The population, grain, grain sown area and year-end data sets are extracted from the provincial and prefecture level statistical yearbooks of Qinghai, Tibet, Xinjiang, Gansu, Sichuan and Yunnan for many consecutive years. The missing data are interpolated as follows: 1. To ensure the accuracy of county data, Some counties and cities have been merged in this data (there may be errors in dividing and imputing the data for 20 years according to the proportion, but there will certainly be no problem in the merger, and the county area is small, so it is merged). 2. Xiahe County and cooperative city are merged into Xiahe County (cooperative city was separated from Xiahe County in 1998). 3. Gucheng district and Yulong County are merged into Gucheng district (Lijiang County was divided into Gucheng district and Yulong County in 2003). 4. The inner city district, East City District, West City District The four districts in Chengbei district have been merged into the district directly under the central government of Xining City (because the population of the four districts is given separately or the sum is given, and the total area of the four districts is only 487 square kilometers, they are merged). 5. For some missing data, curve fitting has been carried out in combination with similar years, and R2 is between 0.85-0.99. 6. In order to ensure the accuracy of the data, change maps have been prepared County by county
ZHANG Lu
The data is 1:250000 socio-economic data of Sichuan Tibet line and surrounding areas, including GDP, population and other data. Population and GDP are one of the important indicators of social and economic development, regional planning and resource and environmental protection. Administrative regions are usually taken as the basic statistical unit. The spatialization of population and GDP replaces the traditional administrative statistics unit with spatial statistics unit, which brings great convenience for data sharing and spatial statistical analysis among multiple fields. The data comes from the kilometer grid data set of China's population and GDP spatial distribution of resource and environmental science and data center. The data set of China's population and GDP spatial distribution kilometer grid of resource and environmental science and data center is cut according to the scope of Sichuan Tibet railway and surrounding areas. The data is in grid format and accurate to every square kilometer. It is applicable to the Sichuan Tibet line and surrounding areas. Population and GDP are one of the important indicators of social and economic development, regional planning and resource and environmental protection.
WANG Zhonggen
The resilience of the growth in the number of children along the Belt and Road reflects the level of resilience of the growth in the number of children in the countries along the Belt and Road, with higher values indicating stronger resilience in the growth of the number of children along the Belt and Road. The data on the resilience of the growth in the number of children and adolescents is prepared by referring to the World Bank's statistical database, using the yearly data on the proportion of children (0-14 years old) in the countries along the Belt and Road from 2000 to 2019, taking into account the yearly changes in each indicator, based on sensitivity and adaptability analysis, and through a comprehensive The product is based on a sensitivity and adaptation analysis, and is based on a comprehensive diagnosis of the resilience of the growth in the number of children. The resilience dataset is an important reference for analysing and comparing the resilience of the growth in the number of children in the countries along the "Belt and Road".
XU Xinliang
The resilience of population growth in countries along the Belt and Road reflects the level of resilience of population growth in the countries along the Belt and Road, and the higher the value of the data, the stronger the resilience of population growth in the countries along the Belt and Road. The World Bank's statistical database was used to prepare the Resilience to Population Growth data product, which uses year-on-year data on the population of countries along the Belt and Road from 2000 to 2019. The Resilience to Population Growth product is based on sensitivity and adaptation analysis. Please refer to the documentation for the methodology of preparing the dataset. "The resilience dataset is an important reference for analysing and comparing the current resilience of population growth in countries along the Belt and Road.
XU Xinliang
The resilience of the population age structure of countries along the Belt and Road reflects the level of resilience of the population age structure of the countries along the Belt and Road, and the higher the value of the data, the stronger the resilience of the population age structure of the countries along the Belt and Road. The World Bank's statistical database was used to prepare the data on the resilience of population age structure, and the data on the proportion of children, the proportion of working-age population and the proportion of elderly population in the countries along the Belt and Road from 2000 to 2019 were used year by year. Based on the sensitivity and adaptability analysis, a comprehensive diagnosis was carried out to produce a resilience product for the age structure of the population. Please refer to the documentation for the methodology of preparing the data set. "The data set is an important reference for analysing and comparing the resilience of population age structures in countries along the Belt and Road.
XU Xinliang
The resilience of population urbanisation development in countries along the Belt and Road reflects the level of resilience of population urbanisation development in the countries along the Belt and Road, with higher values indicating stronger resilience of population urbanisation development in the countries along the Belt and Road. The data on the resilience of population urbanisation development are prepared with reference to the World Bank's statistical database, using year-on-year data on two indicators, namely the number of urban population and the number of population in urban agglomerations with a population of over one million, from 2000 to 2019, and based on sensitivity and adaptability analysis, taking into account the year-on-year changes of each indicator. Based on the sensitivity and adaptability analysis, the product of the resilience of population urbanisation development was prepared through comprehensive diagnosis. "The data set on the resilience of population urbanisation development in the countries along the Belt and Road is an important reference for analysing and comparing the resilience of population urbanisation development in various countries.
XU Xinliang
The data set contains the blood routine and blood biochemical indexes collected from native Tibetans in Lhasa and Nyingchi in Tibet Autonomous Region for four follow-up visits. The project carried out four follow-up surveys in Lhasa and Nyingchi from May to June and September to October 2021, and a total of 212 subjects were recruited. Blood is an important circulating element of human body, which stores the information of human health. Biological samples of subjects were collected at each visit. The professional nurses of Lhasa Second People's Hospital and Nyingchi Jianmin hospital collected 18 ~ 20ml blood samples, and some samples were sent to the hospital for blood routine and blood biochemical analysis. The data can be used to evaluate the health level of permanent residents in Tibet and further analyze the impact of ozone exposure and hypoxia on the health of permanent residents.
GONG Jicheng
The data set contains the systemic inflammatory oxidative stress indexes collected from native Tibetans in Lhasa and Nyingchi in Tibet Autonomous Region for four follow-up visits. The project carried out four follow-up surveys in Lhasa and Nyingchi from May to June and September to October 2021, and a total of 212 subjects were recruited. Biological samples of subjects were collected at each visit. The professional nurses of Lhasa Second People's Hospital and Nyingchi Jianmin hospital collected 18 ~ 20ml blood samples, and some samples were sent to the hospital for analysis. The related indexes of leukocytes such as lymphocytes, basophils, neutrophils, eosinophils and monocytes can reflect the level of systemic oxidative stress inflammation. The data can be used to evaluate the level of systemic inflammatory oxidative stress of native Tibetans in Tibet, and further analyze the effects of ozone exposure and hypoxia on systemic inflammatory oxidative stress of permanent residents.
GONG Jicheng
The data set contains respiratory inflammatory indexes collected from four follow-up visits of native Tibetans in Lhasa and Nyingchi, Tibet Autonomous Region. The project carried out four follow-up surveys in Lhasa and Nyingchi from May to June and September to October 2021, and a total of 212 subjects were recruited. Fractional exhaled nitric oxide (FeNO) is produced by airway cells. Its concentration is highly correlated with the number of inflammatory cells. It is a simple and noninvasive biological index, which can effectively reflect the degree of airway inflammation,. At each visit, about 5 liters of exhaled gas were collected with Teflon air bag, and then the content of nitric oxide (FeNO) in exhaled gas was measured with thermo NOx gas analyzer to characterize the inflammatory level of respiratory system. The data can be used to evaluate the level of respiratory inflammation of native Tibetans in Tibet, and further analyze the effects of ozone exposure and hypoxia on respiratory inflammation of natives.
GONG Jicheng
The data set included lung function and cardiovascular function indexes collected during four follow-up visits to the high altitude natives in Lhasa and Nyingchi, Tibet Autonomous Region. Four follow-up surveys were conducted in Lhasa and Nyingchi from May to June and September to October 2021, and a total of 212 subjects were recruited. During each visit, the forced vital capacity (FVC), forced expiratory volume in one second (FEV1), vital capacity (VC) and other pulmonary function indexes of the subjects were measured by Mir pulmonary function instrument. The heart rate (HR), systolic blood pressure (SBP), diastolic blood pressure (DBP), augmentation index (AIx), carotid femoral pulse wave velocity (cf-PWV) and other cardiovascular function indexes were measured by German vicorder cardiovascular detector. The data can be used to evaluate the cardiopulmonary system function of natives in Tibet, and further analyze the effects of ozone exposure and hypoxia on the cardiopulmonary system function of high altitude natives.
GONG Jicheng
This data uses a landslide hazard risk assessment model consisting of four modules: landslide hazard causative factors, landslide susceptibility model, exposed population and population casualty rate. The module of hazard-causing factors includes DEM, slope, rainfall, temperature, snow cover, GDP, and vegetation cover factors. The landslide hazard susceptibility model is a statistical analysis using a logistic regression model to obtain landslide susceptibility probability values. The population exposure module uses the landslide susceptibility values overlaid with population data. The population casualty rate module is based on the ratio of historical landslide casualties to the population exposed to landslides during the same period. Finally, by substituting the 2020 population data, the exposed population under different levels of landslide hazard susceptibility is calculated and multiplied with the historical period landslide hazard population casualty rate to assessIntegrated multi-hazard population risk in the peri-Himalayan and Asian water tower regions
WANG Ying
Human adaptation to high altitude environment (> 2500m) is an important milestone in the process of human evolution and diffusion. As the highest altitude and largest plateau in the world, the Qinghai Tibet Plateau is an ideal area for human adaptation to extreme hypoxia environment. An early site with continuous strata, the site of jijunbu, was newly discovered on the Bank of Zhuanglang River in Yongdeng County, Gansu Province, northeast of Qinghai Tibet Plateau. A series of samples were taken from the site in 2015 and 2018. The results of photoluminescence dating show that the age of the site is 120-90 Ka, which is the earliest wilderness site on the Qinghai Tibet Plateau, providing new clues for the study of early human activity history and survival adaptation on the Qinghai Tibet Plateau.
ZHANG Dongju
The data set of economic, population, and urbanization growth and change in Qilian mountain area includes the social and economic development indicators of 1949-2020 long-term time series of 5 prefecture-level cities and 14 districts and counties in the Qilian mountain basin, such as the added value of the tertiary industry, population scale, etc. They are the subsets of economic, population, and urbanization growth changes of prefecture-level cities in Qilian mountain and the subsets of county-level economic, population, and urbanization growth changes in Qilian mountain. The data comes from Gansu statistical yearbook, Wuwei statistical bulletin of national economic and social development, Zhangye statistical bulletin of national economic and social development, Jiuquan statistical bulletin of national economic and social development, Jinchang statistical bulletin of national economic and social development, Jiayuguan statistical bulletin of national economic and social development, and social development of Ejina Banner. Since the data source is the publicly released provincial and Municipal Statistical Yearbook, the data has not been cross verified, and the consistency and accuracy of the data need to be verified in the process of data analysis and application. The data set is a macro data set reflecting the growth and change of economy, population, and urbanization in Qilian mountain. It has complete coverage and long-time series. It can provide basic information for the social and economic development and change of Qilian mountain.
WU Feng
Quantitative evaluation and comprehensive measurement of resource and environment carrying capacity is the key technical link of resource and environment carrying capacity research from classification to synthesis. Based on the evaluation of the suitability of human settlements, the limitation of resource carrying capacity and socio-economic adaptability, and according to the research idea and technical route of "suitability zoning restrictive classification adaptability classification warning classification", a three-dimensional tetrahedral model for the comprehensive evaluation of resource and environmental carrying capacity with balanced significance is constructed. Based on the 10km grid, a comprehensive study on the resource and environment carrying capacity was carried out, and the resource and environment carrying capacity index of the areas along the silk road was quantitatively simulated. Taking 1 as the equilibrium significance, it provided support for the comprehensive evaluation of the resource and environment carrying capacity of the areas along the silk road.
YOU Zhen
To investigate the paternal genetic structure of Tibetans, 447 male samples were collected from Ngari (n=211), Chamdo (n=119), and Nyingchi (n=117). Firstly, SNP genotyping was performed to allocate samples into haplogroups. To further evaluate the genetic diversity of the major Y-chromosomal haplogroup in Tibetan populations from Lhasa, eight commonly used Y-chromosomal STR (short tandem repeat) loci (DYS19, DYS388, DYS389I, DYS389II, DYS390, DYS391, DYS392, and DYS393) were genotyped using fluorescence-labeled primers with an ABI 3130XL Genetic Analyzer (Applied Biosystems, USA). The results indicated that haplogroup D displayed highest frequency in these three Tibetan populations (Ngari 54.50%, Nyingchi 64.10%, Chamdo 67.23%). Among haplogroup D, D-P47 showed the highest frequency (Ngari 29.39%, Nyingchi 51.28%, Chamdo 55.46%). Differently, D-N1 showed the highest frequency in Ngari (21.33%), followed by Nyingchi (11.97%) and Chamdo (10.92%). Haplogroup O-M117 is the second frequent haplogroup in these three populations, with the highest frequency in Ngari (29.86%), followed by Nyingchi (26.50%) and Chamdo (15.97%). Compared with the other two populations, Ngari Tibetans have higher frequencies of western Eurasian haplogroups, including R-M17 (1.42%), R-M343 (1.42%), and J, probably reflecting more genetic contribution from the west into Ngari. In combination with the data from Lhasa that deposited in 2019 and 2020, our Y chromosome data of Tibetans from different locations on the Tibetan Plateau will be very helpful to understanding the paternal genetic structure of Tibetans. Moreover, the genetic history of Tibetans can also be dissected by phylogeographic and coalescent analyses.
