"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.
This data is conventional and satellite data of six hour resolution for the Great Lakes region of Central Asia. The conventional data include the observation of ground stations and sounding stations in the Great Lakes region of Central Asia and its surrounding areas (China, Kazakhstan, Kyrgyzstan, Turkmenistan, Tajikistan, Uzbekistan, Afghanistan, Russia, Iran, Pakistan, India, etc.), and the observation elements include temperature, pressure, wind speed and humidity, with the average number of stations in each time It is about 600, and the interval between stations is between 10-100km; the satellite data comes from the cloud guide wind retrieved by polar orbiting satellites (NOAA series and MetOp Series). All the data are from the global telecommunication system (GTS), and the observation data with poor quality are eliminated through quality control. The data can be applied to the data assimilation of the Great Lakes region in Central Asia, and also to the numerical simulation of the Great Lakes region in Central Asia.
The Pan Third Pole is sensitive to global climate change, its warming rate is more than twice of the global rate, and it is affected by the synergy of westerlies and monsoons. How to respond to climate change will have a profound impact on regional ecological security. However, the estimation of NPP by current products is still uncertain. For this reason, this product combines multi-source remote sensing data, including AVHRR NDVI, MODIS reflectivity data, a variety of climate variables (temperature, precipitation, radiation, VPD) and a large number of field measured data, and uses machine learning algorithm to retrieve the net primary production capacity of Pan third polar ecosystem.
Global land cover data are key sources of information for understanding the complex interactions between human activities and global change. FROM-GLC (Finer Resolution Observation and Monitoring of Global Land Cover) from Tsinghua is the 30 m resolution global land cover maps produced. The Global land cover data of all 34 key nodes of pan-third pole region are produced through analyse by argis. The classfication system is crop(10), forest(20), grass(30), shrbu(40), wetland(50), water(60), tundra(70), impervious(80), Bareland(90), snow/ice(100), cloud(120). Finally, This data set serves as the research basis for all remote sensing data and provides baseline data for the project.
GE Yong LING Feng ZHANG Yihang
Based on the multispectral remote sensing data of 210 Landsat 8 oli satellites, corrected and inlaid as false color composite image (RGB: 654), the method of artificial visual interpretation is adopted, and the result of band ratio method is referred, combined with SRTM DEM v4.1 data and Google data The images of earth and hj1a / 1b satellites in different seasons of the same year, excluding the influence of mountain shadow and seasonal snow, referring to the first and second glacial cataloguing data in China, excluding the steep cliffs and exposed bedrock in non glacial areas, comprehensively extracting the thematic vector data of net glaciers, excluding the surface moraine coverage area with unclear glacier end position, and the accuracy of glacial boundary digitization is half Pixel (15m). Through comparative analysis, it can be seen that the mountain glacier data extracted based on multi data sources, reference to multi method results and integration of expert experience and knowledge is more accurate.
The data of this study is mainly based on Google Earth Engine big data cloud processing platform. Sentinel-2 of The Three River Headwater region, Pul and Yukon River Basins in 2017 is selected as the basic data, STRM-DEM and Global Surface Water are used as auxiliary data. AWEIn，AWEIs，WI2015，MNDWI，NDWI and other index threshold extraction are selected to obtain seasonal water body and permanent water body according to annual water frequency(spatial resolution 10m). This water data product provides effective basic data for high spatial-temporal resolution water body change and permafrost hydrological analysis.
Gf-2 satellite is the first civil optical remote sensing satellite independently developed by China with a spatial resolution better than 1 meter. It is equipped with two high-resolution 1-meter panchromatic and 4-meter multi-spectral cameras, and the spatial resolution of the sub-satellite can reach 0.8 meters. This data set is the remote sensing image data of 6 jing gaofen-2 satellite in 2017.The folder list is: GF2_PMS1_E100.5_N37.2_20171013_L1A0002678101 GF2_PMS1_E100.5_N37.4_20171013_L1A0002678097 GF2_PMS1_E100.6_N37.6_20171013_L1A0002678096 GF2_PMS2_E100.3_N37.4_20170810_L1A0002534662 File naming rules: satellite name _ sensor name _ center longitude _ center latitude _ imaging time _L****
China Centre for Resources Satellite Data and Application
The data set is the average wind speed of the Central Asia including three temperate deserts, the Karakum, Kyzylkum and Muyunkun Deserts, and one of the world's largest arid zones. The data was obtained by GLDAS global three-hour assimilation data extraction calculation. The data is in tif format. The space and time resolutions are 0.25° and 3 hours respectively. The time is from 01, January, 2017 to 31, December, 2017. The data set uses the the Geodetic coordinate system. We can use the data to calculate the sand flux. It can be used for the investigation of the Desert oil and gas field, and oasis cities.
