Data content: money supply (2012-2021) and assets and liabilities of financial institutions (2007-2020) Data source and processing method: The original data of the third pole (China) banks and currencies from 2015 to 2021 were obtained from the official website of the World Bank and Sina.com, and the data set of the third pole (China) banks and currencies from 2012 to 2021 was obtained through data sorting, screening and cleaning. The data started from 2012 to 2021 in Microsoft Excel (xls) format. Data quality description: excellent Data application achievements and prospects: provide effective reference as socio-economic data
FU Wenxue
Data content: price index_ Consumer Price Index (CPI) (2009-2022) Data source and processing method: The original data of the third pole (China) price index economy from 2015 to 2022 were obtained from the official website of the World Bank and Sina.com, and the economic data set of the third pole (China) price index from 2009 to 2022 was obtained through data collation, screening and cleaning. The data started from 2009 to 2022 in Microsoft Excel (xls) format. Data quality description: excellent Data application achievements and prospects: provide effective reference as socio-economic data
FU Wenxue
Data content: annual statistics of gross domestic product (GDP) (1991-2021), domestic assets and liabilities data (2011-2020) and domestic input and output data (2012-2018) Data source and processing method: The original macroeconomic data of the third pole (China) from 2015 to 2021 were obtained from the official website of the World Bank and Sina.com, and the macroeconomic data set of the third pole (China) from 1991 to 2021 was obtained through data sorting, screening and cleaning. The data was stored in Microsoft Excel (xls) format. Data quality description: excellent Data application achievements and prospects: provide effective reference as socio-economic data
FU Wenxue
Data content: foreign economy and trade_ Total import and export of goods (1991-2021) Data source and processing method: The original data of foreign trade and investment of the third pole (China region) from 2015 to 2021 were obtained from the official website of the World Bank and Sina.com, and the data set of foreign trade and investment of the third pole (China region) from 1991 to 2021 was obtained through data sorting, screening and cleaning. The data started from 1991 to 2021 in Microsoft Excel (xls) format. Data quality description: excellent Data application achievements and prospects: provide effective reference as socio-economic data
FU Wenxue
This data set is the daily vorticity related flux observation data of Naqu flux station (31.64 ° N 92.01 ° E, 4598 m a.s.l.), including ecosystem net ecosystem productivity (NEP), total primary productivity (GPP) and ecosystem respiration (ER) data. The main steps of data pre-processing include wild point removal (± 3 σ）、 Coordinate axis rotation (3D wind rotation), Webb Pearman Leuning correction, outlier elimination, carbon flux interpolation and decomposition, etc. Missing data are interpolated through the nonlinear empirical formula between CO2 flux value (Fc) and environmental factors.
ZHANG Yangjian
This dataset is the daily vorticity related flux observation data of Naqu flux station (31.64 ° N 92.01 ° E, 4598 m a.s.l.), including net ecosystem productivity (NEP), total primary productivity (GPP), ecosystem respiration (ER), evapotranspiration, latent heat, sensible heat, air temperature, relative humidity, wind speed, soil temperature, soil moisture and other data. The main steps of data pre-processing include wild point removal (± 3 σ）、 Coordinate axis rotation (3D wind rotation), Webb Pearman Leuning correction, outlier elimination, carbon flux interpolation and decomposition, etc. Missing data are interpolated through the nonlinear empirical formula between CO2 flux value (Fc) and environmental factors.
ZHANG Yangjian
Data content: Industrial added value of national economy (monthly) (2010-2021) Data source and processing method: obtain the original data of the third pole (China) industrial economy in 2010-2021 from the official website of the World Bank and Sina.com, and obtain the industrial economy data set in 2010-2021 (China) through data sorting, screening and cleaning. The data starts from 2010 to 2021 in Microsoft Excel (xls) format. Data quality description: excellent Data application achievements and prospects: provide effective reference as social, industrial and economic data
FU Wenxue
The data set includes the implied water resources and land resource flows among 11 cities and counties in the Heihe River basin, including Ganzhou, Sunan, Minle, Linze, Gaotai, Shandan, Suzhou, Jinta, Jiayuguan and Ejina. Table 1 includes the transfer volume of virtual water resources and virtual land resources among multiple regions. Table 2 includes the virtual water resources export volume of each regional sub sector and the virtual water resources import volume of each regional sub sector. Table 3 includes the export volume of virtual land resources of each regional sub sector and the import volume of virtual land resources of each regional sub sector. Based on the input-output tables of 11 cities and counties in the Heihe River Basin, we investigate the consumption, loss and flow of water and land resources in each economic sector, construct a coupled water-land resource accounting statement, and calculate the virtual water resources and virtual land resources flow by sector in each region based on the input-output analysis method. The water consumption and land use data of each region and sector are obtained from official statistical yearbook data.
CHEN Bin
Provide detailed spatial distribution of GDP data in China from 1990 to 2015 year by year. The data is 1km grid data, and the unit is 10000 yuan / square kilometer. This grid data comprehensively considers multiple factors for weight allocation to realize the spatialization of GDP, which is convenient for data sharing and spatial statistical analysis. The data comes from the resource and environment science data registration and publication system. The year-on-year data is obtained by linear interpolation of the original data, and is saved in GeoTIFF file format. The methods and standards of data over the years are consistent, the coverage is complete, and the collection and processing process is traceable and reliable.
WANG Can , WANG Jiachen
Based on the non survey method, referring to the provincial input-output table and county-level statistical data of the Qilian Mountain region, the project compiled the input-output table of the Qilian Mountain Region in 2017. This table provides a data basis for analyzing the production and consumption of regional economy and the virtual water resources contained in its products or services. The input-output table uses the input-output tables of Qinghai Province, Inner Mongolia Autonomous Region and Gansu Province in 2017, analyzes the industrial production, residents' consumption and interregional trade information of districts and counties included in the Qilian Mountains, and constructs the input-output table of the Qilian Mountains. The input-output table is the characterization of the regional macroeconomic structure and the level of regional products or services.