KONG Qingpeng
The Hindu Kush mountains are tall mountains in Central Asia. The average altitude is about 5000 meters, and the highest peak, tiriqmir peak, is 7690 meters above sea level. It is the watershed between the Indus River in the southwest of the Qinghai Tibet Plateau and the Amu Darya River in the Pamir Plateau. Studying the genetic structure of the population in this area will help to deeply understand the diffusion history of the population and the genetic basis of adapting to the plateau environment. Studying the genetic structure of the population in this area will help to deeply understand the diffusion history of the population and the genetic basis of adapting to the plateau environment. In this study, we studied the maternal genetic structure of 213 individuals from 5 populations distributed in Xingdu Kush mountains. The mitochondrial genome sequences of 213 individuals (average depth > 1000x) were obtained by mitochondrial genome capture library construction and second-generation sequencing (Illumina hiseq x ten platform). Based on the idea of phylogeny, we control the quality of these data to ensure that there are no quality problems such as sample pollution. The modified Cambridge standard sequence was used as a reference for the output of mutation sites. According to the mitochondrial DNA phylogenetic tree (phylotree. ORG) of people around the world, each sample was divided into haplotype groups. Based on the mtDNA data of modern population and ancient samples published in the past, the origin and diffusion history of population in this area were systematically studied. The results show that the main maternal genetic components of Indo European populations in this region come from western Eurasia. Haplotypes w3a1a and j1b1a1 may be related to the migration of Indo European language groups, indicating that the diffusion of Indo European language groups to South Asia may not only be a simple cultural expansion, but also accompanied by the migration of some people. In addition, the study also shows that northern Pakistan may play an important channel role in the diffusion of Indo European languages to South Asia.
KONG Qingpeng
The data is the population and urbanization data of the Qinghai Tibet Plateau. The data are mainly from census data, including 1990, 2000 and 2010. The main data fields include resident population, urban population and urbanization rate of resident population. Under the GIS platform, the spatial database is constructed through the connection of administrative division vector data and population data. Among them, the data quality related to population is accurate to people. The data mainly serve the research on population geography, urbanization and urban development of the Qinghai Tibet Plateau. It is worth noting that the data of resident population and urbanization rate in census years are relatively accurate. With the opening of the data of the seventh census, it will be updated one after another.
QI Wei
The temperature humidity index (THI) was proposed by J.E. Oliver in 1973. Its physical meaning is the temperature after humidity correction. It considers the comprehensive impact of temperature and relative humidity on human comfort. It is an important index to measure regional climate comfort. On the basis of referring to the existing classification standards of physiological and climatic evaluation indexes, combined with the natural and geographical characteristics of the Qinghai Tibet Plateau and facing the needs of human settlements suitability evaluation in the Qinghai Tibet Plateau, the temperature and humidity index and its suitability zoning results of the Qinghai Tibet Plateau (more than 3000 meters) are developed (including unsuitable, critical suitable, general suitable, relatively suitable and highly suitable).
LI Peng, LIN Yumei
This data set records the statistical data of agricultural and animal husbandry scientific and technological talent resources in Qinghai Province, covering the period from 2011 to 2016. The data are divided by animal husbandry and veterinary, planting, fishery, agricultural machinery, land reclamation and other projects. The data set contains six data tables, which are: Statistics of scientific and technological human resources in agriculture and animal husbandry (applicable to extension institutions) (2011), statistics of scientific and technological human resources in agriculture and animal husbandry (applicable to extension institutions) (2012), statistics of scientific and technological human resources in agriculture and animal husbandry (applicable to extension institutions) (2013), statistics of scientific and technological human resources in agriculture and animal husbandry (applicable to extension institutions) (2014), Statistics of agricultural and animal husbandry scientific and technological human resources (applicable to extension institutions) (2015), statistics of agricultural and animal husbandry scientific and technological human resources (applicable to extension institutions) (2016). The data table structure is similar. For example, the statistical table of agricultural and animal husbandry scientific and technological talent resources (applicable to extension institutions) (2011) has five fields: Field 1: number of employees at the end of the year Field 2: number of scientific and technological talents Field 3: Qualification Field 4: Education Field 5: Gender
AGRICULTURAL AND RURAL Department of Qinghai Province
The data set records the basic situation of rural areas in Qinghai Province, including rural households, rural population and other information. The statistical data covers the period from 2014 to 2018. The data are divided into 8 states, cities and 43 counties and districts according to Xining City, Haidong region, Haibei Prefecture, Huangnan Prefecture, Hainan prefecture, Guoluo Prefecture, Yushu prefecture and Haixi Prefecture. The data set contains five data tables, which are: basic rural situation (2014), basic rural situation (2015), basic rural situation (2016), basic rural situation (2017) and basic rural situation (2018). The structures of each data table are similar. For example, the basic rural situation (2014) data sheet has two fields: Field 1: number of rural households Field 2: rural population
AGRICULTURAL AND RURAL Department of Qinghai Province
The Tibetan Plateau has a harsh conditions for human to inhabit. When human beings went into the Tibetan Plateau and how they adapt to the extreme environment have attract broad attention. At present, extensive studies on this issue have been conducted in the northeastern Tibetan Plateau with few work in other regions. There are a lot of archaeological sites in the Yarlung Zangbo River Basin while most of them are lack of cultural layers. Systematic archaeological investigations had been done to 25 cultural layers and 3 tombs in Lhasa and Nyignchi
YANG Xiaoyan, WANG Yanren
Topographic relief is a comprehensive representation of regional altitude and surface cutting degree. Based on the definition and calculation formula of topographic relief under the background of China's human settlements assessment, the digital elevation model (Aster GDEM 30 m) data is resampled into 1 km, The data set includes: (1) kilometer grid spatial data of Tibetan Plateau topographic relief（ 2) Terrain suitability evaluation data of Qinghai Tibet Plateau. The data can be used to analyze the spatial difference of topographic relief of the Qinghai Tibet Plateau, which is of great significance to the study of human settlements and Natural Suitability of the Qinghai Tibet Plateau.
XIAO Chiwei, LI Peng,
The data set includes county-level demographic data of 252 areas in Qinghai-Tibet Plateau in 1982, 1990, 2000, 2010 and 2018, and GDP data in 1988, 1995, 2000, 2010 and 2015. The demographic data includes registered population, resident population, urban population, rural population, male population, female population and non-agricultural population. GDP data includes total GDP output value and GDP output value of primary, secondary and tertiary industries. The data are helpful to study the impact of human activities on the ecological climate of Qinghai-Tibet Plateau, and to explore the urbanization development, urban and rural population mobility, resident population change, local birth rate and agricultural population change in Qinghai-Tibet Plateau. The data were obtained by contacting the local statistics bureau, relevant statistical yearbooks and annual statistical bulletins of various places during the second scientific investigation of Qinghai-Tibet Plateau.
FU Bin
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
This data set records the mechanical changes of population in Qinghai Province from 1952 to 2018. The data is divided by year. The data is the annual report data of the provincial public security department. The immigration and emigration population after 1985 are inter provincial immigration and emigration. The data in 1952 is based on the China population · Qinghai volume published by China finance and Economics Press Based on relevant data. The data are compiled from the statistical yearbook of Qinghai Province issued by Qinghai Provincial Bureau of statistics. The dataset contains 25 data tables: Changes of population and machinery in Qinghai Province in Main Years (1990-2019) xls Changes in population and machinery in major years 1952-2004 xls Changes in population and machinery in major years 1952-2008 xls Changes in population and machinery in major years 1952-2009 xls Changes in population and machinery in major years 1952-2010 xls Changes in population and machinery in major years 1952-2011 xls Changes in population and machinery in major years 1952-2012 xls Changes in population and machinery in major years 1952-2013 xls Changes in population and machinery in major years 1952-2014 xls Changes in population and machinery in major years 1952-2015 xls Changes in population and machinery in major years 1952-2016 xls Changes in population and machinery in major years 1952-2006 xls Changes in population and machinery in major years 1952-2007 xls Mechanical changes in population in Main Years 1987-2005 xls Changes in population and machinery in major years 1990-2017 xls Changes in population and machinery in major years 1990-2018 xls Main population changes 1952-2001 xls Main population changes 1952-2002 xls Population changes 1952-2003 xls Changes in population machinery, 1952-2002 xls Changes in population and machinery, 1952-2003 xls Changes of population and machinery in the whole province from 1952 to 1998 xls Changes of population and machinery in the whole province from 1952 to 1999 xls Changes of population and machinery in the whole province from 1952 to 2000 xls Changes of population and machinery in the whole province from 1952 to 2001 The XLS data table has the same structure. For example, there are five fields in the 1952-1998 data table of population and machinery changes in the province: Field 1: year Field 2: number of people Field 3: migration rate Field 4: number of people Field 5: emigration rate
Qinghai Provincial Bureau of Statistics
The data set records the number of students per 10,000 population in Qinghai province from 1952 to 2020, and the data is divided by statistical year. The data are collected from qinghai Statistical Yearbook released by Qinghai Provincial Bureau of Statistics. The dataset contains 22 data tables, which are: Number of students per 10,000 population in Qinghai Province (1957-2020). XLS Number of students per 10,000 population in the province, 1952-1998. XLS Number of students per 10,000 population in the province, 1952-1999. XLS Number of students per 10,000 population in the province, 1952-2000. XLS Number of students per 10,000 population in the province, 1952-2001. XLS Number of students per 10,000 population in The province, 1952-2002. XLS Number of students per 10,000 population in the province 1952-2003. XLS Number of students per 10,000 population in the province, 1952-2004. XLS Main years Number of students per 10,000 population in the province 1952-2006. XLS Main years Number of students per 10,000 population in the province 1952-2007. XLS Main years Number of students per 10,000 population in the province 1952-2008. XLS Number of students per 10,000 population in the province 1952-2009. XLS Number of students per 10,000 population in the province 1952-2011. XLS Number of students per 10,000 population in the province 1952-2012. XLS Number of students per 10,000 population in The province 1952-2013. XLS Number of students per 10,000 population in The province 1952-2014. XLS Number of students per 10,000 population in The province 1952-2015. XLS Number of students per 10,000 population in The province 1952-2016. XLS Number of students per 10,000 population in The province from 1957 to 2017. XLS Number of students per 10,000 population in The province, 1957-2018. XLS Number of students per 10,000 population in the province, 1963-2010. XLS Number of students per 10,000 population in main years 1996 -2005. XLS The data table structure is the same. For example, the number of students per 10,000 population in the province from 1952 to 1998 has 6 fields: Field 1: Year Field 2: College students Field 3: Secondary school students Field 4: Intermediate division Field 5: Secondary school students
Qinghai Provincial Bureau of Statistics
The data set records the changes of employees in all units of Qinghai Province, and the data is divided according to the changes of employees in all units. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set consists of three data tables Changes in employees of all units 1998.xls, Changes in employees of all units, 1999.xls, Changes of employees in all units in 2000.xls. The data table structure is the same. For example, there are five fields in the 1998 data sheet on the change of employees in all units Field 1: Category Field 2: Total Field 3: recruitment from rural areas Field 4: recruit from town Field 5: Veterans employed
Qinghai Provincial Bureau of Statistics
This data set records the situation of laid-off workers in Qinghai Province, and the data is divided according to the diversion situation of laid-off workers in state-owned enterprises. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set consists of four tables The situation of laid off workers in enterprises, 1998.xls The situation of laid off workers in enterprises, 1999.xls The situation of laid off workers in enterprises, 2000.xls The distribution of laid-off workers in state-owned enterprises in 1997. The data table structure is the same. For example, there are four fields in the data table of the distribution of laid-off workers in state-owned enterprises Field 1: Category Field 2: Industrial Enterprise Field 3: large and medium sized industrial enterprises Field 4: enterprises directly under the central government
Qinghai Provincial Bureau of Statistics
The data set records the number of employees of other units in Qinghai Province by industry and region at the end of the year, and the data is divided by the number of employees of other units by industry and region at the end of the year. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set consists of 8 data tables Number of employees in other units by industry at the end of the year 1995-2001.xls Number of employees in other units by industry at the end of the year 1995-2002.xls Number of employees of other units by industry at the end of 2003.xls Number of employees of other units by industry at the end of 2004.xls Number of employees of other units by industry at the end of 2005.xls Number of employees in other units by industry and region at the end of 2006.xls Number of employees in other units by industry and region at the end of 2007.xls The number of employees of other units by industry and region at the end of 2008.xls. The data table structure is similar. For example, there are 10 fields in the 2005 data table of the number of employees of other units by industry and region at the end of the year Field 1: Project Field 2: province total Field 3: Xining City Field 4: Haidong region Field 5: Haibei Prefecture Field 6: huangnanzhou Field 7: Hainan Field 8: Golog Field 9: Yushu prefecture Field 10: Haixi
Qinghai Provincial Bureau of Statistics
The data set records the basic situation of farmers and herdsmen families in Qinghai Province, and the data are divided according to the basic situation of farmers and herdsmen families. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set contains a data table, which is the basic information of farmers and herdsmen families in the main years 1985-2007.xls. The basic information of farmers and herdsmen families in the main years from 1985 to 2007 has seven fields Field 1: number of households surveyed Field 2: resident population of survey households Field 3: average annual income per person Field 4: average annual expenditure per person Field 5: total expenditure Field 6: cash expenditure Field 7: average annual net income per person
Qinghai Provincial Bureau of Statistics
