The data set product contains the aboveground biomass and vegetation coverage data products of the Qinghai-Tibet Plateau every five years from 1990 to 2020 (1990, 1995, 2000, 2005, 2010, 2015 and 2020).The aboveground biomass of the Qinghai-Tibet Plateau is the remote sensing inversion product of above-ground biomass inversion models based on different land cover types including grassland, forest, etc. Vegetation coverage data of the Qinghai-Tibet Plateau is inversed using remote sensing by the dimidiate pixel model. Among them, the aboveground biomass and vegetation coverage data from 2000 to 2020 were estimated based on MODIS data, the spatial resolution was 250 m; the aboveground biomass and vegetation coverage data of 1990 and 1995 were estimated based on NOAA AVHRR data, the spatial resolution after resampling process is 250 m. This dataset can provide basic data for revealing the temporal and spatial pattern of land cover areas and quality on the Qinghai-Tibet Plateau and supporting the assessment of ecosystems, ecological assets and ecological security.
To explore inorganic hydrochemical characteristics of the upper Yarlung Zangbo River, water samples were collected from the main stream and different tributaries in this region in August 2020. The water was collected with 100mL polyethylene (PE) plastic bottle, and the basic physical and chemical parameters such as pH value (±0.2) and dissolved oxygen (±1%) of the sampling site were measured by multi -parameter water quality monitor (YSI-EX02,USA).,and HCO3- concentration was titrated with 0.025mol/L HCl.The concentrations of Na+, K+, Ca2+, Mg2+, SO42-, NO3- and Cl- ions were analyzed and determined by ion chromatograph (Shenhan CIC-D160, China) in the laboratory. Using Gibbs model, correlation analysis and principal component analysis method, analyzed the one main ion concentration changes, chemical composition characteristics, analytical, and the ion source was designed to reveal inorganic water chemical characteristics of The Tibet plateau glacier melt water runoff, and for plateau typical river water and changing trend forecast provides the basis.
The population, grain, grain sown area and year-end data sets are extracted from the provincial and prefecture level statistical yearbooks of Qinghai, Tibet, Xinjiang, Gansu, Sichuan and Yunnan for many consecutive years. The missing data are interpolated as follows: 1. To ensure the accuracy of county data, Some counties and cities have been merged in this data (there may be errors in dividing and imputing the data for 20 years according to the proportion, but there will certainly be no problem in the merger, and the county area is small, so it is merged). 2. Xiahe County and cooperative city are merged into Xiahe County (cooperative city was separated from Xiahe County in 1998). 3. Gucheng district and Yulong County are merged into Gucheng district (Lijiang County was divided into Gucheng district and Yulong County in 2003). 4. The inner city district, East City District, West City District The four districts in Chengbei district have been merged into the district directly under the central government of Xining City (because the population of the four districts is given separately or the sum is given, and the total area of the four districts is only 487 square kilometers, they are merged). 5. For some missing data, curve fitting has been carried out in combination with similar years, and R2 is between 0.85-0.99. 6. In order to ensure the accuracy of the data, change maps have been prepared County by county
This dataset is a raster dataset of annual rainfall erosivity on the Qinghai-Tibet Plateau from 1960 to 2019. The rainfall erosivity was calculated using the daily rainfall data of 129 stations in the Qinghai-Tibet Plateau and its surrounding 150km range, of which 74 stations were located inside the Qinghai-Tibet Plateau and 55 stations were located outside. The calculation method is consistent with the algorithm of the first national Water Resources Inventory, using WGS_ 1984 coordinate system and Albers projection (central meridian 105°E, standard parallels 25°N and 47°N), and then Kriging interpolation is carried out year by year to generate grid map with spatial resolution of 250m. Rainfall erosivity is the main dynamic factor of soil erosion, and it is also the basic factor calculated by models such as CSLE and RUSLE. The integrated daily rainfall data of long-time series has high data accuracy, which improves the accuracy of rainfall erosivity estimation, and also helpful to further accurately estimate the amount of soil erosion on the Qinghai Tibet Plateau.
Vegetation primary productivity (Net Primary Production, NPP) dataset, source data from MODIS product (MOD17A3H), after data format conversion, projection, resampling and other preprocessing. The existing format is TIFF format, the projection is Krasovsky_1940_Albers projection, the unit is kg C/m2/year, and the spatial range is the entire Qinghai-Tibet Plateau. The spatial resolution of the data is 500 meters, the temporal resolution is every 5 years, and the time range is from 2001 to 2020. The NPP of the Qinghai-Tibet Plateau showed a trend of increasing gradually from northwest to southeast.
Land cover refers to the mulch formed by the current natural and human influences on the earth's surface. It is the natural state of the earth's surface, such as forests, grasslands, farmland, soil, glaciers, lakes, swamps and wetlands, and roads. The Land Cover (LC) dataset is original from MODIS products and preprocessed by format conversion, projection and resampling. The existing format is TIFF and projection is Krasovsky_1940_Albers. The data set has a spatial resolution of 1000 meters and provides one image per year during the period from 2002 to 2020. Land cover products were classified into 17 categories defined by the International Geosphere Biosphere Programme (IGBP), including 11 categories of natural vegetation, 3 categories of land use and Mosaic, and 3 categories of non-planting land.
The Normalized Difference Vegetation Index (LST) dataset is original from MODIS products and preprocessed by format conversion, projection and resampling. The existing format is TIFF and projection is Krasovsky_1940_Albers. The data set has a spatial resolution of 1000 meters and provides one image per year during the period from 2001 to 2020. NDVI products are calculated by reflectance of red and near-infrared bands, which can be used to detect vegetation growth state and vegetation coverage. NDVI is ranged from -1 to 1, and the negative value means the land is covered by snow, water, etc. By contrast, positive value means vegetation coverage, and the coverage increases with the increase of NDVI.