Cultivated land dataset of countries along the Belt and Road (1961-2015)

The data set records the Cultivated land of 1961-2015 countries along 65 countries along the Belt and Road. Arable land (in hectares) includes land defined by the FAO as land under temporary crops (double-cropped areas are counted once), temporary meadows for mowing or for pasture, land under market or kitchen gardens, and land temporarily fallow. Land abandoned as a result of shifting cultivation is excluded.Data sources: Food and Agriculture Organization, electronic files and web site. The data collected by the Food and Agriculture Organization (FAO) of the United Nations from official national sources through the questionnaire are supplemented with information from official secondary data sources. The secondary sources cover official country data from websites of national ministries, national publications and related country data reported by various international organizations. Data on agricultural land are valuable for conducting studies on a various perspectives concerning agricultural production, food security and for deriving cropping intensity among others uses. Agricultural land indicator, along with land-use indicators, can also elucidate the environmental sustainability of countries' agricultural practices. The dataset contains 3 tables:Arable land (hectares), Arable land(hectares per person), Arable land (% of land area)

0 2020-05-14

Health expenditure of countries along "One Belt and One Road" (2000-2015)

The data set records the health expenditure of 2000-2015 countries along 65 countries along the belt and road. Current expenditures on health per capita in current US dollars. Estimates of current health expenditures include healthcare goods and services consumed during each year.Data sources: World Health Organization Global Health Expenditure database (http://apps.who.int/nha/database). The data set contains 2 tables:Current health expenditure (% of GDP),Current health expenditure (% of GDP)

0 2020-05-14

Gross national expenditure of countries along the Belt and Road (1960-2017)

The data set records the gross national expenditure of 1960-2017 countries along 65 countries along the belt and road. Gross national expenditure (formerly domestic absorption) is the sum of household final consumption expenditure (formerly private consumption), general government final consumption expenditure (formerly general government consumption), and gross capital formation (formerly gross domestic investment). Data are in current U.S. dollars. Data sources: World Bank national accounts data, and OECD National Accounts data files. The dataset contains 5 tables:Gross national expenditure (constant 2010 US$),Gross national expenditure (constant LCU),Gross national expenditure (current LCU),Gross national expenditure (current US$),Gross national expenditure (% of GDP).

0 2020-05-14

The data set records the gross national income of 1960-2017 countries along 65 countries along the belt and road. GNI (formerly GNP) is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. Data sources: World Bank national accounts data, and OECD National Accounts data files. The data set contains 5 tables:GNI (constant 2010 US$),GNI (constant LCU),GNI (current LCU),GNI (current US$),GNI growth (annual %).

0 2020-05-14

Merchandise exports and imports dataset of countries along the Belt and Road (1960-2017)

The data set records the merchandise exports and imports of 1960-2017 countries along 65 countries along the belt and road. Merchandise imports show the c.i.f. value of goods received from the rest of the world valued in current U.S. dollars.Merchandise exports show the f.o.b. value of goods offered to the rest of the world valued in current U.S. dollars.Data sources:The data on total imports of goods (merchandise) are from the World Trade Organization (WTO), which obtains data from national statistical offices and the IMF's International Financial Statistics, supplemented by the Comtrade database and publications or databases of regional organizations, specialized agencies, economic groups, and private sources (such as Eurostat, the Food and Agriculture Organization, and country reports of the Economist Intelligence Unit). The data set contains 2 tables: Merchandise imports (current US$),Merchandise exports (current US$).

0 2020-05-14

Statistical yearbook of Xinjiang (2006-2015)

Statistical Yearbook of Xinjiang 2006-2015, data from China statistical database: www.shujuku.org.The xinjiang statistical Yearbook system collects the economic and social statistical data of the whole region, regions and counties (cities) from 2006 to 2015. It is an annual publication that comprehensively reflects the economic and social development of xinjiang uygur autonomous region.The Yearbook includes: national economic accounting;Population and employment;Investment in fixed assets;Foreign economic trade and tourism;Resources and environment;Energy;Prices;Agriculture;Industry;The construction industry;Transportation and postal services;Wholesale and retail, accommodation and catering;The financial sector.Education, technology and culture;Statistics on health and environmental conditions.This data source is based on several important sectors of the country and has high credibility. It is the basis for understanding the impact of cryosphere changes on socio-ecology-economy, and also the basis for offering advice on how to deal with adverse changes.