This data set records the statistical data of the basic situation of rural households in Qinghai Province. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set consists of three data tables Basic information of rural households, 1984-1998.xls, Basic information of rural households, 1984-1999.xls, Basic information of rural households 1985-2000.xls. The data table structure is similar. For example, there are four fields in the basic information of rural households from 1984 to 1998 Field 1: number of households investigated Field 2: household permanent population (person) Field 3: average population per household (person) Field 4: full and half labor force (person)
Qinghai Provincial Bureau of Statistics
This data set records the statistical data of the total income, total expenditure and net income per capita of the rural poverty monitoring households in Qinghai Province. The data are divided by the total income, total expenditure and net income per capita of the rural poverty monitoring households. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set consists of two data tables Total income, total expenditure and net income per capita of rural poverty monitoring households, 1997-1999.xls, Total income per capita, total expenditure and net income of rural poverty monitoring households, 1999-2000.xls. The data table structure is similar. For example, there are eight fields in the data table of per capita total income, total expenditure and net income of Rural Poverty Monitoring Survey households from 1997 to 1999 Field 1: number of villages investigated Field 2: number of households investigated Field 3: number of respondents (person) Field 4: full and half labor force (person) Field 5: total annual revenue Field 6: annual total expenditure Field 7: depreciation of productive fixed assets Field 8: annual net income
Qinghai Provincial Bureau of Statistics
This data set records the statistical data of per capita income and expenditure of Rural Poverty Monitoring and survey households in Qinghai Province. The data is divided according to the per capita income and expenditure of Rural Poverty Monitoring and survey households in Qinghai Province. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set mainly includes 10 data tables Per capita income and expenditure of rural poverty monitoring households, 2001-2005.xls Per capita income and expenditure of rural poverty monitoring households, 2001-2006.xls Per capita income and expenditure of rural poverty monitoring households, 2001-2007.xls Per capita income and expenditure of rural poverty monitoring households, 2001-2008.xls Per capita income and expenditure of rural poverty monitoring households, 2001-2009.xls Per capita income and expenditure of rural poverty monitoring households, 2001-2010.xls Per capita income and expenditure of rural poverty monitoring households, 2004.xls The survey of rural per capita income and expenditure in 2006-xls Per capita income and expenditure of rural poverty monitoring households, 2008-2012.xls Per capita income and expenditure of rural poverty monitoring households, 2010-2013.xls The data table structure is similar. For example, there are eight fields in the data table of per capita income and expenditure of Rural Poverty Monitoring Survey households from 2001 to 2006 Field 1: number of villages investigated Field 2: number of households investigated Field 3: number of respondents (person) Field 4: full and half labor force (person) Field 5: total annual revenue Field 6: annual total expenditure Field 7: depreciation of productive fixed assets Field 8: annual net income
Qinghai Provincial Bureau of Statistics
This data set records the statistical data of the per capita income and expenditure of the rural poverty monitoring survey households in Qinghai Province (sampling survey). The data is divided according to the per capita income and expenditure of the rural poverty monitoring survey households in Qinghai Province. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set consists of three data tables Per capita income and expenditure of rural poverty monitoring households (sampling survey) 1999-2001.xls A survey of per capita income and expenditure of rural households in 2002 Rural Poverty Monitoring Survey household income and expenditure per capita (sampling survey) 2000-2003.xls The data table structure is similar. For example, there are four fields in the data table of per capita income and expenditure of Rural Poverty Monitoring Survey households (sampling survey) from 1999 to 2001 Field 1: total annual revenue Field 2: annual total expenditure Field 3: depreciation of productive fixed assets Field 4: annual net income
Qinghai Provincial Bureau of Statistics
The data set records the basic situation of rural households in Qinghai Province from 1985 to 2013, which is divided by industry, region, affiliation and registration type. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set consists of 12 data tables Basic situation of rural households in Main Years 1985-2004.xls Basic information of rural households in Main Years 1985-2006.xls Basic situation of rural households in Main Years 1985-2008.xls Basic information of rural households in Main Years 1985-2009.xls Basic situation of rural households in Main Years 1990-2010.xls Basic information of rural households in Main Years 1990-2005.xls Basic situation of rural households in Main Years 1995-2011.xls Basic situation of rural households in Main Years 2000-2013.xls Basic situation of rural households in Main Years 2000-2012.xls Basic information of rural households 1985-2001.xls Basic information of rural households, 1985-2002.xls Basic information of rural households 1985-2003.xls The data table structure is the same. For example, there are 10 fields in the 1985-2001 data table about the basic situation of rural households Field 1: Project Field 2: 1985 Field 3: 1990 Field 4: 1995 Field 5: 1996 Field 6: 1997 Field 7: 1998 Field 8:1999 Field 9:2000 Field 10:2001
Qinghai Provincial Bureau of Statistics
This data set records the statistical data of the proportion of rural households grouped by net income in the survey households in Qinghai Province from 1985 to 2011, which is divided by industry, region, affiliation and registration type. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set consists of 12 data tables The proportion of rural households grouped by net income in the survey households in the main years 1985-2004.xls The proportion of rural households grouped by net income in the survey households in the main years 1985-2006.xls The proportion of rural households grouped by net income in the survey households in the main years 1985-2008.xls The proportion of rural households grouped by net income in the survey households in the main years 1985-2009.xls The proportion of rural households grouped by net income in the survey households in the main years 1985-2010.xls The proportion of rural households grouped by net income in the survey households in the main years 1990-2005.xls The proportion of rural households grouped by net income in the survey households in Main Years 1995-2011.xls The proportion of rural households grouped by net income in the survey households in Main Years 1995-2011.xls Proportion of households grouped by net income of farmers and herdsmen in survey households in Main Years 1985-2007.xls The proportion of rural households grouped by net income in the survey households, 1985-2001.xls The proportion of rural households grouped by net income in the survey households, 1985-2002.xls The proportion of rural households grouped by net income in the survey households 1985-2003.xls The data table structure is the same. For example, the proportion of rural households grouped by net income in the survey households has 10 fields in the data table from 1985 to 2001 Field 1: Project Field 2: 1985 Field 3: 1990 Field 4: 1995 Field 5: 1996 Field 6: 1997 Field 7: 1998 Field 8:1999 Field 9:2000 Field 10:2001
Qinghai Provincial Bureau of Statistics
This data set records the statistical data of the number of rural family employees in Qinghai Province from 1952 to 2000, which is divided by industry, region, affiliation and registration type. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set consists of two data tables The number of rural family employees by industry 1952-1999.xls The number of rural family employees by industry 1952-2000.xls The data table structure is the same. For example, there are eight fields in the 2003 data sheet about the professional and technical personnel in different industries Field 1: Category Field 2: 1952 Field 3: 1978 Field 4: 1990 Field 5: 1995 Field 6: 1998 Field 7: 1999 Field 8: year 2000
Qinghai Provincial Bureau of Statistics
The data set recorded the basic situation of rural areas and the statistical data of rural employees in Qinghai Province from 2000 to 2020. The data were divided by rural grassroots organizations, household number and population, rural employees and national economic industries. The data are collected from qinghai Statistical Yearbook released by Qinghai Provincial Bureau of Statistics. The dataset contains 18 data tables, which are: Basic Statistics of Rural areas and Rural Employees 2000-2005. XLS Basic Statistics of Rural areas and Rural Employees 2000-2006. XLS Basic Statistics of Rural areas and Rural Employees 2000-2007. XLS Rural basic information and rural employees 2002-2003. XLS Rural Basic Information and Rural Employees 2004. XLS Basic statistics of rural areas and Rural Employees 2005-2009. XLS Basic Statistics on Rural areas and Rural Employees 2005-2010. XLS Basic Statistics of Rural areas and Rural Employees 2005-2011. XLS Basic Statistics of Rural areas and Rural Employees 2007-2012 XLS Basic Statistics of Rural areas and Rural Employees 2008-2013 XLS Rural basic Information and Rural Employees 2008. XLS Basic Statistics on Rural areas and Rural Employees 2010-2014 XLS Basic Statistics on Rural areas and Rural Employees 2010-2015 XLS Basic Statistics on Rural areas and Rural Employees 2011-2016 XLS Basic Statistics on Rural areas and Rural Employees 2012-2017. XLS Basic Statistics on Rural areas and Rural Employees 2013-2018 XLS Basic Statistics on Rural areas and Rural Employees 2014-2019. XLS Basic Statistics on Rural areas and Rural Employees 2015-2020 XLS The data table structure is the same. For example, the 2002-2003 data table of rural basic information and Rural Employment has 6 fields: Field 1: indicator Field 2:2000 Field 3:2001 Field 4:2002 Field 5:2003 Field 6:2003 is % of 2002
Qinghai Provincial Bureau of Statistics
This data set records the statistical data of the number of retirees, retirees and retirees in Qinghai Province from 1998 to 2006, which are divided by industry, region, affiliation and registration type. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set consists of 10 tables The number of retired, retired and retired personnel and the composition of insurance and welfare expenses, 2000.xls Composition of insurance and welfare expenses for retired, retired and retired personnel, 1999.xls Number of retirees, retirees and retirees, 2001.xls Number of retirees, retirees and retirees 2002.xls Number of retirees, retirees and retirees, 1998.xls Number of retirees, retirees and retirees, 1999.xls Number of retirees, retirees and retirees 2000.xls Number of retirees, retirees and retirees 2004.xls Number of retirees, retirees and retirees 2006.xls Number of retirees, retirees and retirees 2003.xls The data table structure is the same. There are five fields in the data table of the number of retirees, retirees and retirees in 2001 Field 1: Department Field 2: Total Field 3: number of retired cadres by the end of this year Field 4: number of retired employees by the end of this year Field 5: number of retired employees receiving regular living expenses by the end of this year
Qinghai Provincial Bureau of Statistics
"This data set records the statistical data of the basic situation of households in Qinghai Province from 2013 to 2020. The data are divided by the number of sample households, households within the period, permanent resident labor force, permanent resident employees and housing. The data are collected from qinghai Statistical Yearbook released by Qinghai Provincial Bureau of Statistics. The dataset contains 9 data tables, which are: Basic Information of Households 2013-2014 XLS Basic information of Households 2014-2015 XLS Basic information of Households 2016-2017. XLS Basic information of Households in 2016. XLS Basic information on Households 2017-2018. XLS Basic information of households in 2019. XLS Basic Information of Households 2020. XLS The data table structure is the same. For example, basic household information 2013-2014 data table has 7 fields: Field 1: indicator Field 2: All households Field 3: Urban households Field 4: Rural households Field 5: All households Field 6: Urban households Field 7: Rural households
Qinghai Provincial Bureau of Statistics
The data set recorded the basic employment statistics of Qinghai Province from 1985 to 2019, which were divided by the total number of employed persons, the composition of employed persons, the number of employed persons by urban and rural areas, and the number of registered unemployed persons in urban areas. The data are collected from qinghai Statistical Yearbook released by Qinghai Provincial Bureau of Statistics. The dataset contains 19 data tables, which are: Basic information on employment in main years 1985-2006. XLS Basic information on employment in main years 1985-2010. XLS Basic information on employment in main years 1990-2005.xls Basic information on employment in main years 1998-2004. XLS Basic information on employment in main years 2000-2007.xls Basic information on employment in main years 2000-2008. XLS Basic information on employment in main years 2000-2009. XLS Basic information on employment in main years 2005-2011. XLS Basic information on employment in main years 2007-2013. XLS Basic information on employment in Main years 2008-2014. XLS Basic information on employment in main years 2009-2015. XLS Basic information on employment in main years 2010-2016. XLS Basic information on employment in main years 2011-2017. XLS Basic information on employment in major years 2012-2018. XLS Basic information on Employment in main years 2018-2019. XLS Basic information on employment in main years 2007-2012. XLS Basic information on employment 1995-2001. XLS Basic information on employment 1996-2002. XLS Basic information on employment 1997-2003. XLS The data table structure is the same. For example, the basic employment data table 1995-2001 contains eight fields: Field 1: Item Field 2:1995 Field 3:1996 Field 4:1997 Field 5:1998 Field 6:1999 Field 7:2000 Field 8:2001
Qinghai Provincial Bureau of Statistics
The dataset records the statistical data of marriage registration in Qinghai province from 1998 to 2020, and the data are divided by industry, region, affiliation and registration type. The data are collected from qinghai Statistical Yearbook released by Qinghai Provincial Bureau of Statistics. The dataset contains 15 data tables, which are: Marriage registration 1998. XLS Marriage registration 1999. XLS Marriage registration 2000. XLS Marriage registration 2001. XLS Marriage registration 2002. XLS Marriage registration 2003. XLS Marriage registration 2004. XLS Marriage registration 2005. XLS Marriage Registration 2006. XLS Marriage Registration 2007. XLS Marriage Registration 2008. XLS Marriage registration 2009. XLS Marriage Registration in 2010. XLS Marriage Registration 2011. XLS Marriage registration 2011-2020. XLS The data table structure is the same. For example, marriage registration 2001 The 2001 data table has 6 fields: Field 1: region Field 2: Permission to register marriage couples Field 3: # First marriage Field 4: # Remarried person Field 5: # Remarriage pair Field 6: Permission to register divorce couples
Qinghai Provincial Bureau of Statistics