WU Feng
Vulnerability of disaster bearing body is the degree of damage that human social and economic activities may suffer under the disturbance or pressure of natural disasters under a certain social and economic background, that is, the nature that disaster bearing body is vulnerable to damage and loss in the face of natural disasters. Based on the actual scientific research and expert guidance, this data constructs the vulnerability assessment indicators of disaster bearing bodies from the three aspects of exposure, sensitivity and adaptability, and uses the revised serv vulnerability model to calculate the Himalayan surrounding areas (domestic part) and the Asian water tower area. In order to systematically analyze the vulnerability of disaster bearing bodies in the study area, this data selects indicators from six aspects: population, economy, traffic lines, ecological environment, livestock and buildings, and constructs an indicator system of 6 first-class indicators, 18 second-class indicators and 29 third-class indicators. After the obtained vulnerability assessment results of population, economy, traffic lines, ecological environment, livestock and buildings are normalized, the vulnerability assessment maps of Himalayan surrounding areas (domestic part) and Asian water tower area are obtained by vector superposition.
ZHOU Qiang, CHEN Yingming , LIU Fenggui, CHEN Ruishan , CHEN Qiong, XIA Xingsheng , NIU Baicheng , DUAN Yufang
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 health care development in countries along the Belt and Road reflects the level of resilience of health care development in the countries along the Belt and Road, and the higher the value of the data, the stronger the resilience of health care development in the countries along the Belt and Road. The World Bank statistical database was used for the preparation of the health resilience data. Based on the year-on-year data of these four indicators, and taking into account the year-on-year changes of each indicator, the product of resilience in the development of healthcare conditions was prepared through comprehensive diagnosis based on sensitivity and adaptability analysis. "The Resilience in Health Care Development dataset for countries along the Belt and Road is an important reference for analysing and comparing the current resilience in health care development in each country.
XU Xinliang
The development resilience of social employment in the countries along the Belt and Road reflects the level of resilience of social employment in the countries along the Belt and Road, and the higher the value of the data, the stronger the development resilience of social employment in the countries along the Belt and Road. The data product of social employment development resilience is prepared by referring to the World Bank statistical database, using the year-by-year data of the ratio of total unemployment to total labour force in the countries along the Belt and Road from 2000 to 2019, and based on sensitivity and adaptability analysis by considering the year-by-year changes of each indicator. A comprehensive diagnostic was carried out to generate a resilience product for the development of social employment. "The data set on the resilience of social employment development in the countries along the Belt and Road is an important reference for analysing and comparing the resilience of the current population growth in each country.
XU Xinliang
The resilience of education in Belt and Road countries reflects the level of resilience of education in the countries along the Belt and Road, and the higher the value, the stronger the resilience of education in the countries along the Belt and Road. The data on the resilience of educational conditions are prepared by referring to the World Bank's statistical database, using year-on-year data on four indicators - literacy rate, education expenditure, secondary school enrolment rate and tertiary enrolment rate - for countries along the Belt and Road from 2000 to 2019, and taking into account the year-on-year changes in each indicator. Based on the sensitivity and adaptability analysis, a comprehensive diagnosis was carried out to generate a resilience product for the development of education conditions. "The data set on the resilience of educational conditions in countries along the Belt and Road is an important reference for analysing and comparing the current resilience of educational conditions in each country.
XU Xinliang
The GDP per capita growth resilience dataset for countries along the Belt and Road is a comprehensive reflection of the level of GDP per capita growth resilience of each country. The GDP per capita growth resilience dataset was prepared with reference to the World Bank's statistical database, using year-on-year data on GDP per capita (constant 2010 US dollars) for countries along the Belt and Road from 2000 to 2019, and based on sensitivity and adaptability analysis, taking into account the year-on-year changes of each indicator. Through a comprehensive diagnostic, a product on GDP per capita growth resilience was prepared. "The GDP per capita growth resilience dataset for countries along the Belt and Road is an important reference for analysing and comparing the current GDP per capita growth resilience of each country.
XU Xinliang
The Belt and Road financial system resilience dataset reflects the level of resilience of the financial system of each country, and the higher the value of the data, the stronger the resilience of the financial system of the countries along the Belt and Road. The financial system resilience includes money market development resilience, banking system resilience, and stock market resilience. The data products are prepared with reference to the World Bank's statistical database, using broad money growth (annual percentage), real interest rates, net domestic credit (current local currency) as a percentage of GDP, and net domestic credit (current local currency) for countries along the Belt and Road from 2000 to 2019. The financial system resilience product is prepared through a comprehensive diagnosis based on sensitivity and adaptability analysis, taking into account year-on-year changes in each indicator, using year-on-year data on six indicators: bank liquidity reserves as a percentage of bank assets, bank capital as a percentage of assets, and total stock transactions as a percentage of GDP. The financial system resilience dataset for countries along the "Belt and Road" is an important reference for the analysis and comparison of the current financial system resilience of each country.
XU Xinliang
Macroeconomics refers to the entire national economy or the national economy as a whole, as well as its economic activities and operational status. "The data set of macroeconomic development resilience of countries along the Belt and Road reflects the level of macroeconomic development resilience of the countries along the Belt and Road, and the higher the data value, the stronger the macroeconomic development resilience of the countries along the Belt and Road. The macroeconomic development resilience dataset is prepared with reference to the World Bank's statistical database, using year-on-year changes in four indicators: GDP per capita, gross fixed capital formation as a percentage of GDP, inflation as measured by the GDP deflator, and total savings as a percentage of GDP for countries along the "Belt and Road" from 2000 to 2019. The macroeconomic development resilience product was prepared through a comprehensive diagnosis based on sensitivity and adaptability analysis, taking into account the year-on-year changes of each indicator. "The resilience dataset of macroeconomic development of countries along the Belt and Road is an important reference for analysing and comparing the resilience of macroeconomic development of various countries.
