The degree of opening to the outside world refers to the degree of opening to the outside world of a country or region's economy, which is embodied in the degree of opening to the outside world of the market, usually including the amount of import and export, the use of foreign capital, the level of tariff, the convenience of customs clearance, free trade agreements, market access, capital exchange, intellectual property protection, etc. The data are one belt, one road, 64 countries, including the net inflow of foreign direct investment (US $100 million), total import (US $100 million) and total export volume (US $100 million). Data sources include the world bank, the United Nations Conference on Trade and development, and the WTO. The 64 countries along the line include 16 in West Asia and North Africa, 16 in central and Eastern Europe, 5 other CIS countries, 8 in South Asia, 11 in Southeast Asia, including Myanmar, Vietnam and Thailand, and 5 in Mongolia, Russia and Central Asia.
Gross domestic product (GDP) is a monetary measure of the market value of all the final goods and services produced in a period of time, which has been used to determine the economic performance of a whole country or region. We have collected the published GDP data. Collect the public GDP data. On the basic of 1-kilometer scale global GDP grid data in 2010 released by the United Nations, the total GDP of the node area was obtained. The lighting data and land use data of node areas are took as auxiliary data, after data preprocessing, data interpolation and multiple regression analysis, establish the relationship between GDP and the hundred meter scale multiple data, and then, the GDP data of 34 key node areas are obtained.
GE Yong LI Qiangzi 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.
The data include the coastal ports and airport distribution in the Belt and Road region. The data are from the Natural Earth global port and airport data. The data are cut according to the standard map of the 65 countries along the Belt and road, and further corrected, then the distribution of the ports and airports in the area along the B&R is obtained. This data is mainly one to analyze the B&R area's important spatial layout and main characteristics of the transportation facilities, and to get other attributes data of port and airport in the following research, including the throughput of different port cargo types, the incoming and outgoing throughput, the number of docks and berths, the number of passengers on the airport, the data of the flights and routes of ports and airports, we can get further understanding of the spatial differentiation of the distribution of ports and airports in the B&R region.
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.
The trade data between China and BRI Countries, including China's export data to BRI Countries, China's import data from BRI Countries and the total trade volume between China and BRI Countries. BRI Countries refer to the 64 countries along the traditional silk road, including Kazakhstan, Kyrgyzstan, Tajikistan, Uzbekistan, Turkmenistan, Mongolia, Russia, Vietnam, Laos, Kampuchea, Thailand, Malaysia, Singapore, Indonesia, Brunei, Indonesia, Indonesia, convergence, and Bangladesh, Afghanistan, Nepal, Bhutan, Sri Lanka, Maldives, Poland, Czech Republic, Slovakia, Hungary, Slovenia, Croatia, Romania, Bulgaria, Serbia, Montenegro, Macedonia, Bosnia and Herzegovina, Albania, Estonia, Lithuania, Latvia, Ukraine, Belarus, Moldova, Turkey Iran, Syria, Iraq, UAE, Saudi Arabia, Qatar, Bahrain, Kuwait, Lebanon, Oman, Yemen, Jordan, Israel, Palestine, Armenia, Georgia, Azerbaijan, Egypt.
Gross domestic product (GDP) is a monetary measure of the market value of all the final goods and services produced in a period of time, which has been used to determine the economic performance of a whole country or region. According to the collected the published global GDP data of 2015, a downscaling model, named support vector machine regression kriging was established for predicting 100-m GDP in thirty-four key nodes along the Belt and Road. The remote sensed night light data, land cover, vegetation and terrain indices were employed as ancillary variables in downscaling process. To solve the problem of missing data existing in the ancillary datasets, we will apply kriging and function interpolation methods to fill gaps. The aggregation and resampling were used to obtain 1-km and 500-m all ancillary variables, as well as 100-m terrain indices including elevation, slope and aspect. The adopted downscaling model contains trend and residual predictions. The support vector machine regression is used to model the relationship among GDP and its ancillary variables for obtaining GDP trends at fine scale based on scale invariant of the relationship. And then, the kriging interpolation is used to estimate GDP residuals at fine scale. In the downscaling process, the mentioned downscaling model was firstly employed in 1-km and 500-m data for obtaining 500-m GDP predictions; and it was again used in 500-m and 100-m data for achieving 100-m GDP predictions. The 100-m GDP predictions in constant 2011 international US dollars would provide high spatial resolution data for risk assessments.