This data set records the statistical data of various professional and technical personnel of state-owned enterprises and institutions in Qinghai Province from 2001 to 2020. The data are divided into agriculture, forestry, animal husbandry and fishery, mining, manufacturing, power, gas and water production and supply, construction, transportation, warehousing and postal administration, information transmission, computer services and software, wholesale and retail, accommodation and catering, and gold Financial industry, real estate industry, leasing and business service industry, scientific research and technology service, geological exploration industry, water conservancy environment and public facilities management industry, resident service and other service industries, education, health, social security and social welfare industry, culture, sports and entertainment industry, public management and social organizations, international organizations, etc. The data are compiled from the statistical yearbook of Qinghai Province issued by Qinghai Provincial Bureau of statistics. The dataset contains 36 data tables: Professional and technical personnel of state-owned institutions and enterprises in major years 2005-2013 xls Professional and technical personnel of state-owned institutions and enterprises in major years 2005-2014 xls Professional and technical personnel of state-owned institutions and enterprises in major years 2005-2012 xls Professional and technical personnel of state-owned enterprises and institutions in major years 2005-2015 xls Professional and technical personnel of state-owned enterprises and institutions in major years 2005-2016 xls Professional and technical personnel of state-owned enterprises and institutions in Qinghai Province from 2015 to 2020 xls Professional and technical personnel of state-owned enterprises and institutions in Qinghai Province from 2010 to 2019 xls Professional and technical personnel of state-owned enterprises and institutions in major years 2005-2017 xls Professional and technical personnel of state-owned enterprises and institutions in major years 2010-2018 xls Situation of various professional and technical personnel in institutions and enterprises, 2001-2003 xls Situation of various professional and technical personnel in institutions and enterprises, 2001-2005 xls。 Professional and technical personnel of institutions and enterprises, 2004 xls Professional and technical personnel of public institutions by industry, 2004 xls Professional and technical personnel of public institutions by industry, 2003 xls Professional and technical personnel of enterprises and institutions by industry, 2006 xls Professional and technical personnel of the enterprise by industry, 2004 xls Professional and technical personnel by industry, 2003 xls Professional and technical personnel in state - owned institutions and enterprises, 2001 - 2006 XLS Professional and technical personnel in state - owned institutions and enterprises, 2001 - 2007 XLS Professional and technical personnel in state - owned institutions and enterprises, 2001 - 2008 XLS Professional and technical personnel of state - owned institutions and enterprises 2005 - 2009 xls Professional and technical personnel of state-owned institutions and enterprises, 2005-2010 XLS Professional and technical personnel of state-owned institutions and enterprises, 2005-2011 xls Professional and technical personnel of state-owned enterprises and institutions by industry, 2010 xl Professional and technical personnel of state-owned enterprises and institutions by industry, 2011 xls Professional and technical personnel of state-owned enterprises and institutions by industry, 2012 xls Professional and technical personnel of state-owned enterprises and institutions by industry, 2013 xls Professional and technical personnel of state-owned enterprises and institutions by industry, 2014 xls Professional and technical personnel of state-owned enterprises and institutions by industry, 2015 xls Professional and technical personnel of state-owned enterprises and institutions by industry, 2016 xls Professional and technical personnel of state-owned enterprises and institutions by industry, 2017 xls Professional and technical personnel of state-owned enterprises and institutions by industry in 2018 xls Professional and technical personnel of various industries in state-owned enterprises and institutions, 2006 xls Professional and technical personnel of various industries in state-owned enterprises and institutions, 2007 xls Professional and technical personnel of various industries in state-owned enterprises and institutions, 2008 xls Professional and technical personnel of state-owned enterprises and institutions by industry, 2009 xls The data table structure is the same. For example, there are 7 fields in the 2003 data sheet of the enterprise's professional and technical personnel by industry: Field 1: Industry Field 2: Total Field 3: engineering technicians Field 4: agricultural technicians Field 5: Researchers Field 6: health technicians Field 7: Educators
Qinghai Provincial Bureau of Statistics
This data set records the statistical data of the number of employees in urban collective units of Qinghai Province from 2006 to 2008 by industry, region and purpose. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set contains 11 tables, which are: the number of employees in urban collective units by industry and region at the end of the year (2006). XLS, the number of employees in urban collective units by industry and region at the end of the year (2007). XLS, the number of employees in urban collective units by industry and region at the end of the year (2008). XLS, etc. The data table structure is the same. For example, the data table in 2006 has four fields: Field 1: year Field 2: Industry Field 3: Region Field 4: amount
Qinghai Provincial Bureau of Statistics
This data set records the statistical data of registered unemployed persons in cities and towns of Qinghai Province from 1980 to 2003, which are divided by industry, region and purpose. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set contains seven tables, which are: changes of urban registered unemployed persons from 1980 to 2001.xls, changes of urban registered unemployed persons from 1980 to 2002.xls, changes of urban registered unemployed persons from 1980 to 2003.xls, changes of urban registered unemployed persons from 1990 to 1998.xls, etc. The data table structure is the same. For example, there are four fields in the data table from 1980 to 2003 Field 1: year Field 2: number of unemployed Field 3: total number of people Field 4: Proportion
Qinghai Provincial Bureau of Statistics
This data set records the statistical data of employees and labor remuneration of urban units in Qinghai Province from 2006 to 2008, which are divided by industry, region and purpose. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set contains three data tables: Urban unit employment and labor remuneration (2006). XLS, urban unit employment and labor remuneration (2007). XLS, urban unit employment and labor remuneration (2008). XLS. The data table structure is the same. For example, the data table in 2008 has four fields: Field 1: year Field 2: number of units Field 3: number of people Field 4: other
Qinghai Provincial Bureau of Statistics
This data set records the statistical data of employees' changes in urban units of Qinghai Province from 2001 to 2008, which are divided by industry, region and purpose. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set contains nine tables, which are: changes of employees in urban units (2002). XLS, changes of employees in urban units (2003). XLS, changes of employees in urban units (2004). XLS, changes of employees in urban units (2006). XLS, etc. The data table structure is the same. For example, the data table in 2002 has four fields: Field 1: year Field 2: Rural Field 3: Town Field 4: People
Qinghai Provincial Bureau of Statistics
This data set records the statistical data of the number of employees at the end of the year according to the three industries in Qinghai Province, and the data are divided by industry, region, subordinate relationship, etc. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set consists of three tables: the number of employees at the end of the year by three industries 1952-2001.xls, the number of employees at the end of the year by three industries 1952-2002.xls, and the number of employees at the end of the year by three industries 1952-2003.xls. The data table structure is the same. For example, there are three fields in the data table from 1952 to 2001 Field 1: year Field 2: Practitioners Field 3: Industry
Qinghai Provincial Bureau of Statistics
This data set records the statistical data of total wages of employees employed in all units by industry in Qinghai Province from 2010 to 2020. Data in an ecological-economic, mining, manufacturing, electricity, gas and water, construction, wholesale and retail trade, transportation, warehousing and postal service, accommodation and catering industry, information transmission, software, finance, real estate, leasing and business services, scientific research and technical services, water environment and public facilities management, residents service, repair and other services, and taught Education, health and social work, culture, sports and entertainment, public administration and social security. The data are collected from qinghai Statistical Yearbook released by Qinghai Provincial Bureau of Statistics. The dataset contains eight data tables, which are: Employees employed in All Units by Industry (2011). XLS, Employees employed in All Units by Industry (2012). XLS, Employees employed in All Units by Industry (2010-2013). XLS, Employees employed in All Units by Industry (2010-2014). Number of Employed Persons in All Units by Industry 2011-2015 XLS, Number of Employed Persons in All Units by Industry 2012-2017 XLS, Number of Employed Persons in All Units by Industry in Qinghai Province (2015-2020) XLS, Employed persons in all Units by Industry 2013-2018. XLS. The data table structure is the same. For example, the data table from 2012 to 2018 has 9 fields: Field 1: Item Field 2: Item Field 3:2012 Field 4:2013 Field 5:2014 Field 6:2015 Field 7:2016 Field 8:2017 Field 9:2018
Qinghai Provincial Bureau of Statistics
This data set records the statistical data of the number of employed persons in Qinghai Province by urban and rural areas at the end of the year, and the data is divided by industry, region, type, etc. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set consists of three tables, which are: the number of employed persons at the end of the year 2005-2006.xls by urban and rural areas, the number of employed persons at the end of the year 2006-2007.xls by urban and rural areas, and the number of employed persons at the end of the year 2007-2008.xls by urban and rural areas. The data table structure is the same. For example, the data table from 2005 to 2006 has three fields: Field 1: Project Field 2: Town Field 3: Rural Field 4: Total
Qinghai Provincial Bureau of Statistics
This data set records the statistical data of the number of employees at the end of the year in Qinghai Province by urban and rural areas, and the data is divided by industry, region, etc. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set consists of 8 tables, which are: number of employees at the end of the year by urban and rural areas (2003). XLS, number of employees at the end of the year by urban and rural areas (1999-2000. XLS), number of employees at the end of the year by urban and rural areas (2000-2001. XLS), number of employees at the end of the year by urban and rural areas (2001-2002. XLS), number of employees at the end of the year by urban and rural areas (2003-2004. XLS), number of employees at the end of the year by urban and rural areas (2003-2004. XLS) Number of employees 2004-2005.xls, number of employed persons by urban and rural areas 2008-2009.xls number of employed persons by urban and rural areas 2009-2010.xls. The data table structure is the same. For example, the data table in 2003 has three fields: Field 1: Total Field 2: Township Field 3: Rural
Qinghai Provincial Bureau of Statistics
The data set records the number of rural labor force in different industries in Qinghai Province from 1952 to 1998, and the data is divided by year. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set contains one data table, which is: the number of rural labor by industry 1952-1998.xls. The data table structure is the same. For example, there are eight fields in the data table from 1952 to 1998 Field 1: Category Field 2: 1952 Field 3: 1978 Field 4: 1990 Field 5: 1995 Field 6: 1996 Field 7: 1997 Field 8: 1998
Qinghai Provincial Bureau of Statistics
The data set records the number of rural households, population and rural employees in Qinghai Province from 1978 to 2003, and the data is divided by year. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set consists of four tables: rural employees 1978-2001.xls, rural employees 1978-2002.xls, rural households, population and rural employees 1978-2003.xls, rural households, population and rural employees 2004.xls. The data table structure is the same. For example, there are eight fields in the data table from 1978 to 2001 Field 1: Year Region Field 2: total of rural employees Field 3: agriculture, forestry, animal husbandry and fishery Field 4: Industry Field 5: Construction Field 6: transportation, warehousing, posts and Telecommunications Field 7: Wholesale and retail trade catering industry Field 8: other non agricultural industries
Qinghai Provincial Bureau of Statistics
The data set records the population and family planning situation of Qinghai Province from 2001 to 2014, and the data is divided by year. The statistical data of Qinghai Province is published by Qinghai Provincial Bureau of statistics. The data set contains 15 data tables with the same structure. For example, the data table in 2001 has 10 fields: Field 1: Indicators Field 2: Total Field 3: Xining City Field 4: Haidong region Field 5: Haibei Prefecture Field 6: Hainan Field 7: Huang Nanzhou Field 8: Golog Field 9: Yushu prefecture Field 10: Haixi
Qinghai Provincial Bureau of Statistics
The data set records the population changes in Qinghai province from 1952 to 2019, and the data is divided by year. The data are collected from qinghai Statistical Yearbook released by Qinghai Provincial Bureau of Statistics. The dataset contains 19 data tables, all of which have the same structure. For example, the data table from 1952 to 1998 has 11 fields: Field 1: Year Field 2: Year-end population Field 3: Male Field 4: Female Field 5: Town population Field 6: Rural population Field 7: Agricultural population Field 8: Non-agricultural population Field 9: Birth rate Field 10: Population mortality rate Field 11: Natural population growth rate
Qinghai Provincial Bureau of Statistics
The data set records the total population and natural changes of Qinghai Province from 1952 to 2010, and the data are divided by year. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set contains 13 data tables with the same structure. For example, there are eight fields in the data table from 1952 to 1998 Field 1: year Field 2: total population Field 3: number of births Field 4: birth rate Field 5: number of deaths Field 6: mortality Field 7: natural increase Field 8: natural growth rate
Qinghai Provincial Bureau of Statistics
The data set records the statistical data of birth rate, death rate and natural growth rate (2001-2008) in different regions of China, and the data are divided by year. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set contains eight data tables, each of which has the same structure. For example, the data table in 2008 has five fields: Field 1: Province (city, district) Field 2: total population at the end of the year Field 3: birth rate Field 4: population mortality Field 5: natural population growth rate
Qinghai Provincial Bureau of Statistics
This data set records the statistical data of the proportion of urban population in various regions of China (2010-2018), which is divided by year. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set consists of three data tables Proportion of urban population in different regions of China (2010-2016). Xls Proportion of urban population in different regions of China (2011-2017). Xls The proportion of urban population in all regions of China (2011-2018). XLS, the data table structure is the same. For example, the data table in 2018 has two fields: Field 1: year Field 2: Region
Qinghai Provincial Bureau of Statistics
This data set records the statistical data of the permanent population size (2007-2018) in different regions of China, and the data are divided by year. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set consists of seven data tables with the same structure. For example, the data table from 2011 to 2018 has two fields: Field 1: year Field 2: Region
Qinghai Provincial Bureau of Statistics
The data set records the statistical data of registered unemployed persons in major years in Qinghai Province, and the data are divided by year. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set includes three data tables: the number of employees at the end of the year 1952-1998.xls, the number of employees at the end of the year 1952-1999.xls, and the number of employees at the end of the year 1952-2000.xls in the main years. The data table structure is the same. For example, the data table in 2000 has eight fields: Field 1: year Field 2: Practitioners Field 3: state owned economy Field 4: collective economy Field 5: urban private economy Field 6: urban individual economy Field 7: foreign investment economy in Hong Kong, Macao and Taiwan Field 8: other economies
Qinghai Provincial Bureau of Statistics