XU Xinliang
"The resilience of the domestic economic systems of the countries along the Belt and Road reflects the level of resilience of the domestic economic systems of each country, and the higher the value of the data, the stronger the resilience of the domestic economic systems of the countries along the Belt and Road. The resilience of domestic economic systems includes macroeconomic development resilience, industrial and service sector development resilience, and the data products are prepared with reference to the World Bank statistical database, using GDP per capita, gross fixed capital formation as a percentage of GDP, inflation as measured by GDP deflator, and gross savings as measured by GDP deflator for countries along the Belt and Road from 2000 to 2019. The resilience products of the domestic economic system are prepared through a comprehensive diagnosis based on sensitivity and adaptability analysis, taking into account the year-on-year changes of each indicator, using year-on-year data of six indicators: GDP per capita, gross fixed capital formation as a percentage of GDP, gross savings as a percentage of GDP, industrial value added as a percentage of GDP, and service value added as a percentage of GDP. "The resilience dataset of the domestic economic systems of the countries along the Belt and Road is an important reference for analysing and comparing the resilience of the domestic economic systems of various countries.
XU Xinliang
"The resilience dataset reflects the level of resilience of industrial and service development in the countries along the Belt and Road, and the higher the value, the stronger the resilience of industrial and service development in the countries along the Belt and Road. The resilience of industrial and service sector development data products are prepared with reference to the World Bank's statistical database, using the year-on-year changes of two indicators, namely the value added of industry as a percentage of GDP and the value added of service sector as a percentage of GDP, for countries along the Belt and Road from 2000 to 2019, and on the basis of considering the year-on-year changes of each indicator. Based on the sensitivity and adaptability analysis, a comprehensive diagnostic was prepared to generate products on the resilience of industrial and service sector development. "The resilience dataset of industrial and service sector development in countries along the Belt and Road is an important reference for analysing and comparing the current resilience of industrial and service sector development in each country.
XU Xinliang
"The Belt and Road countries' external trade system resilience dataset comprehensively reflects the level of resilience of each country's external trade system, and the higher the value of the data, the stronger the resilience of the external trade system of the countries along the Belt and Road. The World Bank's statistical database was used for the preparation of the external trade system resilience data, and the annual data of three indicators, namely the ratio of trade volume to gross national product (GDP), the annual growth rate of exports of goods and services, and the annual growth rate of imports of goods and services of countries along the Belt and Road, were used from 2000 to 2019. On the basis of the year-on-year changes in each indicator, a comprehensive diagnosis based on sensitivity and adaptability analysis was carried out to generate a resilience product for the foreign trade system. Please refer to the documentation for the methodology of preparing the data set. "The resilience dataset of the foreign trade system of countries along the Belt and Road is an important reference for analysing and comparing the current resilience of the foreign trade system of each country.
XU Xinliang
Using the dynamic computable general equilibrium model, taking 2012 as the base year, simulate the GDP changes of 48 industrial sectors in Zhangye City from 2013 to 2030, and carry out the prediction and simulation under different scenarios of benchmark growth, low-speed growth and high-speed growth, which can better describe the economic changes and industrial structure changes of various industrial sectors in Zhangye City in Heihe River Basin. The data comes from the input-output table of Heihe River Basin, Zhangye statistical yearbook and Zhangye statistical bulletin of national economic and social development. 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 simulation data set reflecting the economic development of Zhangye City in the middle reaches of the Heihe River Basin. It has a long time series and can provide reference information for the economic development and changes of industrial structure in the middle reaches of the Heihe River Basin.
WU Feng
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
Food consumption is not only an important indicator to determine the carrying capacity of land resources, but also an important basis to reflect residents' living standards. The food consumption data of the Qinghai Tibet Plateau is based on the data of the Tibet statistical yearbook to sort out the main types and consumption of food in urban and rural areas, such as the consumption of grain, meat, eggs and milk; Combined with the questionnaire survey data of typical counties, the type and quantity data of food consumption in typical counties are statistically sorted out. The data set includes: (1) urban and rural food consumption data on the Qinghai Tibet Plateau; (2) Consumption data of typical counties in Qinghai Tibet Plateau. The data can be used to analyze the spatial differences of food consumption in the Qinghai Tibet Plateau, which is of great significance to the study of land carrying capacity in the Qinghai Tibet Plateau.
