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 water resource supply resilience of countries along the “Belt and Road” reflects the level of water supply resilience of countries along the route. The higher the data value, the stronger the resilience of water supply in countries along the route. Preparation of data products for water supply resilience of countries along the “Belt and Road”, using the annual precipitation, surface runoff and underground net data produced by FLDAS (Famine Early Warning System Network Land Data Assimilation System) based on the Noah land surface model from 2000 to 2019 The flow simulation data set, on the basis of considering the year-to-year changes, based on sensitivity and adaptability analysis, and through comprehensive diagnosis, prepared and generated water resource supply resilience products. The data set of water supply resilience of countries along the “Belt and Road” has important reference significance for analyzing and comparing the current status of water resources supply resilience in various countries.
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 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 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 resilience of road traffic development in countries along the Belt and Road reflects the level of resilience of road traffic development in the countries along the Belt and Road, and the higher the value of the data, the stronger the resilience of road traffic development in the countries along the Belt and Road. The road traffic development resilience data product is prepared by referring to the World Bank statistical database, using the year-by-year data of four indicators, namely road mileage, railway mileage, air traffic and container terminal throughput of the countries along the "Belt and Road" from 2000 to 2019, and based on the year-by-year changes of each indicator, based on sensitivity Based on the sensitivity and adaptability analysis, the road traffic development resilience product is prepared through comprehensive diagnosis. The data set of road traffic development resilience of countries along the "Belt and Road" is an important reference for analysing and comparing the current road traffic development resilience of countries.
XU Xinliang
The resilience of population urbanisation development in countries along the Belt and Road reflects the level of resilience of population urbanisation development in the countries along the Belt and Road, with higher values indicating stronger resilience of population urbanisation development in the countries along the Belt and Road. The data on the resilience of population urbanisation development are prepared with reference to the World Bank's statistical database, using year-on-year data on two indicators, namely the number of urban population and the number of population in urban agglomerations with a population of over one million, from 2000 to 2019, and based on sensitivity and adaptability analysis, taking into account the year-on-year changes of each indicator. Based on the sensitivity and adaptability analysis, the product of the resilience of population urbanisation development was prepared through comprehensive diagnosis. "The data set on the resilience of population urbanisation development in the countries along the Belt and Road is an important reference for analysing and comparing the resilience of population urbanisation development in various countries.
XU Xinliang
"The 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 resilience of population growth in countries along the Belt and Road reflects the level of resilience of population growth in the countries along the Belt and Road, and the higher the value of the data, the stronger the resilience of population growth in the countries along the Belt and Road. The World Bank's statistical database was used to prepare the Resilience to Population Growth data product, which uses year-on-year data on the population of countries along the Belt and Road from 2000 to 2019. The Resilience to Population Growth product is based on sensitivity and adaptation analysis. Please refer to the documentation for the methodology of preparing the dataset. "The resilience dataset is an important reference for analysing and comparing the current resilience of population growth in countries along the Belt and Road.
XU Xinliang
The data set covers 599 meteorological stations in five Central Asian countries, including the following elements: * daily maximum temperature, * daily minimum temperature, * observed temperature, * Precipitation (i.e. rain, melting snow), covering the following dates: 1980-1986; 1996-2005; 2010; 2014; 2015 The data comes from ghcn-d, a data set containing global land area daily observation data, which integrates climate records. The data is a direct measurement of surface temperature, without interpolation or model assumptions, and contains many long-term site records. The disadvantage is uneven space coverage. Due to changes in observation time, site location, and the type of thermometer used, the records contain many heterogeneity. For more information about this dataset, see https://www.ncdc.noaa.gov/ghcnd-data-access
