Based on the data of Keyhole satellite in 1960s, using object-oriented supervised classification and manual visual interpretation and correction, water data products are produced. The total interpretation area is 645,000 km2, accounting for 96.28% of the study area, of which 18,844 km2 is missing in The Three River Headwater region, 4,220 km2 is missing in the Yukon River basin study area in Alaska, and 1,954 km2 is missing in the Pul River basin in West Siberia. The width of the minimum linear figure is more than 8 meters, the area of the minimum surface figure is more than 100 square meters, the trace accuracy is 2 pixels, and the first-class interpretation accuracy is more than 95%. The obtained high spatial resolution surface water data products provide effective data for the study of water changes in the 1960s and reliable basis for the study of frozen soil changes.
RAN Youhua
GLObal WAter BOdies database（GLOWABO）were obtained based on the GeoCoverTM Water bodies Extraction Method, Charles verpoorer et al， by Landsat 7 ETM + image in 2000 ± 3 years. The water extraction method combines the principal component analysis, threshold extraction, texture feature extraction and other methods, with a spatial resolution of 15 m and an overall accuracy of 91%. The data also includes water area, perimeter, shape index, elevation and other information. In this data set, The Three River Headwater region, Pul River Basin and Yukon River Basin, are selected to provide data support for polar hydrological research in the northern hemisphere.
Charles Verpoorter
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.
RAN Youhua
According to the global soil map. Net standard, the 0-1m soil depth is divided into 5 layers: 0-5cm, 5-15cm, 15-30cm, 30-60cm and 60-100cm. According to the principle of soil landscape model, the spatial distribution data products of soil organic carbon content in different layers are produced by using the digital soil mapping method. The source data of this data set comes from the soil profile data integrated by the major research plan integration project of Heihe River Basin (soil data integration and soil information product generation of Heihe River Basin, 91325301). Scope: Heihe River Basin; Projection: WGS · 1984 · Albers; Spatial resolution: 100M; Data format: TIFF; Dataset content: hh_soc_layer1.tif: 0-5cm soil organic carbon content; hh_soc_layer2.tif: 5-15cm soil organic carbon content; hh_soc_layer3.tif: 15-30cm soil organic carbon content; hh_soc_layer4.tif: 30-60cm soil organic carbon content; hh_soc_layer5.tif: 60-100cm soil organic carbon content;
SONG Xiaodong ZHANG Ganlin
The data set includes soil pH data of representative soil samples collected from July 2012 to August 2013 in the Heihe River Basin. The first soil survey was conducted in 2012. After the representativeness evaluation of collected samples, we conducted an additional sampling in 2013. These samples are representative enough to represent the soil variation in the Heihe River Basin, of which the soil variation in each landscape could be accounted for. The sampling depths in field refer to the sampling specification of Chinese Soil Taxonomy, in which soil samples were taken from genetic soil horizons.
SONG Xiaodong ZHANG Ganlin
Tibetan Plateau, located in southwest China, is one of the key areas affecting the Asian monsoon, and it is also an early warning area and sensitive area for global climate change. As the main parameter of surface energy balance, surface temperature represents the degree of energy and water exchange between earth and atmosphere, and is widely used in climatology, hydrology and ecology. The study of land-atmosphere interaction in Qinghai-Xizang Plateau urgently needs long time series and all-weather surface temperature data set with high temporal and spatial resolution. However, the frequent cloud cover characteristics in this area limit the use of the existing satellite thermal infrared remote sensing surface temperature data set. The generation method of this data set is an integrated method of thermal infrared and passive microwave surface temperature based on the time component decomposition model of surface temperature. This method was originally applied to Northeast China and its adjacent areas, and subsequently extended to western China including the Qinghai-Xizang Plateau. The main input data of this method are Aqua MODIS,Aqua AMSR-E,GCOM-W1 AMSR2 and other data, and the auxiliary data include leaf area index (LAI) products provided by satellite remote sensing, surface cover type data and so on. This method makes full use of the steady and unstable components of surface temperature provided by satellite thermal infrared remote sensing and passive microwave remote sensing, as well as the spatial correlation of surface temperature. The obtained all-weather surface temperature has good accuracy and image quality. The time span of the dataset is from 2003 to 2018, the time resolution is 2 times a day, and the spatial resolution is 1 km, which is expected to provide data support for related applications.