YANG Yanzhao
"The data set recorded the gross output value of agriculture, forestry, animal husbandry and fishery in Qinghai province in major years, and the statistical data covered the period from 1952 to 2020. The data were classified by main years and regional projects in Xining, Haidong, Haibei Prefecture, Huangnan Prefecture, Hainan Prefecture, Guoluo Prefecture, Yushu Prefecture and Haixi Prefecture. The dataset contains eight data tables, which are: Total Output Value of Agriculture, Forestry, Animal Husbandry and Fishery of Qinghai Province in main years (1952-2020). XLS, Total output value of Agriculture, Forestry, Animal Husbandry and Fishery of Qinghai Province in main years (2012), Total output value of Agriculture, Forestry, Animal Husbandry and Fishery of Qinghai Province in Main years (2013), Total output value of Agriculture, Forestry, Animal Husbandry and Fishery of Qinghai Province in Main years (2014), Total output value of Agriculture, Forestry, Animal Husbandry and Fishery of Qinghai Province in Main years (1952-2020). Gross output value of Agriculture, Forestry, Animal Husbandry and Fishery in major years (2016), Gross output value of Agriculture, Forestry, Animal Husbandry and Fishery in major years (2017), Gross output value of Agriculture, Forestry, Animal Husbandry and Fishery in major years (2018). The data table structure is similar. For example, the total output value of agriculture, Forestry, Animal Husbandry and fishery in the main year (2012) has 7 fields in the data table: Field 1: Year Field 2: gross output value of agriculture, forestry, animal husbandry and fishery Field 3: Agriculture Field 4: Forestry Field 5: Animal husbandry Field 6: Fisheries Field 7: Agriculture, forestry, Animal husbandry and fishery professional and ancillary activities"
AGRICULTURAL AND RURAL Department of Qinghai Province
The data set records the added value of agriculture, forestry, animal husbandry and fishery in Qinghai Province in the main years, and the statistical data covers the period from 2012 to 2018. The data are divided by items such as 2006, 2007, 2008, 2009, 2010, 2011 and 2012. The data set contains 7 data tables, which are: added value of agriculture, forestry, animal husbandry and fishery in Main Years (2012), added value of agriculture, forestry, animal husbandry and fishery in Main Years (2013), added value of agriculture, forestry, animal husbandry and fishery in Main Years (2014), added value of agriculture, forestry, animal husbandry and fishery in Main Years (2015), added value of agriculture, forestry, animal husbandry and fishery in Main Years (2016), added value of agriculture, forestry, animal husbandry and fishery in Main Years (2017), Added value of agriculture, forestry, animal husbandry and fishery in Main Years (2018). The data table structure is similar. For example, the data table of added value of agriculture, forestry, animal husbandry and fishery in Main Years (2012) has 7 fields: Field 1: year / Project Field 2: added value of agriculture, forestry, animal husbandry and fishery Field 3: Agriculture Field 4: Forestry Field 5: Animal Husbandry Field 6: Fisheries Field 7: agriculture, forestry, animal husbandry and Fishery Services
AGRICULTURAL AND RURAL Department of Qinghai Province
The data set records the statistical data of main livestock and poultry production in Qinghai Province, covering the period from 2008 to 2018. The data are divided by pig, cattle, sheep, poultry and other items. The data set contains 11 data tables, which are: Main Livestock and poultry production table (2008), main livestock and poultry production table (2009), main livestock and poultry production table (2010), main livestock and poultry production table (2011), main livestock and poultry production table (2012), main livestock and poultry production table (2013), main livestock and poultry production table (2014) and main livestock and poultry production table (2015), table of main livestock and poultry production (2016), table of main livestock and poultry production (2017), table of main livestock and poultry production (2018). The data table structure is similar. For example, the data table of main livestock and poultry production (2008) has three fields: Field 1: indicator Field 2: Units Field 3: quantity
AGRICULTURAL AND RURAL Department of Qinghai Province
The data set records the basic situation of fishery production in Qinghai Province, and the statistical data covers the period from 2010 to 2018. The data are divided according to the total output of aquatic products, aquaculture area, motor fishing boats, aquaculture fishermen, aquaculture enterprises and other projects. The data set contains 9 data tables, which are: basic situation of fishery production in Qinghai Province (2010), basic situation of fishery production in Qinghai Province (2011), basic situation of fishery production in Qinghai Province (2012), basic situation of fishery production in Qinghai Province (2013), basic situation of fishery production in Qinghai Province (2014), basic situation of fishery production in Qinghai Province (2015) and basic situation of fishery production in Qinghai Province (2016), basic situation of fishery production in Qinghai Province (2017), basic situation of fishery production in Qinghai Province (2018). The data table structure is similar. For example, the data table of basic situation of fishery production in Qinghai Province (2010) has three fields: Field 1: indicator Field 2: Units Field 3: quantity
AGRICULTURAL AND RURAL Department of Qinghai Province
The data set records the basic statistical data of green food enterprises and products in Qinghai Province, covering the period from 2004 to 2008. The data are divided by pearl oyster, pearl oyster egg, split beef, Tibetan green salt, high concentration seabuckthorn fruit honey, rapeseed high-grade cooking oil, pea starch, honey and other items. The data set contains five data tables, namely: green food enterprises and products in Qinghai Province (2004), green food enterprises and products in Qinghai Province (2005), green food enterprises and products in Qinghai Province (2006), green food enterprises and products in Qinghai Province (2007) and green food enterprises and products in Qinghai Province (2008). The data table structure is similar. For example, the data sheet of green food enterprises and products in Qinghai Province (2004) has 6 fields: Field 1: Manufacturer Field 2: registered trademark Field 3: output Field 4: output value (10000 yuan) Field 5: product sales region Field 6: contact number
AGRICULTURAL AND RURAL Department of Qinghai Province