The data set records the statistical data of changes of registered urban unemployed in Qinghai province in major years from 1980 to 2020, and the data is divided by year. The data are collected from qinghai Statistical Yearbook released by Qinghai Provincial Bureau of Statistics. The dataset contains data tables, all of which have the same structure. For example, the 2018 table has seven fields: Field 1: Year Field 2: Total number of unemployed persons Field 3: Number of carryovers from previous year Field 4: New additions for the year Field 5: Number of unemployed persons placed for employment in the current year Field 6: Actual number of unemployed persons at the end of this year Field 7: Registered urban unemployment rate
Qinghai Provincial Bureau of Statistics
The dataset records the statistical data of permanent resident population and natural variation in Qinghai Province in major years from 1952 to 2019, and the data is divided by year. The data of 1990, 2000 and 2010 are the projections of census data of that year, and the data of other years are the projections of sample survey on population change. The data are collected from qinghai Statistical Yearbook released by Qinghai Provincial Bureau of Statistics. The dataset contains 9 data tables, which are: XLS, Permanent Population and Natural Fluctuation in Main Years 1952-2011. XLS, Permanent Population and Natural Fluctuation in Main Years 1952-2012. XLS, Permanent Population and Natural Fluctuation in Main Years 1952-2013 XLS. Permanent Population and Natural Fluctuations in Major Years 1952-2014. XLS, Permanent Population and Natural Fluctuations in Major Years 1952-2016. XLS, Permanent Population and Natural Fluctuations in Major Years 1952-2016. XLS, Permanent Population and Natural Fluctuations in Major Years 1952-2016. XLS, Permanent Population and Natural Fluctuations in Major Years 1952-2016. XLS, Permanent Population and Natural Fluctuations in Major Years 1952-2016. XLS, Permanent Population and Natural fluctuations in Major Years 1952-2016. XLS, Permanent Population and Natural fluctuations in Major Years 1952-2017.xls, Permanent population and natural variation in major years 1952-2018. XLS, data table structure is the same. For example, the 2006 table has 5 fields: Field 1: Year Field 2: Resident population Field 3: Birth Field 4: Death Field 5: Natural growth
Qinghai Provincial Bureau of Statistics
The data set records the statistical data of population change in different regions of Qinghai Province from 1998 to 2010, which is divided by region, total number of households, total population, birth population and death population. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set contains 10 data tables with different structures. For example, the data table in 1999 has five fields: Field 1: Region Field 2: total number of households Field 3: total population Field 4: birth population Field 5: death population
Qinghai Provincial Bureau of Statistics
The data set records the statistics and statistics of registered residence population in Qinghai Province in 2003-2018 years. The data are divided into regions, total population, total population, population changes, births, deaths, immigration and relocation. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set contains 19 data tables with different structures. For example, the data table in 2002 has seven fields: Field 1: ground difference Field 2: number of households Field 3: population Field 4: Total Field 5: household Field 6: collective account Field 7: average family size
Qinghai Provincial Bureau of Statistics
This data records the statistical data of the number of employees in different regions and industries of Qinghai Province at the end of 2006-2008. The data are divided according to the project, the total of the whole province, Xining City, Haidong region, Haibei Prefecture, Huangnan Prefecture, Hainan prefecture, Guoluo Prefecture, Yushu prefecture and Haixi Prefecture. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set contains six data tables with different structures. For example, there are 18 fields in the data table from 1978 to 2002 Field 1: Year Region Field 2: Total Field 3: agriculture, forestry, animal husbandry and fishery Field 4: extractive industries Field 5: manufacturing Field 6: production and supply of electricity, gas and water Field 7: Construction Field 8: geological exploration and water conservancy management Field 9: transportation, warehousing, posts and Telecommunications 10: Wholesale and retail Field 11: finance, insurance Field 12: Real Estate Field 13: social services Field 14: health, sports and social welfare Field 15: education, culture and arts, radio, film and television Field 16: scientific research and integrated technical services Field 17: state organs, political party organs and social organizations Field 18: other
Qinghai Provincial Bureau of Statistics
This data records the statistical data of female employees in different types of registration and sub industries in Qinghai Province from 2001 to 2008. The data are divided by project, total, state-owned units, urban collective units and other units. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set contains eight data tables with the same structure. For example, the data table in 2008 has six fields: Field 1: Project Field 2: item Field 3: Total Field 4: state owned Units Field 5: urban collective units Field 6: other units
Qinghai Provincial Bureau of Statistics
This data records the statistical data of the number of employees at the end of 2001-2008 in Qinghai Province by registration type and sub industry. The data is divided by project, total, state-owned units, urban collective units and other units. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set contains eight data tables with the same structure. For example, the data table in 2006 has five fields: Field 1: Project Field 2: Total Field 3: state owned Units Field 4: urban collective unit Field 5: other units
Qinghai Provincial Bureau of Statistics
"The data records statistics on the number of non-private employment in Qinghai province by type of registration and industry at the end of the year from 2011 to 2020. The data are grouped by enterprises, institutions and organs, and by industry of the national economy. The data are collected from qinghai Statistical Yearbook released by Qinghai Provincial Bureau of Statistics. The dataset contains 10 data tables with the same structure. For example, the 2018 table has six fields: Field 1: Item Field 2: Item Field 3: Total Field 4: State-owned units Field 5: Town collective units Field 6: Other units
Qinghai Provincial Bureau of Statistics
This data records the statistical data of the number of employees of urban units in Qinghai Province at the end of 2009-2018, which are divided by project, total, state-owned units, urban collective units and other units. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. There are 12 data tables in the dataset, and the structure of each year's data table is the same. For example, the data table in 2018 has six fields: Field 1: Project Field 2: item Field 3: Total Field 4: state owned Units Field 5: urban collective units Field 6: other units
Qinghai Provincial Bureau of Statistics
The data set records the main data of the fifth population census of Qinghai Province from 2000 to 2009. The data city is divided by region, population aged 6 and above, number of people with various education levels and average years of education. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set contains 25 data tables with different structures. For example, the data table in 2009 has nine fields: Field 1: Region Field 2: Region Field 3: population aged 6 and above Field 4: number of people with different education levels Field 5: junior college or above Field 6: high school and technical secondary school Field 7: Junior High School Field 8: Primary School Field 9: average years of Education
Qinghai Provincial Bureau of Statistics
The data set records the main data of the sixth national census of Qinghai Province in 2010. The data are divided by province (city, district), permanent population, quantity, gender and proportion. The data set contains 20 data tables, which are: the main data of the sixth national census in 2010.xls, the permanent population aged 6 and above by region, gender and education level in the sixth census in 2011.xls, the permanent population aged 6 and above by age, gender and education level in the sixth census in 2011.xls, and the permanent population aged 6 and above by region, age and gender in the sixth census in 2011.xls In the sixth census, the population aged 15 and above was illiterate in 2011.xls; in the sixth census, the population aged 15 and above was illiterate in 2011.xls; in the sixth census, the population aged 15 and above was illiterate in 2010.xls; in the sixth census, the population aged 15 and above and the sex ratio were illiterate in 2010.xls; in the sixth census, the population aged 15 and above was illiterate in 2010.xls Population with education level 2010.xls, the number and size of households by region and collective households in the sixth population census 2010.xls, the size of households by Region in the sixth population census 2011.xls, the category of households by Region in the sixth population census 2011.xls, the number of rooms and area of households by Region in the sixth population census 2011.xls, and the ethnic composition by Region in the sixth population census 2010.xls The main data of the sixth population census in Qinghai Province are as follows: the age composition of the sixth population census by Region 2010.xls, the population density of the sixth population census by Region 2010.xls, the age composition and dependency ratio of the sixth population census by Region 2011.xls, the age and gender permanent population of the sixth population census 2011.xls, the urbanization rate of the sixth population census by Region 2010.xls Report.docx. The data table structure is different. For example, the data table in 2010 has nine fields: Field 1: Province (city, district) Field 2: Region Field 3: resident population Field 4: quantity Field 5: Rank Field 6: Male Field 7: specific gravity Field 8: Female Field 9: sex ratio
Qinghai Provincial Bureau of Statistics
DNA was extracted from teeth or phalanx. Firstly, we conducted 2 hours UVirradiation on the samples, and removed a layer of surface using a sterile dentistry trill, then again irradiated with 1 hour UV-light on the samples. We drilled out ~80 mg of bone powder for every sample with the sterile dentistry trill, and only do 2 samples at one time (include following procedures until performing sequencing; samples from different archaeological sites were never handled together) to avoid potential individual cross-contamination. Using the 80 mg bone powder, we performed DNA extraction following the silica suspension protocol from an early report (Rohland and Hofreiter 2007), which was modified afterwards (Allentoft, et al. 2015) for customizing recovering of more shorter DNA fragments, that finally resulting a total of 100 μl aliquots for each sample. In brief, the bone powder was digested over night with proteinase K in 0.5M EDTA plus 10% N-Laurylsarcosyl suspension, then the released DNA was absorbed in solution which includes PB buffer, 5M sodium acetate, 5M sodium chloride and SiO2 suspension, and followed by three times of purification using 80% ethyl alcohol. Finally, after airing, the DNA was eluted with 100 μl EB buffer. Next, to perform preliminary aDNA preservation situation screening, using 20μl DNA aliquots of each sample, we built the double strand library (DSL) with no Uracil- DNA-Glycosylase (UDG) treatment under a single indexing with commercial kit (cat no: E7370) from New England Biolabs (Ipswich, MA) following the manufacturer’s guidelines, as previously reported (Meyer and Kircher 2010) that includes end prep, adaptor ligation, purification, PCR amplification and size selection steps. PCRs were conducted in a final volume of 50 μl using AmpliTaq Gold 360 DNA Polymerase (AmpliTaq Gold, Life Technologies Applied Biosystems) which is able to well amplify across uracils, preserve the DNA damage pattern that induced by deamination, which indicating of authentic aDNA (Krause, et al. 2010). We performed all the sequencing (also the following captured library sequencing) on the Illumina HiSeq X Ten (PE-150) platform ( https://www.illumina.com.cn/systems/sequencing-platforms/hiseq-x.html ). The calculated appraise indexes of aDNA quality and preservation are shown in Table S1. Lastly, we rebuilt the DSLs with 3 hours UDG treatment using the remaining DNA extraction aliquots, which could largely remove uracil residues from DNA fragmental end to leave abasic sites, and cuts the DNA at the 5´ and 3´ sides of the abasic sites with enzyme endonuclease VIII (Endo VIII). For these libraries, we performed the mtDNA capture using myBaits® Mito-Target Capture Kits as previous report (Enk, et al. 2014). Briefly, we used the biotinylated RNA “baits” that are transcribed from the human genomic DNA to perform the capture in solution overnight at 65°C, then mixed in streptavidin-coated magnetic beads and sequestered the targets with a magnetic stand. The PCRs for both pre-capture and post-capture are performed using KAPA HiFi Hot start Polymerase (KAPA BIOSYSTEMS).
QI Xuebin
Hanging coffin burial is a kind of burial custom in which the coffin is placed on the cliff, cave and crevice. Hanging coffin burials are widely distributed in the Yangtze River Valley and the south of China, as well as in Southeast Asia and even the Pacific Islands. With the natural weathering and man-made destruction, there are fewer and fewer such relics. As a kind of peculiar and ancient archaeological cultural remains and funeral custom, hanging coffin culture has been widely concerned by archaeologists. Dating method: the wood samples on the hanging coffin were sent to beta analytical testing laboratory in Miami, USA for C14 determination. Methods: 4 in house NEC accelerator mass spectrometers (AMS) and 4 thermo IRMSS under strict chain of custom and quality control using ISO / IEC 17025:2005 testing accreditation pjla accreditation protocols Results: the dating results show that the earliest hanging coffin burial site is located in Wuyishan area of Fujian Province, 3600 years ago, which is equivalent to the Shang and Zhou dynasties in China. Wuyishan area in Fujian Province is considered to be the birthplace of the hanging coffin burial custom, which later spread to other areas in South China, Southeast Asia and the Pacific Islands. Located in the Jinsha River Valley of South Sichuan and Northeast Yunnan, the hanging coffin burial is the latest cultural remains of hanging coffin burial in mainland China (late Ming Dynasty), and also the West pole of the distribution of hanging coffin burial sites in China. There is a hanging coffin group in the mountainous area of Northwest Thailand, 2100-1200 years ago.
QI Xuebin
The complete mitochondrial DNA sequences of 41 human remains from 13 hanging coffin sites 2500-660 years ago in Weixin and Yanjin, Zhaotong, Yunnan, Huacun, Baise, Guangxi and bangmapa, Thailand were analyzed by using the ancient DNA analysis technique. They found that the maternal genetic diversity of the hanging coffin people in Northwest Yunnan was very high, while the genetic diversity of the hanging coffin people in northern Thailand was relatively low. This result is consistent with the view that the hanging coffin burial custom originated in southern China and spread southward to Southeast Asia. In addition, a small number of matrilineal lineages were shared among the hanging coffin people in different regions of Asia, indicating that there is a very close relationship between different hanging coffin people. Combining the results of genetic analysis with the evidences of archaeology, physical anthropology, folklore and history, they speculated that the hanging coffin burial custom originated in the Baiyue ethnic group in the southeast coastal areas of China (such as Wuyishan area) about 3600 years ago, and they are the ancestors of the Dai ethnic group with many ethnic groups. After that, the custom of hanging coffin was widely spread in South China by means of people migration and flow. However, about 2000 years ago (the earliest time of hanging coffin burial in Thailand), a very small number of inheritors of hanging coffin burial spread the custom to some aboriginal groups in Southeast Asia, such as northern Thailand, by means of cultural diffusion. This study only makes a preliminary discussion from the perspective of maternal genetic lineage. For the hanging coffin culture which has spread for more than 3000 years in South China, Southeast Asia and the vast area of the Pacific Islands, the origin and development of its culture and the history of its inheritors may be more complex. In the future, more representative samples of human remains buried in a hanging coffin will be used, from the perspective of genomic DNA and paternal Y-DNA, combined with interdisciplinary research, which will provide more systematic evidence support for a more comprehensive display of the historical and cultural features of the hanging coffin burial custom.
