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
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
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
This data set records the statistical data of per capita GDP and growth rate and ranking (2010-2018) of all regions in 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 of 2017-2018 has four fields: Field 1: Region Field 2: quantity Field 3: Rank Field 4: growth rate
Qinghai Provincial Bureau of Statistics
Grassland actual net primary production (NPPa) was calculated by CASA model. CASA model was calculated with the combination of satellite-observed NDVI and climate (e.g. temperature, precipitation and radiation) as the driving factors, and other factors, such as land-use change and human harvest from plant material, were reflected by the changes of NDVI. CASA NPP was determined by two variables, absorbed photosynthetically active radiation’ (APAR) and the light-use efficiency (LUE). Grassland potential net primary production (NPPp) was calculated by TEM model. TEM is one of process-based ecosystem model, which was driven by spatially referenced information on vegetation type, climate, elevation, soils, and water availability to calculate the monthly carbon and nitrogen fluxes and pool sizes of terrestrial ecosystems. TEM can be only applied in mature and undisturbed ecosystem without take the effects of land use into consideration due to it was used to make equilibrium predications. Grassland potential aboveground biomass (AGBp) was estimated by random forest (RF) algorithm, using 345 AGB observation data in fenced grasslands and their corresponding climate data, soil data, and topographical data.
NIU Ben, ZHANG Xianzhou
Data content: annual GDP statistics (1990-2019), quarterly cumulative GDP statistics (1990-2019) and GDP (2010-2019) Data sources and processing methods: the original macroeconomic data of China (including the third pole) from the official website of the world bank and sina.com from 1990 to 2019 are obtained through data sorting, screening and cleaning. The data are stored in Microsoft Excel (xlsx) format.
FU Wenxue
Data content: Central Bank gold and foreign exchange reserves (2000-2020) and money supply (2000-2017) Data sources and processing methods: the original data of banks and currencies in China (including the third pole) in 2015-2019 are obtained from the official website of the world bank and sina.com, and the bank and currency data sets of China (including the third pole) from 2000 to 2020 are obtained through data sorting, screening and cleaning. The data start time is from 2000 to 2020 in Microsoft Excel (xlsx) format.
FU Wenxue
Data content: Foreign Economic and trade_ Total import and export of goods (1952-2019) and foreign economic and trade_ Total import and export by trade (1981-2019) Data sources and processing methods: the original data of China's foreign trade and investment from 2015 to 2019 (including the third pole) were obtained from the official website of the world bank and sina.com, and the foreign trade and investment data set of China (including the third pole) from 1952 to 2019 was obtained through data sorting, screening and cleaning. The data start time is from 1952 to 2019 in Microsoft Excel (xlsx) format.
FU Wenxue
Data content: national economy_ Industrial value added (monthly) (2010-2019) Data source and processing method: the original industrial economic data of China (including the third pole) from the official website of the world bank and sina.com from 2010 to 2019 are obtained through data sorting, screening and cleaning. The data start time is from 2010 to 2019 in Microsoft Excel (xlsx) format.
FU Wenxue
Data content: price index_ Consumer price index (CPI) (2010-2019) Data source and processing method: obtain the economic original data of the third pole (China region) price index from the official website of the world bank and sina.com from 2015 to 2019, and obtain the economic data set of the third pole (China region) price index from 2010 to 2019 through data sorting, screening and cleaning. The data start time is from 2010 to 2019 in Microsoft Excel (xlsx) format.
FU Wenxue
It is summarized that the agricultural and socio-economic status of the five Central Asian countries (Kazakhstan, Kyrgyzstan, Tajikistan, Uzbekistan and Turkmenistan) in 2016. This data comes from the statistical yearbook of five Central Asian countries, including six elements: total population, cultivated land area, grain production area, GDP, proportion of agricultural GDP to total GDP, proportion of industrial GDP to total GDP, and forest area. Detailed statistics of the six socio-economic elements of the five Central Asian countries. It can be seen from the statistics that there are different emphases among the six elements of the five Central Asian countries. This data provides basic data for the project, facilitates the subsequent analysis of the ecological and social situation in Central Asia, and provides data support for the project data analysis.
LIU Tie
The data set is the global vegetation productivity data, including Gross Primary Productivity(GPP) and Net Primary Productivity (NPP). It was obtained by the CNRM-CM6-1 mode simulation of CMIP6 under the Historical scenario. The time range of the data covers from 1850 to 2014, the time resolution is a month, and the spatial resolution is about 1.406°×1.389°. For the simulated data details, please go to the following link: http://www.umr-cnrm.fr/cmip6/spip.php?article11.
Program for Climate Model Diagnosis and Intercomparison (PCMDI)
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 data contains part of the economic indicators of Qinghai province and Tibet Autonomous Region. The data statistics based on provinces can be used to construct the evaluation index system for the coupling coordination relationship between urbanization and eco-environment on the Tibetan Plateau. The data of the Tibet Autonomous Region contains seven indicators, including the gross domestic product (GDP), the primary, secondary and tertiary industries, industry, construction industry, and the per capita GDP, the time span is 1951-2016. The time span of the data set of Qinghai province is from 1952 to 2015, besides the above seven indicators, there is one more indicator of Qinghai province called agriculture forwdtry animal husbandry and fishery. All data are derived from the statistical yearbook, which is calculated at current prices. The gross domestic product (GDP) for 2005-2008 has been revised based on data from the second economic census.
DU Yunyan
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