ZHOU Ji ZHANG Xiaodong LIU Shaomin
According to the statistical yearbook, different types of land use change areas in the middle reaches of China since liberation were collected and sorted out.
ZHANG Zhiqiang
The main body of the Tibetan Plateau is Qinghai Province and the Tibetan Autonomous Region. The economic and social data of Qinghai Province and the Tibetan Autonomous Region are the basis for the analysis and assessment of the basic data of sustainable development of populations, resources, environment and economic society on the Tibetan Plateau by integrating the basic data of natural sciences. Under normal circumstances, the statistical yearbooks of all provinces and regions are all in paper and CD-ROM versions, and users need to perform secondary editing before they can use them. This data set mainly relies on the raw data of the Statistical Yearbook of Qinghai Province and the Tibetan Autonomous Region to carry out data conversion and integrate the current economic and social data sets. The temporal coverage of the data is from 2007 to 2016, and the temporal resolution is one year. The spatial coverage is Qinghai Province and the Tibetan Autonomous Region of the Tibetan Plateau. The spatial resolution is the administrative unit of the prefecture or city. The data include information on population, economy, finance, agriculture, forestry, animal husbandry and fishery, investment in fixed assets, education and health.
WANG Shijin
This dataset is based on the long sequence (1981-2013)normalized difference vegetation index product(Version 3) of the latest NOAA Global Inventory Monitoring and Modeling System (GIMMS). First, the NDVI data products were re-sampled from the spatial resolution of 1/12 degree to 0.5 degree, then the time series of every year was smoothed by the double-logistic method, and the smoothed curvature was calculated. The maximum curvature of spring was selected as the returning green stage of the vegetation in Spring. This data can be used to analyze the temporal and spatial characteristics of the Holarctic vegetation phenology in Spring.
Xu Xiyan
The NDVI data set is the latest release of the long sequence (1981-2015) normalized difference vegetation index product of NOAA Global Inventory Monitoring and Modeling System (GIMMS), version number 3g.v1. The temporal resolution of the product is twice a month, while the spatial resolution is 1/12 of a degree. The temporal coverage is from July 1981 to December 2015. This product is a shared data product and can be downloaded directly from ecocast.arc.nasa.gov. For details, please refer to https://nex.nasa.gov/nex/projects/1349/.
The National Center for Atmospheric Research
The NDVI data set is the sixth version of the MODIS Normalized Difference Vegetation Index product (2001-2016) jointly released by NASA EOSDIS LP DAAC and the US Geological Survey (USGS EROS). The product has a temporal resolution of 16 days and a spatial resolution of 0.05 degrees. This version is a Climate Modeling Grid (CMG) data product generated from the original NDVI product (MYD13A2) with a resolution of 1 kilometer. Please indicate the source of these data as follows in acknowledgments: The MOD13C NDVI product was retrieved online courtesy of the NASA EOSDIS Land Processes Distributed Active Archive Center (LP DAAC), USGS/Earth Resources Observation and Science (EROS) Center, Sioux Falls, South Dakota, The [PRODUCT] was (were) retrieved from the online [TOOL], courtesy of the NASA EOSDIS Land Processes Distributed Active Archive Center (LP DAAC), USGS/Earth Resources Observation and Science (EROS) Center, Sioux Falls, South Dakota.
NASA
This dataset is based on the sixth edition of the MODIS normalized difference vegetation index product (2001-2014) jointly released by NASA EOSDIS LP DAAC and the US Geological Survey USGS EROS. The NDVI has a time resolution of 16 days and a spatial resolution of 0.05 degree. First,the NDVI data products were re-sampled from the spatial resolution of 0.05 degree to 0.5 degree, then the time series of every year was smoothed by the double-logistic method, and the smoothed curvature was calculated. The maximum curvature of spring was selected as the returning green stage of the vegetation in Spring. This data can be used to analyze the temporal and spatial characteristics of the Holarctic vegetation phenology in Spring.