Vegetation survey data is essential to study the structure and function of the ecosystems. The North Tibet is abundant in grassland ecosystems, including alpine meadow, alpine grassland, and alpine degraded grassland. Due to the unique geographical location, high altitude and anoxic environment, the community survey data in the North Tibetan Plateau is relatively rare. Based on the accumulation of preliminary work, the research team carried out a more comprehensive vegetation survey in 15 counties of the North Tibetan Plateau in the growing season of 2017. This data set includes biomass data inside and outside the fences of the 23 sampling plots from Nagqu to Ritu of the North Tibet Transect. This data set can be used for productivity spatial analysis and mode calibration.
ZHANG Xianzhou NIU Ben
This data set includes the monthly synthesis of 30m*30m surface vegetation index products in Qilian mountain area in 1986, 1990, 1995, 2000, 2005, 2010, 2015, and 2017. Max value composition (MVC) method was used to synthesize monthly NDVI products on the surface using the reflectivity data of Landsat 5, Landsat 8 and sentinel 2 channels from Red and NIR channels. The data are synthesized monthly through Google Earth Engine cloud platform, and the missing pixels are interpolated by calculating the index of the model. The quality of the data is good, and it can be used in environmental change monitoring and other fields.
WU Jinhua ZHONG Bo WU Junjun
This data is originated from the 1:100,000 national basic geographic database, which was open freely for public by the National Basic Geographic Information Center in November 2017. The boundary of the Qinghai-Tibet Plateau was spliced and clipped as a whole, so as to facilitate the study on the Qinghai-Tibet plateau. This data set is the 1:100,000 administrative boundaries of the qinghai-tibet plateau, including National_Tibet_line、 Province_Tibet、City_Tibet、County_Tibet_poly and County_Tibet_line. Administrative boundary layer (County_Tibet_poly) property name and definition: Item Properties Describe Example PAC Administrative division code 513230 NAME The name of the County line name Administrative boundary layer (BOUL) attribute name and definition: Item Properties Describe Example GB classification code 630200 Administrative boundary layer (County_Tibet_line) attribute item meaning: Item Properties Describe Example GB 630200 Provincial boundary GB 640200 Prefectural, municipal and state administrative boundaries GB 650201 county administrative boundaries (determined)
National Basic Geographic Information Center
Qinghai Tibet Plateau is the largest permafrost area in the world. At present, some permafrost distribution maps have been compiled. However, due to the limited data sources, unclear standards, insufficient verification and lack of high-quality spatial data sets, there is great uncertainty in drawing Permafrost Distribution Maps on TP. Based on the improved medium resolution imaging spectrometer (MODIS) surface temperature (LSTS) model of 1 km clear sky mod11a2 (Terra MODIS) and myd11a2 (Aqua MODIS) product (reprocessing version 5) in 2003-2012, the data set simulates the distribution of permafrost and generates the permafrost map of Qinghai Tibet Plateau. The map was verified by field observation, soil moisture content and bulk density. Permafrost attributes mainly include: seasonally frozen ground, permafrost and unfrozen ground. The data set provides more detailed data of Permafrost Distribution and basic data for the study of permafrost in the Qinghai Tibet Plateau.
This dataset contains daily 0.05°×0.05° land surface soil moisture products in Qilian Mountain Area in 2017. The dataset was produced by utilizing the multivariate statistical regression model to downscale the “AMSR-E and AMSR2 TB-based SMAP Time-Expanded Daily 0.25°×0.25° Land Surface Soil Moisture Dataset in Qilian Mountain Area (SMsmapTE, V1)”. The auxiliary datasets participating in the multivariate statistical regression include GLASS Albedo/LAI/FVC, 1km all-weather surface temperature data in western China by Ji Zhou and Lat/Lon information.