QI Xuebin
1) Data content: this data is the chromatin open group data of umbilical cord endothelial cells of Plateau Tibetan and plain Han people generated during the implementation of the project, including 5 cases of Plateau Tibetan umbilical cord endothelial cell chromatin open group data and 5 cases of plain Han umbilical cord endothelial cell chromatin open group data. The amount of chromatin open group data of each cell is > 15g sequencing depth, which can be used to study the high-risk factors The chromatin opening pattern and gene expression regulation pattern of the original Tibetan population and the plain Han population in high altitude hypoxia environment. 2) Data sources and processing methods: Based on our own data, we used the 150 BP pair end sequencing method of Illumina x-ten. 3) Data quality: > 15g data volume, q30 > 90%. 4) Data application achievements and prospects: the data are used to verify the open mode of cell chromatin and gene expression change mode of high altitude hypoxia adaptation genes under hypoxia environment.
QI Xuebin
The data set is mainly included the population, arable land and animal husbandry data of Qinghai Province and Tibet Autonomous Region in the past 100 years. The data mainly comes from historical documents and modern statistics. The data quality is more reliable. It mainly provides arguments for the majority of researchers in the development of agriculture and animal husbandry on the Qinghai-Tibet Plateau.
LIU Fenggui
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 includes the gender, age, social security, education level, labor force and employment status of household members in 1280 families at domestic and abroad, which is used to support the analysis of human capital and livelihood Strategy in sustainable livelihoods. The field survey data is collected by the research group. Before collecting the data, the research group and the invited experts conducted a pretest to improve the questionnaire; before the formal survey, the members participating in the data collection were strictly trained; during the formal survey, each questionnaire could be filed after three times of inspection. The data is of great value to understand the human capital, livelihood strategies and demographic characteristics of farmers in the vulnerable areas of environment and economy, and is an important supplement to the national and macro data in this area.
Linxiu ZHANG, BAI Yunli
The whole mitochondrial genomes of 68 Tibetan samples were sequenced by high-throughput second-generation sequencing. The average depth of sequencing was 1000 ×, ensuring that the mitochondrial genome of each sample was completely covered (100%). Based on the phylogenetic analysis, we control the quality of these data to ensure that there is no sample pollution and other quality problems. According to the phylogenetic tree, each individual was allocated into haplogroups. The results showed that in Lhasa Tibetan population, M9a1c1b1a was the highest (19.12%), followed by G2 (13.23%), M13a (11.76%), C4a (7.35%), D4 (7.35%), A11a1a (5.88%), M9a1b (5.88%), and F1c, F1g, B4, F1d, M62b, F1a, F1b, G1, M11, M8a, U7a, Z3a. These haplogroups have different originations, including Paleolithic components (M13a, M62b, M9a1b, etc.), northern China millet farmers’ components (M9a1c1b1a and A11a1a), components distributed mainly in southern East Asia (F1a, etc.), northern East Asian haplogroups (C4a, D4, etc.). It is worth noting that the maternal component of Lhasa Tibetans is mainly composed of millet agricultural population in northern China, indicating the important impact of genetic input of millet agricultural population in northern China on the genetic structure of the population in this area. Taken together, the maternal genetic structure of Lhasa Tibetan population exhibits time stratification, which may represent the genetic imprint of different population entering the region in different periods.
KONG Qingpeng
The Grassland Degradation Assessment Dataset in agricultural and pastoral areas of the Qinghai-Tibet Plateau (QTP) is a data set based on the 500m Global Land Degradation Assessment Data (2015), which is evaluated according to the degree of grassland degradation or improvement. In this dataset, the grassland degradation of the QTP was divided into two evaluation systems. At the first level, the grassland degradation assessment was divided into 3 types, including no change type, improvement type and degradation type. At the second level, the grassland degradation assessment on the QTP was divided into 9 types, among which the type with no change was class 1, represented by 0. There were 4 types of improvement: slight improvement (3), relatively significant improvement (6), significant improvement (9) and extremely significant improvement (12). The degradation types can be divided into 4 categories: slight degradation (-3), relatively obvious degradation (-6), obvious degradation (-9) and extremely obvious degradation (-12). This dataset covers all grassland areas on the QTP with a spatial resolution of 500m and a time of 2015. The projection coordinate system is D_Krasovsky_1940_Albers. The data are stored in TIFF format, named “grassdegrad”, and the data volume is 94.76 MB. The data were saved in compressed file format, named “500 m grid data of grassland degradation assessment in agricultural and pastoral areas of the Qinghai-Tibet Plateau in 2015”. The file volume is 2.54 MB. The data can be opened by ArcGIS, QGIS, ENVI, and ERDAS software, which can provide reference for grassland ecosystem management and restoration on the QTP.
LIU Shiliang, SUN Yongxiu, LIU Yixuan
It is not clear how the Tibetan people adapt to the extreme environment on the plateau. As an important phenotype, metabolism plays an important role in maintaining the normal biological function of individuals. Previous studies have shown that some small metabolic molecules can adapt to the extreme environment by regulating energy metabolism, oxidative stress and other biological processes. In view of this, the project is expected to find the relationship between human metabolism and extreme environmental adaptation by studying the unique metabolic characteristics of Tibetan people compared with plain people, and then study the plateau adaptation mechanism of Tibetan people from the perspective of metabolism. This data is the metabolomic data generated during the implementation of the project, and the current data includes the metabolomic data of 30 people in the plain. The combined analysis of these data and the subsequent metabolomic data can be used to study the metabolic characteristics of Tibetan people in the plateau hypoxia environment. This data set is the update and continuation of metabolomic data v1.0 of modern Chinese population.
LI Gonghua
As the “third pole” of the world, the Qinghai-Tibet Plateau (QTP) is extremely ecologically sensitive and fragile while facing increasing human activities and overgrazing. In this study, eight types of spatial data were firstly selected, including grazing intensity, Night-Time Light, population density, Gross Domestic Product (GDP) density, the ratio of cultivated land, the slope of the Normalized Difference Vegetation Index (NDVI), distance to road, and distance to town. Then, the entropy weight method was applied to determine the weight of each factor. Finally, the five-year interval human activity intensity data in 1990, 1995, 2000, 2005, 2010 and 2015 were made in the agricultural and pastoral areas of QTP through the spatial overlap method. By preparing the historical spatial datasets of human activity intensity, our study will help to explore the influence of human disturbance on the alpine ecosystems on the QTP and provide effective support for decision-making of government aiming at regional ecosystem management and sustainable development.
LIU Shiliang, SUN Yongxiu, LIU Yixuan, LI Mingqi
The natural resources dataset of the Qinghai-Tibetan Plateau covers 215 counties in this area. The observation intervals are 5 years from 2000-2015. The indicators are rainfall, temperature, humidity, population, and land area. The data sources are meteorological station data, regional statistical yearbook, etc., which are expressed by Excel. This data provides a reference for understanding the natural background conditions on the county scale in the Qinghai Tibet Plateau.
FENG Xiaoming
The natural resources dataset of the Qinghai-Tibetan Plateau covers 215 counties in this area. The observation intervals are 5 years from 2000-2015. The indicators are rainfall, temperature, humidity, population, and land area. The data sources are meteorological station data, regional statistical yearbook, etc., which are expressed by Excel. This data provides a reference for understanding the natural background conditions on the county scale in the Qinghai Tibet Plateau.
FENG Xiaoming
This data set records the division of Qinghai Province from 2000 to 208 according to urban and rural areas, as well as economic types and quantitative statistics. The data are collected from the statistical yearbook: Qinghai statistical yearbook, and the accuracy is the same as the statistical yearbook extracted from the data. The data set contains three data tables, which are 2005-2006, 2006-2007 and 2007-2008 year-end employment statistics by urban and rural areas. The data table structure is the same. Each data table has five fields, such as the number of employed persons at the end of the year by urban and rural areas in 2005-2006: Field 1: towns in 2005 Field 2: 2005 rural Field 3: towns in 2006 Field 4: villages in 2006 Field 5: 2005 total Field 6: 2006 total
ZHAO Hu
This data is the population grid data of ten meter scale in 2019. Each grid expresses the total number of population within this range (unit: person). The source data of this data comes from Myanmar's 2019 1km population data set in the world pop data center（ https://www.worldpop.org/geodata/summary?id=40443 ）, the obtained source data are processed by projection transformation and clipping to obtain the population distribution in Yangon, and then the data are downscaled, The spatial distribution data set of refined population (10m) in Yangon deep water port area is obtained. Regular ten meter scale population grid data are obtained by spatial scale conversion and downscaling. Each grid population is calculated by random forest method according to the population of each administrative unit and multi-source auxiliary data. Population data can be used in many fields, including urban planning, elections, risk assessment, disaster relief, disease prevention and control, poverty reduction and poverty alleviation, etc;
GE Yong, LI Qiangzi, LI Yi
The population grid data of 100 meter scale in 2010, each grid expresses the total number of population within the range (unit: person). The data is from the Institute of earth data, University of Southampton, UK. The data is processed by projection transformation and clipping to get the population distribution in Yangon area. Then the data is downscaled to get the refined population spatial distribution data set in Yangon deepwater port area. This data is based on the census data of administrative units, and the regular 100 meter scale population grid data is obtained through spatial scale conversion. Each grid population is calculated by using random forest method according to the population of each administrative unit and multi-source auxiliary data. Population data can be used in many fields, including urban planning, elections, risk assessment, disaster relief, disease prevention and control, poverty alleviation and so on;
GE Yong, LI Qiangzi, LI Yi
The refined population spatial distribution data set of Hambantota port area is generated by reanalysis based on hrsl data of Sri Lanka. Hrsl data provides an estimate of the population distribution in 2015 at a resolution of 1 arcsec (about 30 meters). The latest census information and built-up area information based on satellite images are used in hrsl data. This data set is based on hrsl data. Firstly, the boundary of buildings is extracted from the 0.5m resolution remote sensing image by computer vision technology, and the building types (high-rise buildings, medium and low rise buildings, bungalows, etc.) are determined by combining with manual visual interpretation and field sampling. The population distribution area mask is constructed in the building area, and the 10 meter grid is used as the analysis unit to calculate the population distribution in the unit According to the proportion of different building types, the proportion of main land use types, building density, distance from road and other related indicators, the average density of building type consistent area is calculated from hrsl data, and the corresponding population density of each building is obtained by machine learning method. Then, the population data in the area is allocated to the corresponding unit by proportional allocation method, and the 10 meter resolution is obtained Population distribution products. The data is distributed in the form of GeoTIFF files. Population GeoTIFF represents population estimates (in person) and provides detailed estimates for population, infrastructure and Sustainability Studies in the humanitarian field.
The data set of socio-economic vulnerability parameters in the agricultural and pastoral areas of the Qinghai Tibet Plateau mainly contains the socio-economic vulnerability parameter data at county level. The data time range is from 2000 to 2015, involving 112 counties and districts in Qinghai Province and Tibet Autonomous Region. The main parameters include population density, the proportion of unit employees in the total population, the proportion of rural employees in the total population, the proportion of agricultural, forestry, animal husbandry and fishery employees in rural employees, per capita GDP, per capita savings balance of residents, per capita cultivated land area, per capita grain output, and people Average oil production, livestock stock per unit area, per capita meat production, the proportion of primary and secondary school students in the total population, and the number of hospital beds per 10000 people. The entropy weight method is used to calculate the weight of each index, and ArcGIS is used to spatialize, and finally the county scale socio-economic vulnerability parameter data is obtained. The original data is from the statistical yearbook of Qinghai Province and Tibet Autonomous Region. The data are expressed by shape file and excel file. This data set will provide reference for socio-economic vulnerability assessment and selection of typical agricultural and pastoral areas.
ZHAN Jinyan, TENG Yanmin, LIU Shiliang
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
This data set includes a monthly composite of 30 m × 30 m surface vegetation coverage products in the Qilian Mountain Area in 2019. In this paper, the maximum value composition (MVC) method is used to synthesize monthly NDVI products and calculate FVC by using the reflectance data of Landsat 8 and sentinel 2 red and near infrared channels. The data is monthly synthesized by Google Earth engine cloud platform, and the index is calculated by the model. The missing pixels are interpolated with good quality, which can be used in environmental change monitoring and other fields.
QI Xuebin
The data includes the runoff components of the main stream and four tributaries in the source area of the Yellow River. In 2014-2016, spring, summer and winter, based on the measurement of radon and tritium isotopic contents of river water samples from several permafrost regions in the source area of the Yellow River, and according to the mass conservation model and isotope balance model of river water flow, the runoff component analysis of river flow was carried out, and the proportion of groundwater supply and underground ice melt water in river runoff was preliminarily divided. The quality of the data calculated by the model is good, and the relative error is less than 20%. The data can provide help for the parameter calibration of future hydrological model and the simulation of hydrological runoff process.
QI Xuebin
1) Data content: this data is the placenta umbilical cord endothelial cells (HUVEC) transcriptome data of high altitude Tibetan and lowland Han population generated during the implementation of the project, including the RNA-seq data of 3 high altitude Tibetan HUVEC and 3 lowland Han placenta HUVEC. Each RNA-seq data is 6G sequencing depth, which can be used to study the effect of high altitude Tibetan population and lowland Han population for gene expression patterns at hypoxic environment. 2) Data source and processing method: own data, the pair end 150bp sequencing method using Illumina x-ten sequencing platform. 3) Data quality: 6G data depth, q30 > 90%. 4) Results and prospects of data application: the data will be used to validate the gene expression pattern of high altitude hypoxia adaptation gene to hypoxia environment at the cell level.