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.
Qian ZHANG Linxiu ZHANG
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.
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.
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 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.
This database is based on the theory of emergy analysis for 17 typical countries along the “Belt and Road” during 2008-2014. These countries are include Kazakhstan, Kyrgyzstan, Tajikistan, Uzbekistan, Turkmenistan, Mongolia, Russia, Pakistan, Bangladesh, Afghanistan, Nepal, Thailand, Myanmar, Ukraine, Moldova, Belarus and Azerbaijan. The basic data sources of this database mainly include detailed information, goods and services on environmental resource flows, natural capital stocks and human production activities. The data in database is calculated and evaluated based on the solar emergy. The database consists of three tables, which are the emergy analysis table of main resource flow, comprehensive emergy analysis table of the main resource category and the system emergy indicators analysis table. The emergy transformities used in this database is updated and calculated according to the emergy baseline (12.0E+24seJ/y) given by Pro. Brown in 2016. Based on the basic data in the database, it can effectively calculate the emergy-based sustainability index system, and give the reasons for the analysis results, the solution and future planning direction for the study country. It is of great significance to the development of the national ecological economic system and provide a scientific basis for the government to improve the sustainable development status of the national ecological economic system.
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.
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.
The data set contains agricultural economic data of all counties and regions in the Tibetan Plateau in 1980-2015, and covering the total number of households and total population in rural areas, agricultural population, rural labor force, cultivated land, paddy field area, the dry land area, power of agricultural machinery, agricultural vehicles, mechanical ploughing area, irrigation area, consumption of chemical fertilizers electricity use, gross output value of agriculture, forestry, animal husbandry and fishery, the output of cattle, pig, sheep, meat, poultry, and fish, the sown area of grain, the output of grain, cotton, oil and all kinds of crops, and characteristic agricultural products and livestock production and other relevant data.The data came from the statistical yearbook of the provinces included in the Tibetan Plateau.The data are of good quality and can be used to analyze the socio-economic and agricultural development of qinghai-tibet plateau.
The data content of the Belt and Road Food Consumption includes: The data of Food Consumption for “B&R” includes: 1. Total food consumption in regions and countries along the “B&R”, mainly including Cereals-Excluding Beer, Meat, Eggs, Milk-Excluding Butter, Fruits - Excluding Wine, Vegetables, Pulses, Starchy Roots, Oilcrops, Sugar& Sweeteners; 2.Nutrient intake in regions and countries along the “B&R”, mainly including energy, protein, fat. Source：FAO. Data application：According to the data provided，the basic characteristics analysis of food consumption, the analysis of the nutrient intake level and the analysis of food consumption pressure can be carried out in the Belt and Road region and the countries along the route, so that the dietary pattern evaluation analysis and the basic characteristics food requirement can be carried out.
The data summarizes the agricultural and socio-economic status of the five Central Asian countries ( Kazakhstan, Kyrgyzstan, Tajikistan, Uzbekistan and Turkmenistan ) in 2015.The data comes from the statistical yearbooks of the five Central Asian countries ( Kazakhstan, Kyrgyzstan, Tajikistan, Uzbekistan and Turkmenistan ), including the Total Population, Cultivated Land Area, Grain production area, GDP, The proportion of agricultural GDP to total GDP and The proportion of industrial GDP to total GDP and Forest Area. Detailed statistics of the six socio-economic factors of the five Central Asian countries are given. Statistics show that each of the six elements of the five Central Asian countries has its own focus. The data provides basic data for the project, facilitates analysis of the ecological and social situation in Central Asia, and provides data support for the future data analysis of the project.