0 2020-05-14

Qilian Mountain prefecture level city and county level social and economic development data set (1949-2018)

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.

0 2020-05-14

Population, urbanization, GDP and industrial structure forecast scenario data of the Urmuqi River Basin (Version 1.0) (2010-2050)

Taking 2005 as the base year, the future population scenario prediction adopted the Logistic model of population, and it not only can better describe the change pattern of population and biomass but is also widely applied in the economic field. The urbanization rate was predicted using the urbanization Logistic model. Based on the existing urbanization horizontal sequence value, the prediction model was established by acquiring the parameters in the parametric equation applying nonlinear regression. The urban population was calculated by multiplying the predicted population by the urbanization rate. The Logistic model was used to predict the future gross national product of each county (or city), and then, according to the economic development level of each county (or city) in each period (in terms of real GDP per capita),the corresponding industrial structure scenarios in each period were set, and each industry’s output value was predicted. The trend of changes in industrial structure in China and the research area lagged behind the growth of GDP, and, therefore, it was adjusted according to the need of the future industrial structure scenarios of the research area.

0 2020-04-28

Vulnerability forecast scenarios dataset of the water resources, agriculture, and ecosystem of the Heihe River Basin (Version 1.0) (2010-2050)

By applying Supply-demand Balance Analysis, the water resource supply and demand of the whole river basin and each county or district were calculated, based on which the vulnerability of the water resources system of the basin was evaluated. The IPAT equation was used to set a future water resource demand scenario, setting variables such as future population growth rate, economic growth rate, and unit GDP water consumption to establish the scenario. By taking 2005 as the base year and using assorted forecasting data of population size and economic scale, the future water demand scenarios of various counties and cities from 2010 to 2050 were forecast. By applying the basic structure of the HBV conceptual hydrological model of the Swedish Hydrometeorological Institute, a model of the variation tendency of the basin under climate change was designed. The glacial melting scenario was used as the model input to construct the runoff scenario under climate change. According to the national regulations of the water resources allocation of the basin, a water distribution plan was set up to calculate the water supply comprehensively. Considering of the supply and demand situation, the water resource system vulnerability was evaluated by the water shortage rate. By calculating the (grain production) land pressure index of the major counties and cities in the basin, the balance of supply and demand of land resources under the climate change, glacial melt and population growth scenarios was analyzed, and the vulnerability of the agricultural system was evaluated. The Miami formula and HANPP model were used to calculate the human appropriation of net primary biomass and primary biomass in the major counties and cities for the future, and the vulnerability of ecosystems from the perspective of supply and demand balance was assessed.

0 2020-04-28

Population, urbanization, GDP and industrial structure forecast scenario data of the Heihe River Basin (Version 1.0) (2010-2050)

Taking 2000 as the base year, the future population scenario prediction adopted the Logistic model of population, and it not only can better describe the change pattern of population and biomass but also is widely applied in the economic field. The urbanization rate was predicted using the urbanization Logistic model. Based on the existing urbanization horizontal sequence value, the prediction model was established by acquiring the parameters in the parametric equation applying nonlinear regression. The urban population was calculated by multiplying the predicted population by the urbanization rate. The Logistic model was used to predict the future gross national product of each county (or city), and then, according to the economic development level of each county (or city) in each period (in terms of real GDP per capita), the corresponding industrial structure scenarios in each period were set, and the output value of each industry was predicted. The trend of industrial structure changing in China and the research area lagged behind the growth of GDP, so it was adjusted according to the need of the future industrial structure scenarios of the research area.

0 2020-04-28