United States Geological Survey (USGS) UitedStateGeologicalSurvey UitedStateGeologicalSurvey NASA EOSDIS LP DAAC Xu Xiyan
The Antarctic Peninsula is also called "Palmer peninsula" or "Graham land". Located in the southwest polar continent, it is the largest peninsula in the Antarctic continent and the farthest peninsula extending northward into the ocean (63 ° south latitude), bordering the Weddell Sea and berengske sea in the East and West. The Antarctic Peninsula is known as the "tropics" of Antarctica. This is a typical sub polar marine climate. Compared with the Antarctic continent, it is one of the warmest and wettest regions in Antarctica. There are a small number of pioneer plants distributed on the islands in the marginal area, mainly bryophytes and lichens. The spectrum and annotation data of Antarctic Peninsula and its surrounding plants are the spectral data of 37 sample points in 9 regions of Fildes Peninsula and Adeli island around the Antarctic Peninsula on January 7-22, 2018, which provide the background information for the study of the distribution and change of Antarctic plants.
XU Xiyan
The data set records the Chinese name, English name and the affiliation between the districts and counties in Tibet. The data were derived from the Tibet Society and Economics Statistical Yearbook and the Tibet Statistical Yearbook. The accuracy of the data is consistent with that of the statistical yearbook. This data set contains two tables: Table 1: The table of administrative divisions in Tibet contains 5 fields. Field 1: Regions Interpretation: Chinese names of the regions Field 2: English names of the regions Interpretation: English names of the regions Field 3: Districts and counties Interpretation: Chinese names of the districts and counties Field 4: English names of the districts and counties Interpretation: English names of the districts and counties Field 5: Land area Unit: square kilometers Table 2: The table of division changes of each county contains 5 fields. Field 1: Districts and counties Field 2: Year Field 3: Area Unit: square kilometers Field 4: Number of townships Field 5: Number of Village Committees
National Bureau of Statistics
The data set contains time series data on the local fiscal revenue, state financial subsidy revenue, local fiscal expenditure, and general budget expenditure in the Tibetan Autonomous Region from 1959 to 2016. The data were derived from the Tibet Society and Economics Statistical Yearbook and Tibet Statistical Yearbook. The accuracy of the data is consistent with that of the statistical yearbooks. Table 1: The table of total fiscal revenue, expenditure and related indexes contains 9 fields. Field 1: Year of the data Field 2: Total revenue, unit: 10,000 yuan Field 3: Local fiscal revenue of Tibet, unit: 10,000 yuan Field 4: General budget revenue, unit: 10,000 yuan Field 5: State financial subsidy revenue, unit: 10,000 yuan Field 6: Total fiscal expenditure, unit: 10,000 yuan Field 7: General budget expenditure, unit: 10,000 yuan Field 8: Total revenue index, unit: % Field 9: Total expenditure index, unit: % Table 2: The table of fiscal revenue and expenditure for each county contains 5 fields. Field 1: Districts and counties Field 2: Year Field 3: Local fiscal revenue, unit: 10,000 yuan Field 4: Local general budget fiscal revenue, unit: 10,000 yuan Field 5: Year-end balance of various loans of financial institutions
National Bureau of Statistics
The data set contains three tables: the livestock number and meat production in each county, the production of milk and fur, and the year-end livestock number. These tables contain time series data on the livestock number and livestock products in Tibet from 1951 to 2016. The data were derived from the Tibet Society and Economics Statistical Yearbook and Tibet Statistical Yearbook. The accuracy of the data is consistent with that of the statistical yearbooks. Table 1: The table of livestock number and meat production contains 8 fields. Field 1: Year of the data Field 2: Districts and counties included in the data Field 3: The year-end number of all year-end livestock, unit: 10,000 Field 4: The number of large livestock, unit: 10,000 Field 5: The number of sheep, unit: 10,000 Field 6: Total meat production, unit: ton Field 7: Beef production, unit: ton Field 8: Sheep meat production, unit: ton Table 2: The table of milk and fur production contains 8 fields. Field 1: Year of the data Field 2: Districts and counties included in the data Field 3: Milk production, unit: ton Field 4: Cow milk production, unit: ton Field 5: Goat wool production, unit: ton Field 6: Sheep wool production, unit: ton Field 7: The number of sheep skins, unit: piece Field 8: The number of cattle hides, unit: piece Table 3: The table of year-end livestock number contains 7 fields. Field 1: Year of the data Field 2: The total number of all livestock, unit: 10,000 Field 3: The number of large livestock unit: 10,000 Field 4: The number of cattle, unit: 10,000 Field 5: The number of goats, unit: 10,000 Field 6: The number of sheep, unit: 10,000 Field 7: The number of pigs, unit: 10,000