This data set contains the results of the calculation of Net Primary Productivity (NPP) on the Tibetan Plateau based on ecological models and remote sensing data from 1982 to 2006. Ecosystem NPP of the Tibetan Plateau was generated based on the remote sensing Advanced Very High Resolution Radiometer (AVHRR) data and the Carnegie-Ames-Stanford Approach (CASA) model(1982-2006), the soil carbon content was generated based on the second soil census data, and the biomass carbon data were generated based on the High Resolution Biosphere Model (HRBM) model. Forest ecosystem NPP of the Tibetan Plateau (1982-2006): npp_forest82.e00，npp_forest83.e00，npp_forest84.e00，npp_forest85.e00，npp_forest86.e00， npp_forest87.e00，npp_forest88.e00，npp_forest89.e00，npp_forest90.e00，npp_forest91.e00， npp_forest92.e00，npp_forest93.e00，npp_forest94.e00，npp_forest95.e00，npp_forest96.e00， npp_forest97.e00，npp_forest98.e00，npp_forest99.e00，npp_forest00.e00，npp_forest01.e00， npp_forest02.e00，npp_forest03.e00，npp_forest04.e00，npp_forest05.e00，npp_forest06.e00 Grassland ecosystem NPP of the Tibetan Plateau(1982-2006)： npp_grass82.e00，npp_grass83.e00，npp_grass84.e00，npp_grass85.e00，npp_grass86.e00， npp_grass87.e00，npp_grass88.e00，npp_grass89.e00，npp_grass90.e00，npp_grass91.e00， npp_grass92.e00，npp_grass93.e00，npp_grass94.e00，npp_grass95.e00，npp_grass96.e00， npp_grass97.e00，npp_grass98.e00，npp_grass99.e00，npp_grass00.e00，npp_grass01.e00，npp_grass02.e00，npp_grass03.e00，npp_grass04.e00，npp_grass05.e00，npp_grass06.e00. Biomass carbon and soil carbon of the Tibetan Plateau： Biomass.e00，Socd.e00. The soil carbon content data （Socd） are generated based on data of the second soil census of China and Soil Map of China (1:1,000,000) by soil subclass interpolation. The NPP data are generated from the CASA model and AVHRR data simulation: Potter CS, Randerson JT, Field CB et al. Terrestrial ecosystem production: a process model based on global satellite and surface data. Global Biogeochemical Cycles, 1993, 7: 811–841. The biomass carbon data are generated via HRBM model simulation： McGuire AD, Sitch S, et al. Carbon balance of the terrestrial biosphere in the twentieth century: Analyses of CO2, climate and land use effects with four process-based ecosystem models. Global Biogeochem. Cycles, 2001, 15 (1), 183-206. The raw data are mainly remote sensing data and field observation data with high accuracy; the verification and adjustment of the measured data in the field during the production were undertaken to maintain the error of the simulation results and the field measured data within the acceptable range as much as possible; the verification results of the NPP data and the field measured data show that the error remains within 15%. The spatial resolution is 0.05°×0.05° (longitude×latitude).
ZHOU Caiping
The data defines LC classes using a set of classifiers. The system was designed as a hierarchical classification, which allows adjusting the thematic detail of the legend to the amount of information available to describe each LC class, whilst following a standardized classification approach. As the CCI-LC maps are designed to be globally consistent, their legend is determined by the level of information that is available and that makes sense at the scale of the entire world. The “level 1” legend – also called “global” legend – presented in Table 3-1 meets this requirement. This legend counts 22 classes and each class is associated with a ten values code (i.e. class codes of 10, 20, 30, etc.). The CCI-LC maps are also described by a more detailed legend, called “level 2” or “regional”. This level 2 legend makes use of more accurate and regional information – where available – to define more LCCS classifiers and so to reach a higher level of detail in the legend. This regional legend has therefore more classes which are listed in Appendix 1. The regional classes are associated with nonten values (i.e. class codes such as 11, 12, etc.). They are not present all over the world since they were not properly discriminated at the global scale.
YANG Yu
The data set records the operation of the pollution source monitoring center in Haixi Prefecture of Qinghai Province from July 2018 to September 2019. The data is collected from the Department of ecological environment of Haixi Prefecture. The data set contains 42 text files, recording the weekly report of Haixi pollution source monitoring center from July 2018 to September 2019, and each file records the content of the weekly report once. Including the video monitoring system operation, online monitoring system operation, new online monitoring system construction acceptance, online monitoring system construction acceptance, online monitoring data analysis and transmission efficiency. Data coverage time range: July 16, 2018 to September 1, 2019.
Ecological Environment Bureau of Haixi Prefecture Qinghai Province
The UHSLC offers tide gauge data with two levels of quality-control (QC). Fast Delivery (FD) data are released within 1-2 months of data collection and receive only basic QC focused on large level shifts and obvious outliers. The GLOSS/CLIVAR (formerly known as the WOCE) "fast" sea level data is distributed as hourly, daily, and monthly values. This project is supported by the NOAA Climate and Global Change program, and is one of the activities of the University of Hawaii Sea Level Center. Each file is given a name "h###.dat" where "h" denotes hourly sea level data and "###" denotes the station number. A file exists for every station with hourly data. The UHSLC datasets are GLOSS data streams (read more here). There are many tide gauge records in the UHSLC database, but the backbone is the GLOSS Core Network (GCN) – a global set of ~300 tide gauge stations that serve as the foundation of the global in situ sea level network. The network is designed to provide evenly distributed sampling of global coastal sea level variation at a variety of time-scales.