CHAI Linna ZHU Zhongli LIU Shaomin
This data set contains the observation data of 10 m tower eddy covariance instrument from January 1, 2017 to December 31, 2017. The site is located in donghuayuan Town, Huailai County, Hebei Province. The longitude and latitude of the observation point are 115.7880e, 40.3491n and 480m above sea level. The acquisition frequency of the eddy correlator is 10Hz, the height of the frame is 5m, the ultrasonic direction is due north, and the distance between the ultrasonic anemometer (csat3) and the CO2 / H2O analyzer (li7500a) is 15cm. The released data is 30 minutes data obtained by post-processing the original collected 10Hz data by eddypro software. The main processing steps include: outlier value elimination, delay time correction, coordinate rotation (secondary coordinate rotation), frequency response correction, ultrasonic virtual temperature correction and density (WPL) correction. At the same time, the quality evaluation of each flux value is mainly the test of atmospheric stability (Δ st) and turbulence similarity characteristics (ITC). The 30 min flux values output after processing were also screened: (1) the data of instrument error; (2) the data of 1 h before and after precipitation; (3) the data of 10 Hz original data missing more than 10% every 30 min; (4) the observation data of weak turbulence at night (U * less than 0.1 M / s) were eliminated. The average period of observation data is 30 minutes. There are 48 data in a day, and the missing data is marked as - 6999. From May 27 to July 22, the data was missing due to problems with the ultrasonic anemometer. The observational data released by eddy correlator include date / time, wind direction WDIR (°), horizontal wind speed wnd (M / s) and standard deviation of lateral wind speed STD_ Uy (M / s), ultrasonic virtual temperature TV (k), water vapor density H2O (g / m3), carbon dioxide concentration CO2 (mg / m3), friction velocity ustar (M / s), obuhof length, sensible heat flux HS (w / m2), latent heat flux Le (w / M2), carbon dioxide flux FC (mg / (M2S)), quality identification of sensible heat flux QA_ HS, quality identification of latent heat flux QA_ LE。 The quality identification of sensible heat, latent heat and carbon dioxide flux can be divided into three levels (quality mark 0: (Δ st < 30, ITC < 30); 1: (Δ st < 100, ITC < 100); the rest are 2). The meaning of data time, for example, 0:30 represents the average of 0:00-0:30; the data is stored in *. XLS format. Guo et al, 2020 is used for site introduction and Liu et al, 2013 for data processing
LIU Shaomin XU Ziwei
The data set contains the observation data of 40m tower vortex correlator on January 1, 2017, solstice, 2017, December 31, 2017.The station is located in east garden town, huailai county, hebei province.The latitude and longitude of the observation point is 115.7923E, 40.3574N, and the altitude is 480m.The acquisition frequency of vortex correlativity instrument is 10Hz, the frame height is 3.5m, the ultrasonic direction is due to the north, and the distance between the ultrasonic anemometer (CSAT3) and the CO2/H2O analyzer (EC150) is 0cm. The released data is the 30-minute data obtained from the post-processing of the original collected 10Hz data with Eddypro software. The main steps of the processing include: outfield value elimination, delay time correction, coordinate rotation (secondary coordinate rotation), frequency response correction, ultrasonic virtual temperature correction and density (WPL) correction.Quality assessment for each intercompared to at the same time, mainly is the atmospheric stability (Δ st) and turbulent characteristics of similarity (ITC) test.The 30min pass value output after processing was also screened :(1) the data when the instrument was wrong was removed;(2) data of 1h before and after precipitation were excluded;(3) the missing rate of 10Hz original data is more than 10% every 30min;(4) the observed data of weak turbulence at night were excluded (u* less than 0.1m/s).The average period of observation data was 30 minutes, 48 data a day, and the missing data was marked as -6999.There are many negative values of water vapor density measured by EC150 in winter, filled with -6999. The observation data released by vortex correlator include:Date/Time for the Date/Time, wind Wdir (°), Wnd horizontal wind speed (m/s), standard deviation Std_Uy lateral wind speed (m/s), ultrasonic virtual temperature Tv (K), the water vapor density H2O (g/m3), carbon dioxide concentration CO2 (mg/m3), friction velocity Ustar) (m/s), the length of cloth hoff, sensible heat flux Hs (W/m2), latent heat flux LE (W/m2), carbon dioxide flux Fc (mg/(m2s)), the quality of the sensible heat flux identifier QA_Hs, the quality of the latent heat flux identifier QA_LE.The quality of the sensible heat and latent heat, carbon dioxide flux identification is divided into three (quality id 0: (Δ st < 30, the ITC < 30);1: (Δ st < 100, ITC < 100);The rest are 2).The meaning of data time, such as 0:30 represents the average between 0:00 and 0:30;The data is stored in *.xls format.The data was missing during the period from May 26 to May 29 due to instrument calibration. Guo et al, 2020 is used for site introduction and Liu et al, 2013 for data processing.