QI Xuebin
The average altitude of the Tibetan Plateau is more than 4000 meters. The harsh environment such as high cold and low oxygen poses a huge challenge to human survival. However, since the late Paleolithic period, Tibetan people in the plateau have reached the Plateau, and in the Neolithic period, people began to permanently settled on the high-altitude areas on a large scale. The history of population migration in this process has become the focus of different fields. In order to analyze the genetic structure of Tibetan population from the perspective of the whole genome and trace back the history of human settlement on the plateau, we obtained the whole genome variation data of 20 Tibetan individuals. The SNP typing of 20 samples was carried out by DNA array method, and about 700000 loci (including nuclear genome, mitochondrial DNA and Y chromosome) of each sample were obtained. Based on the above data, relevant biological information analysis (mainly including chip site quality control analysis, Y chromosome and mitochondrial DNA haplotype analysis) was carried out. This data is helpful to analyze the genetic structure of Tibetan population from the perspective of nuclear genome, Y chromosome and mitochondrial DNA. By comparing with the data of people around the plateau, we can trace the migration and settlement history of the plateau population comprehensively.
KONG Qingpeng
How the Tibetan people adapt to the extreme environment of the plateau is not clear at present. Metabolism, as an important phenotype, plays an important role in maintaining the normal biological function of individuals. Previous studies have shown that some small metabolic molecules can adapt to the extreme environment by regulating the biological processes such as energy metabolism and oxidative stress. In view of this, this project is to find the relationship between the human metabolism and the extreme environmental adaptation by studying the unique metabolic characteristics of Tibetan population compared with the plain population, and then study the plateau adaptation mechanism of Tibetan population from the perspective of metabolism. This data is the metabolome data generated during the implementation of this project. The current data includes the metabolome data of 30 people in the plain. The combined analysis of this data and the subsequent metabolome data can be used to study the metabolism characteristics of the Tibetan people at high altitude in the low oxygen environment.
LI Gonghua
Gridded population with 100m spaital resolution of the 34 key areas along One Belt One Road in 2010, which indicates that the population count (Unit: person) 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 2010. 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, LI Qiangzi, DONG Wen
"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
"One belt, one road" along the lines of risk rating, credit risk rating and Moodie's national sovereignty rating reflects the structure of sovereign risk in every country. The rating of Moodie's national sovereignty is from the highest Aaa to the lowest C level, and there are twenty-one levels. Data source: organized by the author. Data quality is good. The rating level is divided into two parts, including investment level and speculation level. AAA level is the highest, which is the sovereign rating of excellent level. It means the highest credit quality and the lowest credit risk. The interest payment has sufficient guarantee and the principal is safe. The factors that guarantee the repayment of principal and interest are predictable even if they change. The distribution position is stable. C is the lowest rating, indicating that it cannot be used for real investment.
SONG Tao
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
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 dataset, based on night light data and macro statistical data, uses remote sensing inversion method（1km*1km）to obtain the poverty rate in different regions within each country. It has three advantages. a) The calculation unit can be adjusted according to the boundaries of administrative regions to reflect the poverty rate of sub-regions within the large country and scale, which is rare in statistically data. b) The survey and summary cycle limits the updating of national and sub-regional poverty rate, while the method based on night light data is more convenient. c) Due to the continuous annual data of night light, the difficulty of obtaining regional poverty rate in a long period was overcome. In view of the three outstanding advantages mentioned above, this data set can support to achieve the research subjects and provide scientific data for understanding the basic situation of poverty along the Silk Roads.
ZHANG Qian, Linxiu ZHANG
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
1) data content: social and economic data of major countries and regions in the pan third polar region, including four categories: urbanization index, economic and industrial index, population index and social index, including urbanization rate, total population, population in the largest city, population, GDP, life expectancy and other indicators in the urban agglomeration with population over 1 million; 2) data source and processing method: data source World Bank, 65 countries and regions of Pan third pole are extracted, others are not processed; 3) data quality description: some data are missing from 1960-1992; 4) data application results and prospects: it can be used for urbanization and other socio-economic analysis.
LI Guangdong
This data includes future population and GDP estimates based on the SSP2 scenario at the Mekong basin grid scale. The data comes from the global population projection data with a spatial resolution of 5 minutes (about 10km) and the GDP projection data with a spatial resolution of 0.5 degrees (about 50km) provided by the ISIMIP. The method of spatial interpolation is used to get 0.25-degree population projection data from 5-min population projection, and 0.5-degree GDP projection data is downscaled to obtain the 0.25 degree GDP data. The data provided by ISIMIP has passed the data with good quality control, and has not been further verified after data interpolation. The data can be used for the socio-economic impact assessment of climate change and extreme climate events in the Mekong River Basin.
LIU Xingcai
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
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 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
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
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
One belt, one road, 64 countries in 2017 accounted for the total population of the country. Data source: organized by the author. Data quality is good. The data can have one broad prospect in one belt, one road, and the other is comprehensive research on economy, society, population and governance structure. "One belt, one road" covers Asia Pacific, Eurasia, Middle East, Africa, etc., including 65 countries, with a total population of over 4 billion 400 million, accounting for 63% of the world's population. One belt, one road, one belt, one road, one belt, one road, one country, one country, and one country.
SONG Tao
One belt, one road, in 2017, the proportion of religious population in 64 countries is the total population. Data source: organized by the author. Data quality is good. The data can have one broad prospect in one belt, one road, and the other is comprehensive research on economy, society, population and governance structure. "One belt, one road" covers Asia Pacific, Eurasia, Middle East, Africa, etc., including 65 countries, with a total population of over 4 billion 400 million, accounting for 63% of the world's population. One belt, one road, one belt, one road, one belt, one road, one area, and the other two. The first one is to make contributions to the systematic research and comprehensive application of the whole area.
SONG Tao
The dataset records 1960-2017 years of urban population statistics in 65 along the Belt and Road.Data sources: (1) United Nations Population Division. World Population Prospects: 2017 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. The data set contains 3 tables: (1))Urban population;(2)Urban population (% of total population;(3)Urban population growth (annual %).
XU Xinliang
The data recorded one belt, one road, 65 countries, 1990-2017 years of labor force. The labor force includes people aged 15 and over who provide labor for the production of goods and services in a specific period of time. It includes those who are currently employed and those who are unemployed but seeking work, as well as first-time job seekers. Data source: according to the data of the ILO, the ILO and the world bank population estimates. Labor data retrieved in September 2018. The data set reflects one belt, one road, the state of labor resources in the countries along the route, and is also an important part of the basic national conditions, and is also one of the important bases for formulating economic and social development strategies.
XU Xinliang
The dataset records 1960-2017 years of rural population statistics in 65 along the Belt and Road.Data sources: (1) United Nations Population Division. World Population Prospects: 2017 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. The data set contains 3 tables: (1))Rural population;(2)Rural population (% of total population;(3)Rural population growth (annual %).
XU Xinliang
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
The data set records one belt, one road, 65 years' 1960-2017 years population age composition, including the age group population and its proportion in the total population. Data sources: (1) United Nations Population Division, world population prospects: 2017, 2018 revision; (2) census reports and other statistical publications of the National Bureau of statistics; (3) Eurostat: population statistics; (4) United Nations Statistics Division, population and vital statistics reports (different years); (5) United States Census Bureau: international database; (6) Pacific Community Secretariat: statistical and demographic programme. One belt, one road, the future population development, and the future development of social economy. The data set contains six data tables: the total population aged 0-14, the proportion aged 0-14, the total population aged 15-64, the proportion aged 15-64 women, the total population aged 65 and above, and the proportion aged 65 and above
XU Xinliang
The data set records one belt, one road, 1960-2017 countries' population data along 65 countries. The total population is the sum of population groups living in a certain time and a certain area. Population density is the number of people per unit land area. Population growth rate is the rate of population growth caused by natural and migration changes in a certain period of time. Total population, population density and population growth rate are the most basic indicators in population statistics. They are of great significance for understanding national conditions and national strength, formulating population plans and economic and social development plans, and carrying out population scientific research. Data sources: (1) United Nations Population Division, world population prospects: 2017, 2018 revision; (2) census reports and other statistical publications of the National Bureau of statistics; (3) Eurostat: population statistics; (4) United Nations Statistics Division, population and vital statistics reports (different years); (5) United States Census Bureau: international database; (6) Pacific Community Secretariat: statistical and demographic programme. The data set contains three data tables: total population, population density, population growth rate,
XU Xinliang
The data set records the proportion of male and female data of 1960-2017 countries along 65 countries along the belt and road. Data sources: (1) United Nations Population Division. World Population Prospects: 2017 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. The data set contains 4 tables：(1)Population, male;(2)Population, male (% of total);(3)Population, female;(4)Population, female (% of total).
XU Xinliang
The contents include five Central Asian countries, Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan and Uzbekistan. The basic socio-economic indicators from 2012 to 2017 are divided into 12 categories: GDP, price, industry, agriculture, animal husbandry, construction, capital investment, transportation, foreign trade, labor market, wages, living standards and the exchange rate of the US dollar. Developments and changes. The data comes from ww. cisstat. com. The original index name is Russian, which is translated and edited. The accurate official data can provide basic data basis for the study of social and economic development in Central Asian countries.
BAO Shaoyong
The data set records the urbanization rate data of each state of Uzbekistan from 2000 to 2017.The data is from Uzbekistan's national statistics bureau. Urbanization is a concept with broad implications.In a narrow sense, it generally refers to the urbanization of population, which refers to the increase of the number of cities and the expansion of the urban scale, and the process of population aggregation to cities in a certain period.Urbanization rate refers to the proportion of permanent urban residents in a region in the total permanent resident population.The name of the original index is Russian, which has been translated and edited.The accuracy of the official data can provide basic data basis for the study of the socio-economic development of central Asian countries.
Kazakhstan National Bureau Of Statistics, HUANG Jinchuan, MA Haitao
The data set records the urbanization rate data of each state of Tajikistan from 2000 to 2016.The data is from kazakhstan's national statistics bureau. Urbanization is a concept with broad implications.In a narrow sense, it generally refers to the urbanization of population, which refers to the increase of the number of cities and the expansion of the urban scale, and the process of population aggregation to cities in a certain period.Urbanization rate refers to the proportion of permanent urban residents in a region in the total permanent resident population.The name of the original index is Russian, which has been translated and edited.The accuracy of the official data can provide basic data basis for the study of the socio-economic development of central Asian countries.
HUANG Jinchuan, MA Haitao
The distribution data of Central Asia desert oil and gas fields are in the form of vector data in ". SHP". Including the distribution of oil and gas fields and major urban settlements in the five Central Asian countries. The data is extracted and cut from modis-mcd12q product. The spatial resolution of the product is 500 m, and the time resolution is 1 year. IGBP global vegetation classification scheme is adopted as the classification standard. The scheme is divided into 17 land cover types, among which the urban data uses the construction and urban land in the scheme. The data can provide data support for the assessment and prevention of sandstorm disasters in Central Asia desert oil and gas fields and green town.