The data set records the directory data of national and provincial leading enterprises in agriculture and animal husbandry industrialization in Qinghai Province. The statistical data covers the period from 2004 to 2012. The data are divided by Qinghai Sanjiang Group Co., Ltd., Qaidam Longkang high tech Pharmaceutical Co., Ltd., Huangzhong County Foreign Trade Co., Ltd., Guinan County cattle and sheep fattening Comprehensive Development Co., Ltd., Minhe Tianrun industry and Trade Development Co., Ltd., Xunhua Tianxiang Two Pepper company, etc. The data set contains 9 data tables, which are: the list of national and provincial leading enterprises in agriculture and animal husbandry industrialization in Qinghai Province (2004), the list of national and provincial leading enterprises in agriculture and animal husbandry industrialization in Qinghai Province (2005), the list of national and provincial leading enterprises in agriculture and animal husbandry industrialization in Qinghai Province (2006), and the list of national and provincial leading enterprises in agriculture and animal husbandry industrialization in Qinghai Province (2007), list of national and provincial leading enterprises in agriculture and animal husbandry industrialization in Qinghai Province (2008), list of national and provincial leading enterprises in agriculture and animal husbandry industrialization in Qinghai Province (2009), list of national and provincial leading enterprises in agriculture and animal husbandry industrialization in Qinghai Province (2010), list of national and provincial leading enterprises in agriculture and animal husbandry industrialization in Qinghai Province (2011) , the list of national and provincial leading enterprises in agriculture and animal husbandry industrialization in Qinghai Province (2012). The data table structure is similar. For example, the list of national and provincial leading enterprises in agriculture and animal husbandry industrialization in Qinghai Province (2004) has two fields: Field 1: enterprise name Field 2: level
AGRICULTURAL AND RURAL Department of Qinghai Province
The data set records the total output value and added value of agriculture, forestry, animal husbandry and fishery in Qinghai Province at current price. The statistical data covers the period from 2006 to 2014. The data are divided by total output value of agriculture, forestry, animal husbandry and fishery, agriculture, forestry, animal husbandry, fishery, agriculture, forestry, animal husbandry and fishery services, etc. The data set contains 9 data tables, which are: total output value and added value of agriculture, forestry, animal husbandry and fishery (current price) (2006), total output value and added value of agriculture, forestry, animal husbandry and fishery (current price) (2007), total output value and added value of agriculture, forestry, animal husbandry and fishery (current price) (2008), total output value and added value of agriculture, forestry, animal husbandry and fishery (current price) (2009), total output value and added value of agriculture, forestry, animal husbandry and fishery (current price) (2010), total output value and added value of agriculture, forestry, animal husbandry and fishery (current price) (2011), total output value and added value of agriculture, forestry, animal husbandry and fishery (current price) (2012), total output value and added value of agriculture, forestry, animal husbandry and fishery (current price) (2013), total output value and added value of agriculture, forestry, animal husbandry and fishery (current price) (2014). The data table structure is similar. For example, the data table of total output value and added value (current price) (2006) of agriculture, forestry, animal husbandry and fishery has four fields: Field 1: indicator name Field 2: 2006 Field 3: 2005 Field 4: increase or decrease%
AGRICULTURAL AND RURAL Department of Qinghai Province
The data set records the basic situation of rural areas and agricultural production conditions in Qinghai Province. The statistical data covers the period from 2007 to 2013. 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 includes rural basic situation and agricultural production conditions (Table 1) (2007), rural basic situation and agricultural production conditions (Table 2) (2007), rural basic situation and agricultural production conditions (Table 3) (2007), rural basic situation and agricultural production conditions (Table 4) (2007), rural basic situation and agricultural production conditions (Table 5) (2007), rural basic situation and agricultural production conditions (Table 6) (2007), rural basic situation and agricultural production conditions (Table 7) (2007), rural basic situation and agricultural production conditions (Table 8) (2007), rural basic situation and agricultural production conditions (Table 1) (2008), rural basic situation and agricultural production conditions (Table 2) There are 105 data sheets in total (2008). The structures of each data sheet are similar. For example, the data sheet of rural basic situation and agricultural production conditions (Table I) (2007) has 20 fields: Field 1: number of township governments Field 2: number of village committees Field 3: number of cooperatives Field 4: number of rural households Field 5: rural population Field 6: rural community infrastructure Field 7: total rural labor resources Field 8: total number of rural employees Field 9: current year outgoing personnel Field 10: education level Field 11: agriculture, forestry, animal husbandry and fishery practitioners Field 12: total cultivated land resources at the beginning of the year Field 13: cultivated land area increased in the current year Field 14: cultivated land area reduced in the current year Field 15: national infrastructure land occupation Field 16: land occupation of rural collective infrastructure Field 17: land occupied by individual farmers Field 18: Reforestation area Field 19: area for returning farmland to grassland Field 20: change cultivated land to garden land
AGRICULTURAL AND RURAL Department of Qinghai Province
The data set records the basic situation of leading enterprises in agriculture and animal husbandry industrialization in Qinghai Province, and the statistical data covers the period from 2013 to 2018. The data is divided by enterprise name, enterprise registration type, legal representative, general manager, enterprise address, fixed telephone, mobile phone and fax. The data set contains six data tables, which are: basic information table of leading enterprises in agriculture and animal husbandry industrialization in Qinghai Province (2013), basic information table of leading enterprises in agriculture and animal husbandry industrialization in Qinghai Province (2014), basic information table of leading enterprises in agriculture and animal husbandry industrialization in Qinghai Province (2015), basic information table of leading enterprises in agriculture and animal husbandry industrialization in Qinghai Province (2016), Basic information of leading enterprises in agriculture and animal husbandry industrialization in Qinghai Province (2017), and basic information of leading enterprises in agriculture and animal husbandry industrialization in Qinghai Province (2018). The data table structure is the same. For example, the basic information table of leading enterprises in agriculture and animal husbandry industrialization in Qinghai Province (2013) has 9 fields: Field 1: enterprise name Field 2: enterprise registration type Field 3: legal representative Field 4: General Manager Field 5: business address Field 6: zip code Field 7: fixed telephone, mobile phone and fax Field 8: Web address Field 9: remarks
AGRICULTURAL AND RURAL Department of Qinghai Province