LIU Shaomin XU Ziwei XIAO Qing
The data set contains observations from the 10m tower automatic weather station on January 1, 2017 at solstice on December 31, 2017.The station is located in east garden town, huailai county, hebei province.The latitude and longitude of the observation point is 115.7880E, 40.3491N, and the altitude is 480m. The automatic weather station is installed on a 10m tower, the acquisition frequency is 30s, and the output time is 10min.The observation factors include air temperature and relative humidity (5m), and the direction is due north.The wind speed (10m), the wind direction (10m), the direction is due to the north;Air pressure (installed in waterproof box);Rainfall (10m);The four-component radiation (5m), the direction is due to the south;The infrared surface temperature (5m), the arm is facing south, and the probe is facing vertically downward.The soil temperature and humidity probe was buried at 1.5m to the south of the meteorological tower. The buried depth of the soil temperature probe was 0cm, 2cm, 4cm, 10cm, 20cm, 40cm, 80cm, 120cm and 160cm. The buried depth of the soil moisture sensor was 2cm, 4cm, 10cm, 10cm, 10cm, 10cm, 20cm, 80cm, 120cm and 160cm.The average soil temperature was 2, 4cm underground.Soil hot flow plates (3) are buried in the ground 6cm. Processing and quality control of observation data :(1) ensure 144 data per day (every 10min). If data is missing, it will be marked by -6999;(2) eliminate the moments with duplicate records;(3) data that is obviously beyond the physical meaning or the range of the instrument is deleted;(4) the format of date and time is unified, and the date and time are in the same column.For example, the time is: 2017-6-1010:30.During January 1, solstice, April 15, there was a problem with the soil temperature sensor with a depth of 40cm, and the data was missing. Guo et al, 2020 is used for site introduction and Liu et al, 2013 for data processing
LIU Shaomin XU Ziwei
The data set contains the observation data of the evapotranspiration apparatus on January 1, 2017 (solstice) and December 31, 2017.The site is located in huailai county, hebei province, east garden town, the underlying surface for corn.The latitude and longitude of the observation point is 115.7880E, 40.3491N, and the altitude is 480m. The collection frequency of the evapotranspiration permeameter is 1 time/min, and the released data is 10min output data.The evapotranspiration meter is a cylindrical structure with a surface area of 1m2 and a buried depth of 1.5m. The observation accuracy of evapotranspiration is 0.01mm.Two evapotranspiration seeptometers were installed, one kept bare soil (lysimeter_1), the other for the corn underlay (lysimeter_2) during the growing season (May 10 - September 15).Soil temperature and humidity probe, soil water potential probe and soil heat flow plate are also installed in the evapotranspiration apparatus.The buried depth of the soil temperature sensor is 5cm, 30cm, 50cm, 100cm and 140cm.The buried depth of the soil water sensor is 2cm, 10cm, 20cm and 40cm.The soil heat flux plate is buried 10cm underground;The buried depth of the soil water potential sensor was 30cm and 140cm.Processing and quality control of observation data :(1) ensure 144 data per day (every 10min). If data is missing, it will be marked by -6999;(2) delete the data of observation anomalies caused during maintenance;(3) data that is obviously beyond the physical meaning or the range of the instrument is deleted;(4) the format of date and time is unified, and the date and time are in the same column.For example, the time is: 2016-6-10-10:30. The observation data released by the evapotranspiration permeameter include:Date/Time, weighing mass (i.l._1_wag_l_000 (Kg), i.l._2_wag_l_000 (Kg)), seepage mass (i.l._1_wag_d_000 (Kg), i.l._2_wag_d_000 (Kg)), soil heat flux (Gs_1_10cm, Gs_2_10cm) (W/m2),Multi-layer soil moisture (Ms_1_5cm, Ms_1_10cm, Ms_1_30cm, Ms_1_50cm, Ms_1_50cm, Ms_1_100cm, Ms_2_5cm, Ms_2_10cm, Ms_2_30cm, Ms_2_50cm, Ms_2_100cm) (%),Multi-layer soil temperature (Ts_1_5cm, Ts_1_30cm, Ts_1_50cm, Ts_1_100cm, Ts_1_140cm, Ts_2_140cm, ts_2_2_5cm, ts_2_2_50cm, Ts_2_100cm, Ts_2_140cm) (℃), soil water potential (TS_1_30 (hPa), TS_1_140 (hPa), TS_2_30 (hPa), TS_2_30 (hPa), TS_2_140 (hPa), TS_2_140 (hPa));The data is stored in *.xls format.