GAO Xin
Gridded population with 100m spaital resolution of the 8 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
Gridded population with 1km 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 socioeconomic data and applications center of Columbia University, USA. The prejection transform and extraction processes were done to generate the gridded population with 1km spaital resolution of the 34 key areas along One Belt One Road in 2015. The original gridded popution is spatially downscaled from census data by the area weighted method for each administrative unit. Accurate population data at grid level 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
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
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
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
The data set contains data on the birth rate, mortality rate and natural growth rate in Tibet. 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. The table contains 4 fields. Field 1: Year of the data Field 2: Birth rate, unit: ‰ Field 3: Mortality rate, unit:‰ Field 4: Natural growth rate, unit: ‰
National Bureau of Statistics
The data set contains series data of populations of major cities and counties on the Tibetan Plateau from 1970 to 2006. It is used to study social and economic changes on the Tibetan Plateau. The table has six fields. Field 1: Year Interpretation: Year of the data Field 2: Province Interpretation: The province from which the data were obtained Field 3: City/Prefecture Interpretation: The city or prefecture from which the data were obtained Field 4: County Interpretation: The name of the county Field 5: Population (10,000) Interpretation: Population Field 6: Data Sources Interpretation: Source of Data Extraction The data comes from the statistical yearbook and county annals of Tibet Autonomous Region, Qinghai, Sichuan, Gansu, Yunnan and Xinjiang. Some are listed as follows: [1] Gansu Yearbook Editorial Committee. Gansu Yearbook [J]. Beijing: China Statistics Press, 1984, 1988-2009 [2] Statistical Bureau of Yunnan Province. Yunnan Statistical Yearbook [J]. Beijing: China Statistics Press, 1988-2009 [3] Statistical Bureau of Sichuan Province, Sichuan Survey Team. Sichuan Statistical Yearbook [J]. Beijing: China Statistics Press, 1987-1991, 1996-2009 [4] Statistical Bureau of Xinjiang Uighur Autonomous Region . Xinjiang Statistical Yearbook [J]. Beijing: China Statistics Press, 1989-1996, 1998-2009 [5] Statistical Bureau of Tibetan Autonomous Region. Tibet Statistical Yearbook [J]. Beijing: China Statistics Press, 1986-2009 [6] Statistical Bureau of Qinghai Province. Qinghai Statistical Yearbook [J]. Beijing: China Statistics Press, 1986-1994, 1996-2008. [7] County Annals Editorial Committee of Huzhu Tu Autonomous County. County Annals of Huzhu Tu Autonomous County [J]. Qinghai: Qinghai People's Publishing House, 1993 [8] Haiyan County Annals Editorial Committee. Haiyan County Annals[J]. Gansu: Gansu Cultural Publishing House, 1994 [9] Menyuan County Annals Editorial Committee. Menyuan County Annals[J]. Gansu: Gansu People's Publishing House, 1993 [10] Guinan County Annals Editorial Committee. Guinan County Annals [J]. Shanxi: Shanxi People's Publishing House, 1996 [11] Guide County Annals Editorial Committee. Guide County Annals[J]. Shanxi: Shanxi People's Publishing House, 1995 [12] Jianzha County Annals Editorial Committee. Jianzha County Annals [J]. Gansu: Gansu People's Publishing House, 2003 [13] Dari County Annals Editorial Committee. Dari County Annals [J]. Shanxi: Shanxi People's Publishing House, 1993 [14] Golmud City Annals Editorial Committee. Golmud City Annals [J]. Beijing: Fangzhi Publishing House, 2005 [15] Delingha City Annals Editorial Committee. Delingha City Annals [J]. Beijing: Fangzhi Publishing House, 2004 [16] Tianjun County Annals Editorial Committee. Tianjun County Annals [J]. Gansu: Gansu Cultural Publishing House, 1995 [17] Naidong County Annals Editorial Committee. Naidong County Annals [J]. Beijing: China Tibetology Press, 2006 [18] Gulang County Annals Editorial Committee. Gulang County Annals [J]. Gansu: Gansu People's Publishing House, 1996 [19] County Annals Editorial Committee of Akesai Kazak Autonomous County. County Annals of Akesai Kazakh Autonomous County [J]. Gansu: Gansu People's Publishing House, 1993 [20] Minxian County Annals Editorial Committee. Minxian County Annals [J]. Gansu: Gansu People's Publishing House, 1995 [21] Dangchang County Annals Editorial Committee. Dangchang County Annals [J]. Gansu: Gansu Cultural Publishing House, 1995 [22] Dangchang County Annals Editorial Committee. Dangchang County Annals(Sequel) (1985-2005) [J]. Gansu: Gansu Cultural Publishing House, 2006 [23] Wenxian County Annals Editorial Committee. Wenxian County Annals[J]. Gansu: Gansu Cultural Publishing House, 1997 [24] Kangle County Annals Editorial Committee. Kangle County Annals [J]. Shanghai: Sanlian Bookstore. 1995 [25] County Annals Editorial Committee of Jishishan (Baoan, Dongxiang, Sala) Autonomous County. County Annals of Jishishan (Baoan, Dongxiang, Sala) Autonomous County[J], Gansu: Gansu Cultural Publishing House, 1998 [26] Luqu County Annals Editorial Committee. Luqu County Annals [J]. Gansu: Gansu People's Publishing House, 2006 [27] Zhouqu County Annals Editorial Committee. Zhouqu County Annals [J]. Shanghai: Sanlian Bookstore. 1996 [28] Xiahe County Annals Editorial Committee. Xiahe County Annals [J]. Gansu: Gansu Cultural Publishing House, 1999 [29] Zhuoni County Annals Editorial Committee. Zhuoni County Annals [J]. Gansu: Gansu Nationality Publishing House, 1994 [30] Diebu County Annals Editorial Committee. Diebu County Annals [J]. Gansu: Lanzhou University Press, 1998 [31] Pengxian County Annals Editorial Committee. Pengxian County Annals [J]. Sichuan: Sichuan People's Publishing House, 1989 [32] Guanxian County Annals Editorial Committee. Guanxian County Annals [J]. Sichuan: Sichuan People's Publishing House, 1991 [33] Wenjiang County Annals Editorial Committee. Wenjiang County Annals [J]. Sichuan: Sichuan People's Publishing House, 1990 [34] Shifang County Annals Editorial Committee. Shifang County Annals [J]. Sichuan: Sichuan University Press, 1988 [35] Tianquan County Annals Editorial Committee. Tianquan County Annals [J]. Sichuan: Sichuan Science and Technology Press, 1997 [36] Shimian County Annals Editorial Committee. Shimian County Annals [J]. Sichuan: Sichuan Cishu Publishing House, 1999 [37] Lushan County Annals Editorial Committee. Lushan County Annals [J]. Sichuan: Fangzhi Publishing House, 2000 [38] Hongyuan County Annals Editorial Committee. Hongyuan County Annals [J]. Sichuan: Sichuan People's Publishing House, 1996 [39] Wenchuan County Annals Editorial Committee. Wenchuan County Annals [J]. Sichuan: Bayu Shushe, 2007 [40] Derong County Annals Editorial Committee. Derong County Annals [J]. Sichuan: Sichuan University, 2000 [41] Baiyu County Annals Editorial Committee. Baiyu County Annals [J]. Sichuan: Sichuan University Press, 1996 [42] Batang County Annals Editorial Committee. Batang County Annals [J]. Sichuan: Sichuan Nationality Publishing House, 1993 [43] Jiulong County Annals Editorial Committee. Jiulong County Annals(Sequel) (1986-2000) [J]. Sichuan: Sichuan Science and Technology Press, 2007 [44] County Annals Editorial Committee of Derung-Nu Autonomous County Gongshan. County Annals of Derung-Nu Autonomous County Gongshan [J]. Beijing: Nationality Publishing House, 2006 [45] Lushui County Annals Editorial Committee. Lushui County Annals [J]. Yunnan: Yunnan People's Publishing House, 1995 [46] Deqin County Annals Editorial Committee. Deqin County Annals [J]. Yunnan: Yunnan Nationality Publishing House, 1997 [47] Yutian County Annals Editorial Committee. Yutian County Annals [J]. Xinjiang: Xinjiang People's Publishing House, 2006 [48] Cele County Annals Editorial Committee. Cele County Annals [J]. Xinjiang: Xinjiang People's Publishing House, 2005 [49] Hetian County Annals Editorial Committee. Hetian County Annals [J]. Xinjiang: Xinjiang People's Publishing House, 2006 [50] Qiemo County Local Chronicles Editorial Committee. Qiemo County Annals [J]. Xinjiang: Xinjiang People's Publishing House, 1996 [51] Shache County Annals Editorial Committee. Shache County Annals [J]. Xinjiang: Xinjiang People's Publishing House, 1996 [52] Yecheng County Annals Editorial Committee. Yecheng County Annals [J]. Xinjiang: Xinjiang People's Publishing House, 1999 [53] Akto County Local Chronicles Editorial Committee. Akto County Annals [J]. Xinjiang: Xinjiang People's Publishing House, 1996 [54] Wuqia County Local Chronicles Editorial Committee. Wuqia County Annals [J]. Xinjiang: Xinjiang People's Publishing House, 1995
National Bureau of Statistics
Taking 2005 as the base year, the future population scenario was predicted by adopting the Logistic model of population. It not only can better describe the change pattern of population and biomass but is also widely applied in the economic field. The urbanization rate was predicted by using the urbanization Logistic model. Based on the existing urbanization horizontal sequence value, the prediction model was established by acquiring the parameters in the parametric equation by nonlinear regression. The urban population was calculated by multiplying the predicted population by the urbanization rate. The data adopted the non-agricultural population. The Logistic model was used to predict the future gross national product of each county (or city), and then, according to the economic development level of each county (or city) in each period (in terms of GDP per capita),the corresponding industrial structure scenarios in each period were set, and the output value of each industry was predicted. The trend of changes in industrial structure in China and the research area lagged behind the growth of GDP and was therefore adjusted according to the need of the future industrial structure scenarios of the research area.
ZHONG Fanglei
Taking 2005 as the base year, the future population scenario prediction adopted the Logistic model of population; not only is it better able to describe the change pattern of population and biomass, but it is also widely applied in the economic field. The urbanization rate was predicted using the urbanization Logistic model. Based on the existing urbanization horizontal sequence value, the prediction model was established by acquiring the parameters in the parametric equation applying nonlinear regression. The urban population was calculated by multiplying the predicted population by the urbanization rate. The Logistic model was used to predict the future gross national product of each county (or city), and then according to the economic development level of each county (or city) in each period (in terms of real GDP per capita), the corresponding industrial structure scenarios in each period were set, and the output value of each industry was predicted. The trend of changing industrial structure in China and the research area lagged behind the growth of GDP and was therefore adjusted according to the need of the future industrial structure scenarios of the research area.
YANG Linsheng, ZHONG Fanglei
By applying Supply-demand Balance Analysis, the water resource supply and demand of the whole river basin and each county or district were calculated, on which basis 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 predicted. 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 for the water resources allocation of the basin, a water distribution plan was set up to calculate the water supply comprehensively. Considering 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
Taking 2000 as the base year, the future population scenario prediction adopted the Logistic model of population, and it not only can better describe the change pattern of population and biomass but also is widely applied in the economic field. The urbanization rate was predicted using the urbanization Logistic model. Based on the existing urbanization horizontal sequence value, the prediction model was established by acquiring the parameters in the parametric equation applying nonlinear regression. The urban population was calculated by multiplying the predicted population by the urbanization rate. The Logistic model was used to predict the future gross national product of each county (or city), and then, according to the economic development level of each county (or city) in each period (in terms of real GDP per capita), the corresponding industrial structure scenarios in each period were set, and the output value of each industry was predicted. The trend of industrial structure changing in China and the research area lagged behind the growth of GDP, so it was adjusted according to the need of the future industrial structure scenarios of the research area.
ZHONG Fanglei
By applying supply-demand balance analysis, the water resource supply and demand of the whole river basin and each county or district were calculated, and the results were used to assess the vulnerability of the water resources system in the basin. The IPAT equation was used to establish a future water resource demand scenario, which involved setting various variables, such as the future population growth rate, economic growth rate, and water consumption per unit GDP. 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 predicted. By applying the basic structure of the HBV conceptual hydrological model of the Swedish Hydro-meteorological Institute, a model of the variation trends of the basin under a changing climate was designed. The glacial melting scenario was used as the model input to construct the runoff scenario in response to climate change. According to the national regulations of the water resource allocation in the basin, a water distribution plan was set up to calculate the water supply comprehensively. Considering the supply and demand situation, the water resource system vulnerability was evaluated by the water shortage rate. By calculating the grain production-related land pressure index of the major counties and cities in the basin, the balance of supply and demand of land resources in scenarios of climate change, glacial melting and population growth was analysed, 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 in the future, and the vulnerability of ecosystems from the perspective of supply and demand balance was assessed.
YANG Linsheng, ZHONG Fanglei
Taking 2005 as the base year, the future population scenario was predicted by adopting the logistic model of population. This model not only effectively describes the pattern of changes in population and biomass but is also widely applied in the field of economics. The urbanization rate was predicted using the urbanization logistic model. Based on the observed horizontal pattern of urbanization, a predictive model was established by determining the parameters in the parametric equation by applying nonlinear regression. The urban population was calculated by multiplying the predicted population by the urbanization rate. The data represent the non-agricultural population. The logistic model was used to predict the future gross domestic product of each county (or city), and then the economic development level of each county (or city) in each period (in terms of GDP per capita). The corresponding industrial structure scenarios in each period were set, and the output value of each industry was predicted. The trend of industrial structure changes in China and the research area lagged behind the growth in GDP, so the changes were adjusted according to the need for future industrial structure scenarios in the research area.
YANG Linsheng, ZHONG Fanglei
The main body of the Tibetan Plateau is Qinghai Province and the Tibetan Autonomous Region. The economic and social data of Qinghai Province and the Tibetan Autonomous Region are the basis for the analysis and assessment of the basic data of sustainable development of populations, resources, environment and economic society on the Tibetan Plateau by integrating the basic data of natural sciences. Under normal circumstances, the statistical yearbooks of all provinces and regions are all in paper and CD-ROM versions, and users need to perform secondary editing before they can use them. This data set mainly relies on the raw data of the Statistical Yearbook of Qinghai Province and the Tibetan Autonomous Region to carry out data conversion and integrate the current economic and social data sets. The temporal coverage of the data is from 2007 to 2016, and the temporal resolution is one year. The spatial coverage is Qinghai Province and the Tibetan Autonomous Region of the Tibetan Plateau. The spatial resolution is the administrative unit of the prefecture or city. The data include information on population, economy, finance, agriculture, forestry, animal husbandry and fishery, investment in fixed assets, education and health.
WANG Shijin
Taking 2005 as the base year, the future population scenario prediction adopted the Logistic model of population, and it not only can better describe the change pattern of population and biomass but is also widely applied in the economic field. The urbanization rate was predicted using the urbanization Logistic model. Based on the existing urbanization horizontal sequence value, the prediction model was established by acquiring the parameters in the parametric equation applying nonlinear regression. The urban population was calculated by multiplying the predicted population by the urbanization rate. The Logistic model was used to predict the future gross national product of each county (or city), and then, according to the economic development level of each county (or city) in each period (in terms of real GDP per capita),the corresponding industrial structure scenarios in each period were set, and each industry’s output value was predicted. The trend of changes in industrial structure in China and the research area lagged behind the growth of GDP, and, therefore, it was adjusted according to the need of the future industrial structure scenarios of the research area.
ZHONG Fanglei, YANG Linsheng
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
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
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
Contact Support
Northwest Institute of Eco-Environment and Resources, CAS
0931-4967287
poles@itpcas.ac.cn
Links
National Tibetan Plateau Data CenterFollow Us
A Big Earth Data Platform for Three Poles © 2018-2020 No.05000491 | All Rights Reserved
｜ 
No.11010502040845
Tech Support: westdc.cn