The data set records the animal husbandry production in pastoral and semi pastoral counties of Qinghai Province. The statistical data covers the period from 2009 to 2018. The data are divided according to the basic situation, livestock and poultry breeding, output and marketing of livestock products, sales of livestock products and other items. The data set contains 10 data tables, which are: animal husbandry production in pastoral counties and semi pastoral counties (2009), animal husbandry production in pastoral counties and semi pastoral counties (2010), animal husbandry production in pastoral counties and semi pastoral counties (2011), animal husbandry production in pastoral counties and semi pastoral counties (2012), animal husbandry production in pastoral counties and semi pastoral counties (2013), pastoral counties Animal husbandry production in semi pastoral counties (2014), animal husbandry production in pastoral counties and semi pastoral counties (2015), animal husbandry production in pastoral counties and semi pastoral counties (2016), animal husbandry production in pastoral counties and semi pastoral counties (2017), and animal husbandry production in pastoral counties and semi pastoral counties (2018). The data table structure is similar. For example, there are four fields in the data sheet of animal husbandry production in pastoral counties and semi pastoral counties (2010): Field 1: indicator name Field 2: calculation unit Field 3: Pastoral County Field 4: semi pastoral counties
AGRICULTURAL AND RURAL Department of Qinghai Province
The data set records the situation of green biological capital enterprises and products in Qinghai Province, and the statistical data covers the period from 2013 to 2017. Green production resources include fertilizers, pesticides, feed and feed additives, veterinary drugs, food additives and other production inputs related to green food production. The data are based on Qinghai Yuhe bio organic fertilizer plant, Qinghai jiangheyuan agriculture and animal husbandry technology development Co., Ltd., Golmud Kangsheng potassium Industry Technology Development Co., Ltd., Qinghai Hongen Technology Co., Ltd., Haibei Chuyuan Biotechnology Development Co., Ltd., Minhe Lvbao forage Technology Development Co., Ltd., Qinghai Jingjie Magnesium Technology Co., Ltd Menyuan Yongxing ecological agriculture and animal husbandry development Co., Ltd., Qinghai Nanjia ecological environment development Co., Ltd. and Haibei Qilian Mountain green organic Biotechnology Development Co., Ltd. The data set contains five data tables, which are: green enterprises and products (2013), green enterprises and products (2014), green enterprises and products (2015), green enterprises and products (2016) and green enterprises and products (2017). The data table structure is similar. For example, there are three fields in the data sheet of green funded enterprises and products (2016): Field 1: enterprise name Field 2: Trademarks Field 3: product
AGRICULTURAL AND RURAL Department of Qinghai Province
The data set records the total output value of agriculture, forestry, animal husbandry and fishery in all States, prefectures, cities and counties of Qinghai Province. The statistical data covers the period from 2008 to 2018. The data are divided into 8 states and cities according to Xining City, Haidong region, Haibei Prefecture, Huangnan Prefecture, Hainan prefecture, Guoluo Prefecture, Yushu prefecture and Haixi Prefecture. The data set contains 11 data tables, which are: total output value of agriculture, forestry, animal husbandry and fishery of counties (prefectures and cities) (2008), total output value of agriculture, forestry, animal husbandry and fishery of counties (prefectures and cities) (2009), total output value of agriculture, forestry, animal husbandry and fishery of counties (prefectures and cities) (2010), total output value of agriculture, forestry, animal husbandry and fishery of counties (prefectures and cities) (2011), total output value of agriculture, forestry, animal husbandry and fishery of counties (prefectures and cities) (2012), total output value of agriculture, forestry, animal husbandry and fishery in counties (prefectures and cities) (2013), total output value of agriculture, forestry, animal husbandry and fishery in counties (prefectures and cities) (2014), total output value of agriculture, forestry, animal husbandry and fishery in Counties (prefectures and cities) (2015), total output value of agriculture, forestry, animal husbandry and fishery in counties (prefectures and cities) (2016), total output value of agriculture, forestry, animal husbandry and fishery in counties (prefectures and cities) (2017), and The total output value of agriculture, forestry, animal husbandry and fishery in (prefecture, city) counties (2018). The data table structure is similar. For example, the data table of total output value of agriculture, forestry, animal husbandry and fishery in (prefecture, city) counties (2008) has five fields: Field 1: Agriculture Field 2: Forestry Field 3: Animal Husbandry Field 4: Fisheries Field 5: agriculture, forestry, animal husbandry and Fishery Services
AGRICULTURAL AND RURAL Department of Qinghai Province
The data set records the added value of agriculture, forestry, animal husbandry and fishery in all States (prefectures, cities) and counties of Qinghai Province. The statistical data covers the period from 2008 to 2018. The data are divided into 8 states and cities according to Xining City, Haidong region, Haibei Prefecture, Huangnan Prefecture, Hainan prefecture, Guoluo Prefecture, Yushu prefecture and Haixi Prefecture. The data set contains 11 data tables, which are: added value of agriculture, forestry, animal husbandry and fishery in counties (prefectures and cities) (2008), added value of agriculture, forestry, animal husbandry and fishery in counties (prefectures and cities) (2009), added value of agriculture, forestry, animal husbandry and fishery in counties (prefectures and cities) (2010), added value of agriculture, forestry, animal husbandry and fishery in counties (prefectures and cities) (2011), and added value of agriculture, forestry, animal husbandry and fishery in counties (prefectures and cities) (2012), added value of agriculture, forestry, animal husbandry and fishery in counties (prefectures and cities) (2013), added value of agriculture, forestry, animal husbandry and fishery in counties (prefectures and cities) (2014), added value of agriculture, forestry, animal husbandry and fishery in counties (prefectures and cities) (2015), added value of agriculture, forestry, animal husbandry and fishery in counties (prefectures and cities) (2016), added value of agriculture, forestry, animal husbandry and fishery in counties (prefectures and cities) (2017), and The added value of agriculture, forestry, animal husbandry and fishery in (prefecture, city) counties (2018). The data table structure is similar. For example, the data table of added value of agriculture, forestry, animal husbandry and fishery in (prefecture, city) counties (2008) has five fields: Field 1: Agriculture Field 2: Forestry Field 3: Animal Husbandry Field 4: Fisheries Field 5: agriculture, forestry, animal husbandry and Fishery Services
AGRICULTURAL AND RURAL Department of Qinghai Province
The data set records the output and production of livestock products in different counties of Qinghai Province, and the statistical data covers the period from 2008 to 2018. The data are divided into 8 states and cities according to Xining City, Haidong region, Haibei Prefecture, Huangnan Prefecture, Hainan prefecture, Guoluo Prefecture, Yushu prefecture and Haixi Prefecture. The data set contains 9 data tables, which are: production of livestock products by county (2008), production of livestock products by county (2009), production of livestock products by county (2012), production of livestock products by county (2013), production of livestock products by county (2014) and production of livestock products by county (2015) , the output and production of livestock products by county (2016), the output and production of livestock products by county (2017) and the output and production of livestock products by county (2018) are similar in structure. For example, there are 18 fields in the table of livestock production by county (2015): Field 1: county name Field 2: total meat production Field 3: where: beef Field 4: pork Field 5: mutton Field 6: Poultry Field 7: rabbit meat Field 8: milk production Field 9: milk production Field 10: where: yak milk production Field 11: cashmere production Field 12: goat wool production Field 13: sheep wool production Field 14: where: fine wool production Field 15: semi fine wool production Field 16: honey production Field 17: egg production Field 18: where: egg production