LIU Shaomin XU Ziwei ZHU Zhongli
The data set contains observations from the 40m tower automatic weather station on January 1, 2017 at solstice on December 31, 2017.The station is located in east garden town, huailai county, hebei province.The latitude and longitude of the observation point is 115.7923E, 40.3574N, and the altitude is 480m. The automatic weather station is installed on a 40m tower with a collection frequency of 30s and an output of 10min.The observation factors include 7 layers of air temperature and relative humidity (3m, 5m, 10m, 15m, 20m, 30m, 40m), and the direction is due north.Wind speed on the 7th floor (3m, 5m, 10m, 15m, 20m, 30m, 40m), wind direction (10m), heading due north;Air pressure (installed in waterproof box);Rainfall (3m);Four-component radiation and photosynthetic effective radiation (4m), pointing due south;Infrared surface temperature (8m), the arm is facing south, the probe is facing vertically downward;The soil temperature and humidity probe was buried 1.5m south of the meteorological tower. The soil temperature probe was buried at a depth of 2cm, 4cm, 10cm, 20cm, 40cm, 80cm, 120cm and 160cm. The soil moisture sensor was buried at a depth of 2cm, 4cm, 10cm, 20cm, 80cm, 120cm and 160cm.The average soil temperature was buried 2,4 cm underground.Soil hot flow plates (3) are buried in the ground 6cm. Processing and quality control of observation data :(1) ensure 144 data per day (every 10min). If data is missing, it will be marked by -6999;(2) eliminate the moments with duplicate records;(3) data that is obviously beyond the physical meaning or the range of the instrument is deleted;(4) the format of date and time is unified, and the date and time are in the same column.For example, the time is: 2017-6-1010:30. Guo et al, 2020 is used for site introduction and Liu et al, 2013 for data processing
LIU Shaomin XU Ziwei XIAO Qing
This data set contains the observation data of large aperture scintillator on January 7, 2017 at solstice on December 31, 2017. Two large aperture scintillator models BLS450 and zzlas were installed respectively.The site is located in huailai county, hebei province, east garden town, the underlying surface for corn.The latitude and longitude of the observation point is 115.7880E, 40.3491N, and the altitude is 480m.The effective height of the large aperture scintillation instrument is 14m, the optical diameter length is 1870m, the longitude and latitude of the transmitting end is 115.8023e, 40.3596n, and the longitude and latitude of the receiving end is 115.7825e, 40.3522n.The acquisition frequencies of BLS450 and zzlas were 5Hz and 1Hz respectively, with an average output of 1min. The original data of the large aperture scintillator is 1min, and the released data is the average data of 30min after processing and quality control. Among them, the sensible heat flux is mainly obtained by combining with the data of the automatic meteorological station and by iterative calculation based on the moning-obkhoff similarity theory.In the iterative calculation process, for BLS450, the stability function of Thiermann and Grassl, 1992 was selected.For zzlas, I'm going to pick Andreas 1988's stability function.The main quality control steps include :(1) eliminating the data of Cn2 reaching saturation;(2) eliminate data with weak demodulation signal strength;(3) data of the time of precipitation and the hour before and after the precipitation are excluded;(4) data of weak turbulence under stable conditions were excluded (u* < 0.1m/s). Several notes on the released data :(1) LAS data is mainly BLS450, the missing time is supplemented by zzlas observation, and the missing time of both is marked by -6999.(2) data table: Date/Time: Date/Time, Cn2: air refractive index structure parameter (m-2/3), H_LAS: sensible heat flux (W/m2).The meaning of data time, such as 0:30 represents the average between 0:00 and 0:30;The data is stored in *.xls format. Guo et al, 2020 is used for site introduction and Liu et al, 2013 for data processing
LIU Shaomin XU Ziwei
The data set is remote sensing image of Resource 3 No. 02 (ZY3-02). ZY3-02 was successfully launched from Taiyuan Satellite Launch Center at 11:17 on May 30, 2016 by Long March 4 B carrier rocket. China-made satellite imagery will be further strengthened in the areas of land surveying and mapping, resource survey and monitoring, disaster prevention and mitigation, agriculture, forestry and water conservancy, ecological environment, urban planning and construction, transportation and other fields. List of files: ZY302_PMS_E98.8_N37.4_201707_L1A0000156704 ZY302_PMS_E100.4_N37.0_20171127_L1A0000217243 ZY302_TMS_E99.5_N37.0_20170717_L1A0000160059 ZY302_TMS_E100.3_N36.6_20171127_L1A0000217279 ZY302_TMS_E100.4_N37.0_20170529_L1A0000139947 Folder Naming Rules: Satellite Name Sensor Name Central Longitude Central Latitude Acquisition Time L1****
China Centre for Resources Satellite Data and Application