Asian countries. It can be seen from the statistics that there are different emphases among the six elements of the five Central Asian countries. This data provides basic data for the project, facilitates the subsequent analysis of the ecological and social situation in Central Asia, and provides data support for the project data analysis.
LIU Tie
The socio-economic development data set of Qilian mountain basin includes the socio-economic development indicators of 5 prefecture level cities and 14 districts and counties in 1949-2015, such as industrial structure, population scale, labor force, employment, etc. They are the data subsets of social and economic development of prefecture level cities in Qilian mountain basin and county level cities in Qilian mountain basin. The data comes from Gansu statistical yearbook, Gansu Development Yearbook, Qinghai statistical yearbook, Qinghai national economic and social development statistical bulletin, national agricultural product cost and income data compilation, Xining statistical yearbook. As the data source is the provincial and Municipal Statistical Yearbook published publicly, the data has not been cross verified, and the data consistency test and accuracy verification need to be carried out in the process of data analysis and application. The data set is a macro data set reflecting the social and economic development of Qilian mountain basin, with full coverage and long time series. It can provide basic information for the changes of social and economic development of Qilian mountain basin.
WU Feng
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