AGRICULTURAL AND RURAL Department of Qinghai Province
The data set records the statistical data of the designated wholesale market of agricultural and livestock products in Qinghai Province of the Ministry of agriculture, covering the period from 2007 to 2018. The data are divided by multiple projects, such as Qinghai Xining Haihu Road vegetable and fruit comprehensive wholesale market, Qinghai Ledu County Eastern Qinghai vegetable comprehensive wholesale market, Qinghai Ping'an Haidong agricultural and sideline products wholesale market, Qinghai Golmud Qingken wholesale market, Qinghai Xining Renjie grain and oil wholesale market, and Lejiawan livestock products wholesale market. The data set contains 12 data tables, which are: designated wholesale market of agricultural and livestock products of the Ministry of agriculture (2007), designated wholesale market of agricultural and livestock products of the Ministry of agriculture (2008), designated wholesale market of agricultural and livestock products of the Ministry of agriculture (2009), designated wholesale market of agricultural and livestock products of the Ministry of agriculture (2010), designated wholesale market of agricultural and livestock products of the Ministry of agriculture (2011), designated wholesale market of agricultural and livestock products of the Ministry of agriculture (2012), Designated wholesale market of agricultural and livestock products of the Ministry of agriculture (2013), designated wholesale market of agricultural and livestock products of the Ministry of agriculture (2014), designated wholesale market of agricultural and livestock products of the Ministry of agriculture (2015), designated wholesale market of agricultural and livestock products of the Ministry of Agriculture (2016), designated wholesale market of agricultural and livestock products of the Ministry of agriculture (2017), and designated wholesale market of agricultural and livestock products of the Ministry of agriculture (2018). The data table structure is similar. For example, the data sheet of the designated wholesale market for agricultural and livestock products (2007) of the Ministry of agriculture has four fields: Field 1: sequence number Field 2: market name Field 3: responsible person Field 4: contact number
AGRICULTURAL AND RURAL Department of Qinghai Province
This data set records the statistical data on the establishment of a national standardized production base of green food raw materials in Qinghai, covering the period from 2009 to 2017. The data are based on the national standardized production base of green food raw materials (horse tooth broad bean) in Huangyuan County, Qinghai Province, the national standardized production base of green food raw materials (broad bean) in Huangzhong County, Qinghai Province, the national standardized production base of green food raw materials (potato) in Huangzhong County, Qinghai Province, and the national standardized production base of green food raw materials (Brassica campestris) in Haomen farm, Qinghai Province. There are 4 projects in total. The data set contains nine data tables, which are: Qinghai Province established a national standardized production base of green food raw materials (2009), Qinghai Province established a national standardized production base of green food raw materials (2010), Qinghai Province established a national standardized production base of green food raw materials (2011), Qinghai Province established a national standardized production base of green food raw materials (2012), Qinghai Province established the national standardized production base of green food raw materials (2013), Qinghai Province established the national standardized production base of green food raw materials (2014), Qinghai Province established the national standardized production base of green food raw materials (2015), Qinghai Province established the national standardized production base of green food raw materials (2016), and Qinghai Province established the national standardized production base of green food raw materials (2017). The data table structure is similar. For example, Qinghai Province established a national standardized production base of green food raw materials (2009). The data table has five fields: Field 1: sequence number Field 2: base name Field 3: create company Field 4: base size Field 5: base range
AGRICULTURAL AND RURAL Department of Qinghai Province
The data set records the statistical data of "breeding in the West and breeding in the East" in Qinghai Province, covering the period from 2003 to 2005. The data are divided into 12 counties such as Huangzhong County, Huangyuan County, Datong County, Ping'an County, Xunhua County, Hualong County, Huzhu County, Tongren County and Ledu County, and 14 related reference years such as 2003 and 2004. The data set contains two data tables, namely, "West breeding and East breeding" table (2003-2004) and "West breeding and East breeding" table (2004-2005). The data table structure is similar. For example, the data table of "breeding in the West and breeding in the East" (2004-2005) has five fields: Field 1: Unit Field 2: total number of households Field 3: cattle and sheep fattening Field 4: Loan Status Field 5: fattening stock
AGRICULTURAL AND RURAL Department of Qinghai Province
This data set records the statistical data on the production of animal husbandry counties in Qinghai Province in the current year, covering the period from 2008 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 11 data tables, which are: the production situation of animal husbandry counties in the current year (2008), the production situation of animal husbandry counties in the current year (2009), the production situation of animal husbandry counties in the current year (2010), the production situation of animal husbandry counties in the current year (2011), and the production situation of animal husbandry counties in the current year (2012), Production situation of animal husbandry counties in the current year (2013), production situation of animal husbandry counties in the current year (2014), production situation of animal husbandry counties in the current year (2015), production situation of animal husbandry counties in the current year (2016), production situation of animal husbandry counties in the current year (2017), and production situation of animal husbandry counties in the current year (2018). The data table structure is similar. For example, there are five fields in the data sheet of the production situation of animal husbandry counties in the current year (2008): Field 1: large livestock Field 2: Pig Field 3: sheep Field 4: Poultry Field 5: Rabbit
AGRICULTURAL AND RURAL Department of Qinghai Province