National Bureau of Statistics
The data set describes the number of students enrolled in various types of schools over time. The data were derived from the Tibet Society and Economics Statistical Yearbook and Tibet Statistical Yearbook. The accuracy of the data is consistent with that of the statistical yearbooks. Table 1: The table of student number in various types of schools contains 7 fields. Field 1: Year of the data Field 2: Number of students in colleges and universities Field 3: Number of students in secondary schools Field 4: Number of students in specialized secondary schools Field 5: Number of middle school students Field 6: Number of primary school students Field 7: Number of kindergarten students Table 2: The table of teacher resource statistics in every county contains 7 fields. Field 1: Counties Field 2: Year Field 4: Number of students supervised by each teacher Field 5: Total number of school students Field 6: Number of school students in general middle schools Field 7: Number of school students in primary schools
National Bureau of Statistics
The data set contains two tables detailing the total cultivated land area and the cultivated land area in every county at the end of each year. The data are time series data of cultivated land, dry land, paddy field and effective irrigated area in Tibet from 1959 to 2016 and were derived from the Tibet Society and Economics Statistical Yearbook and Tibet Statistical Yearbook. The accuracy of the data is consistent with that of the statistical yearbooks. Table 1: The table of cultivated land area contains 7 fields. Field 1: Year of the data Field 2: Year-end actual cultivated land area, unit: 1000 hectares Field 3: Dry land area, unit: 1000 hectares Field 4: Paddy field area, unit: 1000 hectares Field 5: Reduced area in the current year, unit: 1000 hectares Field 6: Land occupation of national infrastructure, unit: 1000 hectares Field 7: Increased area in the current year, unit: 1000 hectares Table 2: The table of year-end cultivated land area in each county contains 5 fields. Field 1: Year of the data Field 2: The districts and counties included in the data Field 3: Actual cultivated land area, unit: hectare Field 4: Dry land area, unit: hectare Field 5: Effective irrigated area, unit: hectare
National Bureau of Statistics
The data set contains time series data of various industrial products in the Tibetan Autonomous Region from 1956 to 2016, such as chrome ore, power generation, hydroelectric power, cement, etc. The data were derived from the Tibet Society and Economics Statistical Yearbook and Tibet Statistical Yearbook. The accuracy of the data is consistent with that of the statistical yearbook. The table contains 13 fields. Field 1: Year of the data Field 2: Chromium ore production, unit: ton Field 3: Power generation, unit: 10,000 kilowatt per hour Field 4: Hydroelectric power, unit: 10,000 kilowatt per hour Field 5: Cement, unit: ton Field 6: Beer production, unit: ton Field 7: Mineral water, unit: ton Field 8: Chinese traditional patent medicines, unit: ton Field 9: Flour, unit: ton Field 10: Edible vegetable oil, unit: ton Field 11: Woollen yarn, unit: ton Field 12: Carpet, unit: square metre Field 13: Clothing, unit: pair/piece
National Bureau of Statistics
The data set contains time series data on imports and exports in the Tibetan Autonomous Region from 1953 to 2016, which are presented in both CNY and USD. The data were derived from the Tibet Society and Economics Statistical Yearbook and Tibet Statistical Yearbook. The accuracy of the data is consistent with that of the statistical yearbook. The table contains 7 fields. Field 1: Year Field 2: Gross import and export volume (CNY 10,000.00) Field 3: Gross export volume (CNY 10,000.00) Field 4: Gross import volume (CNY 10,000.00) Field 5: Gross import and export volume (USD 10,000.00) Field 6: Gross export volume (USD 10,000.00) Field 7: Gross import volume (USD 10,000.00)
National Bureau of Statistics