DONG Wen, University of hawaii sealevel center （UHSLC）
"Disaster data for countries along the belt and road, mainly from the global disaster database.The records information of disaster database are from the United Nations, government and non-governmental organizations, research institutions and the media. It's documented in detail such as the country where the disaster occurred, the type of disaster, the date of the disaster, the number of deaths and the estimated economic losses. This study extracts the natural disaster records of the countries along the One Belt And One Road line one by one from the database, and finally forms the disaster database of 9 major disasters of the 65 countries. The natural disaster records collected can be roughly divided into nine categories, including: floods, landslides, extreme temperatures, storms, droughts, forest fires, earthquakes, mass movements and volcanic activities. From 1900 to 2018, a total of 5,479 disaster records were recorded in countries along the One Belt And One Road. From 2000 to 2015, there were 2,673 disaster records. On this basis, the natural disasters of the countries along the belt and road are investigated from four aspects, including disaster frequency, death toll, disaster-affected population and economic loss assessment. Overall, since 1900, a total of 5479 natural disasters have occurred in countries along the One Belt And One Road, resulting in about 19 million deaths and economic losses of about 950 billion us dollars. Among them, the most frequent occurrence is flood and storm; the biggest economic losses are floods and earthquakes; the most affected people are flood and drought; drought and flooding are the leading causes of death
YIN Jun
The Tibetan Plateau in China covers six provinces including Tibet, Qinghai, Xinjiang, Yunnan, Gansu and Sichuan, including Tibet and Qinghai, as well as parts of Xinjiang, Yunnan, Gansu and Sichuan. The research on water and soil resources matching aims to reveal the equilibrium and abundance of water resources and land resources in a certain regional scale. The higher the level of consistency between regional water resources and the allocation of cultivated land resources, the higher the matching degree, and the superior the basic conditions of agricultural production. The general agricultural water resource measurement method based on the unit area of cultivated land is used to reflect the quantitative relationship between the water supply of agricultural production in the study area and the spatial suitability of cultivated land resources. The Excel file of the data set contains the generalized agricultural soil and water resource matching coefficient data of the Tibetan Plateau municipal administrative region in China from 2008 to 2015, the vector data is the boundary data of the Tibetan Plateau municipal administrative region in China in 2004, and the raster data pixel value is the generalized agricultural soil and water resource matching coefficient of the year in the region.
DONG Qianjin, DONG Lingxiao
1)The data content includes three stages of soil erosion intensity in Qinghai-Tibet Plateau in 1992, 2005 and 2015, and the grid resolution is 300m. 2) China soil erosion prediction model (CSLE) was used to calculate the soil erosion amount of more than 4,000 investigation units on the Qinghai-Tibet Plateau. Soil erosion was interpolated according to land use on Qinghai-Tibet Plateau. According to the soil erosion classification standard, the soil erosion intensity map of Qinghai-Tibet Plateau was obtained. 3) By comparing the differences of three-stage soil erosion intensity data, it conforms to the actual change law and the data quality is good. 4) The data of soil erosion intensity are of great significance to the study of soil erosion in the Qinghai-Tibet Plateau and the sustainable development of local ecosystems. In the attribute table, "Value" represents the erosion intensity level, from 1 to 6, the value represents slight, mild, moderate, intense, extremely intense and severe. "BL" represents the percentage of echa erosion intensity in the total area.
ZHANG Wenbo
This data set contains the statistical information of natural disasters in Qinghai Tibet Plateau in the past 50 years (1950-2002), including drought, snow disaster, frost disaster, hail, flood, wind disaster, lightning disaster, cold wave and strong cooling, low temperature and freezing damage, gale sandstorm, insect disaster, rodent damage and other meteorological disasters. Qinghai and Tibet are the main parts of the Qinghai Tibet Plateau. The Qinghai Tibet Plateau is one of the Centers for the formation and evolution of biological species in China. It is also a sensitive area and fragile zone for the international scientific and technological circles to study climate and ecological environment changes. Its complex terrain conditions, high altitude and severe climate conditions determine that the ecological environment is very fragile, It has become the most frequent area of natural disasters in China. The data were extracted from "China Meteorological Disaster Canon · Qinghai volume" and "China Meteorological Disaster Canon · Tibet Volume", which were manually input, summarized and proofread.
Statistical Bureau Statistical Bureau
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
The temperature humidity index (THI) was proposed by J.E. Oliver in 1973. Its physical meaning is the temperature after humidity correction. It considers the comprehensive impact of temperature and relative humidity on human comfort. It is an important index to measure regional climate comfort. On the basis of referring to the existing classification standards of physiological and climatic evaluation indexes, combined with the natural and geographical characteristics of the Qinghai Tibet Plateau and facing the needs of human settlements suitability evaluation in the Qinghai Tibet Plateau, the temperature and humidity index and its suitability zoning results of the Qinghai Tibet Plateau (more than 3000 meters) are developed (including unsuitable, critical suitable, general suitable, relatively suitable and highly suitable).
LI Peng, LIN Yumei
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