The data set records the statistical data on the production of fertile female animals in animal husbandry counties of Qinghai Province, covering the period from 2008 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 11 data tables, which are: production of fertile female livestock in animal husbandry counties (2008), production of fertile female livestock in animal husbandry counties (2009), production of fertile female livestock in animal husbandry counties (2010), production of fertile female livestock in animal husbandry counties (2011) and production of fertile female livestock in animal husbandry counties (2012) , production of fertile female livestock in animal husbandry counties (2013), production of fertile female livestock in animal husbandry counties (2014), production of fertile female livestock in animal husbandry counties (2015), production of fertile female livestock in animal husbandry counties (2016), production of fertile female livestock in animal husbandry counties (2017) and production of fertile female livestock in animal husbandry counties (2018) . the data table structure is similar. For example, the data table has three fields: Field 1: large livestock Field 2: Pig Field 3: sheep
AGRICULTURAL AND RURAL Department of Qinghai Province
The data set records the statistical data of meat production in animal husbandry counties in Qinghai Province, covering the period from 2008 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 11 data tables, which are: meat production by County in animal husbandry (2008), meat production by County in animal husbandry (2009), meat production by County in animal husbandry (2010), meat production by County in animal husbandry (2012), meat production by County in animal husbandry (2013), meat production by County in animal husbandry (2014), Table of meat production by County in animal husbandry (2015), table of meat production by County in animal husbandry (2016), table of meat production by County in animal husbandry (2017), table of meat production by County in animal husbandry (2018). The data table structure is similar. For example, the data sheet of meat production by County in animal husbandry (2008) has five fields: Field 1: large livestock Field 2: Pig Field 3: sheep Field 4: Poultry Field 5: Rabbit
AGRICULTURAL AND RURAL Department of Qinghai Province
The data set records the statistical data of stock production at the end of the period by county of animal husbandry in Qinghai Province, covering the period from 2008 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 14 data tables, which are: livestock production by county at the end of the period (2008), livestock production by county at the end of the period (2009), livestock production by county at the end of the period (2010), livestock production by county at the end of the period (2011) (Table 1), and livestock production by county at the end of the period (2011) (Table 2), livestock production by county at the end of the period (2012), livestock production by county at the end of the period (2013), livestock production by county at the end of the period (2014), livestock production by county at the end of the period (2015), livestock production by County at the end of the period (2016), and livestock production by county at the end of the period (2017), livestock production by county at the end of the period (2018). The data table structure is similar. For example, the data table of livestock production by county at the end of the period (2008) has 6 fields: Field 1: large livestock Field 2: Pig Field 3: sheep Field 4: Poultry Field 5: Rabbit Field 6: bees
AGRICULTURAL AND RURAL Department of Qinghai Province
The data set records the statistical data of animal husbandry production and economic benefit indicators in Qinghai Province, covering the period from 2004 to 2006. The data are divided by the number of female animals that failed to reproduce in the year, the number of live piglets in the year, the total growth rate of livestock, the slaughter rate of livestock, the reproduction rate of female animals, the reproduction survival rate of female animals, etc. The data set contains 9 data tables, which are respectively: animal husbandry production and economic benefit indicators (Table 1) (2004), animal husbandry production and economic benefit indicators (Table 2) (2004), animal husbandry production and economic benefit indicators (Table 3) (2004), animal husbandry production and economic benefit indicators (Table 1) (2005) and animal husbandry production and economic benefit indicators (Table 2) (2005), animal husbandry production and economic benefit indicators (Table 3) (2005), animal husbandry production and economic benefit indicators (Table 1) (2006), animal husbandry production and economic benefit indicators (Table 2) (2006), animal husbandry production and economic benefit indicators (Table 3) (2006). The data table structure is similar. For example, animal husbandry production and economic benefit indicators (Table 1) The data sheet (2004) has three fields: Field 1: indicator Field 2: Units Field 3: year
AGRICULTURAL AND RURAL Department of Qinghai Province
The regional socio-economic data of typical mineral development projects include the economic and social data set of Gannan Tibetan Autonomous Prefecture (1949, 1953, 1965, 1970, 1978-2018), the economic and social data set of cooperative city of Gannan Tibetan Autonomous Prefecture (2000-2017), and the economic and social data set of Maqu County of Gannan Tibetan Autonomous Prefecture (2000-2017). The first row of data is the economic and social indicator, the second row is the indicator unit, and the first column is the year. The data sources are Gannan Tibetan Autonomous Prefecture statistical yearbook, cooperative city statistical yearbook and Maqu County statistical yearbook. The data is sorted and processed to form, and one person enters and one person checks to ensure the data quality. The data format is xlsx and the accuracy is years. It can be used to evaluate the comprehensive economic and social effects of typical mineral development areas in the super large gold belt of Qilian Mountain metallogenic belt in the northeast of Qinghai Tibet Plateau.
CHENG Hao
This data set is the statistical yearbook of Tibet Autonomous Region in different years, mainly including different social and economic statistical contents. The Tibet Statistical Yearbook is mainly based on statistical charts and analysis. It records the annual economic and social development comprehensively, systematically and continuously through highly intensive statistical data. Obtaining statistical data is a necessary prerequisite for economic and social research. With the help of Tibet statistical yearbook, it can provide data support for the social and Economic Research of Tibet Autonomous Region. Due to the lack of data in the Qinghai Tibet Plateau, it is difficult to find detailed socio-economic statistics on the network platform. This data set comes from the statistical departments of the Tibet Autonomous Region, which can provide support for relevant investigation and research.
FU Bin
The data set is based on the NPP simulated by 16 dynamic global vegetation models (TRENDY v8) under S2 Scenario (CO2+Climate) and represents the net primary productivity of the ecosystem. Data was derived from Le Quéré et al. (2019). The range of source data is global, and the Qinghai Tibet plateau region is selected in this data set. Original data is interpolated into 0.5*0.5 degree by the nearest neighbor method in space, and the original monthly scale is maintained in time. The data set is the standard model output data, which is often used to evaluate the temporal and spatial patterns of gross primary productivity, and compared with other remote sensing observations, flux observations and other data.
STEPHEN Sitch
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