The data sources of this dataset mainly include domestic satellite images such as HJ-1A/B, GF-1/2, ZY-3, and Landsat TM/ETM+/OLI series satellite image data. Using the domestic satellite images supplemented by Google Earth images to generate the component training sample and validation sample data of different geographical divisions. Using Google Earth Engine (GEE) to test and correct the model algorithm parameters. The normalized settlement density index (NSDI) is obtained based on random forest algorithm, Landsat TM/ETM+/OLI series satellite images and auxiliary data. The vector boundary of urban built-up area is obtained by density segmentation method after manual interactive interpretation and correction. The NSDI, vegetation coverage index and vector boundary of the Tibetan Plateau are used to produce the original data of urban impervious surface and urban green space fractions in the Tibetan Plateau. After correction and accuracy evaluation, the datasets of urban impervious surface area and green space fractions in the Tibetan Plateau from 2000 to 2020 are generated. The resolution of the data product is 30 m, and the coordinate system and storage format of the data files are unified. The geographic coordinate system is WGS84, the projected coordinate system is Albers, and the data storage format is GeoTIFF, the data unit is percentage (the value range is 0~10000), and the scale factor is 0.01. In order to quantify the change of urban land cover more accurately, samples from several typical cities are selected to verify the dataset. The specific verification methods and accuracy are shown in the published results. The data can be used to analyze and reveal the impact of land cover change and future scenario simulation on the Tibetan Plateau, to provide a scientific basis for building environmentally livable cities and improving the quality of human settlements on the Tibetan Plateau.
KUANG Wenhui, GUO Changqing, DOU Yinyin
The data set records the statistical data of grassland construction in Qinghai Province in the main years, covering the period from 2011 to 2017. The data are divided by fenced grassland area, new enclosure area in the current year, reserved area of artificial grass planting, area of new species in the current year, rodent damage area in the year, rodent damage control area in the year, etc. The data set contains seven data tables, which are: Grassland Construction in major years (2011), grassland construction in major years (2012), grassland construction in major years (2013), grassland construction in major years (2014), grassland construction in major years (2015), grassland construction in major years (2016) and grassland construction in major years (2017). The data table structure is similar. For example, the data sheet of grassland construction in major years (2011) has 10 fields: Field 1: indicator Field 2: 1995 Field 3: year 2000 Field 4: year 2005 Field 5: year 2006 Field 6: year 2007 Field 7: year 2008 Field 8: year 2009 Field 9: year 2010 Field 10: year 2011
AGRICULTURAL AND RURAL Department of Qinghai Province
Sediment ancient DNA is biological ancient DNA scattered in Paleoenvironmental samples, which is different from ancient DNA directly extracted from ancient animal bones and plant remains. Paleoenvironmental DNA is mainly mixed with multi species ancient DNA extracted from environmental samples such as glaciers, frozen soil, lake sediments, peat sediments, site cultural layer, dental calculus and fecal fossils. These DNA enter the environment with biological residues (including remains, hair, feces and urine), degrade rapidly and denature slowly in the environment, and finally adsorb on minerals and other particles or integrate into their own genome by microorganisms for long-term preservation, thus forming paleoenvironmental DNA. Sediment DNA is a new ancient DNA analysis technology. The sediments of archaeological sites can track the DNA preservation status of relevant sites and possible humans, make up for the shortcomings that human fossils are generally available but not available, greatly expand the research object and open a new window to study the population evolution of Paleolithic archaeological sites. The ancient DNA of stratum sediments from baishiya karst cave site where Xiahe human mandible was found was systematically sampled and analyzed.
ZHANG Dongju, FU Qiaomei
The basic principle of ancient recipe analysis based on carbon and nitrogen stable isotope analysis method is you are what you eat, that is, the chemical composition of animal tissues and organs is closely related to their diet. Through the detection of isotope ratio of relevant elements, the food structure of ancient people and animals can be directly revealed Then it discusses the research means of people's livelihood and livestock domestication. The collagen of human and animal bones from shilinggang site in Nujiang, Yunnan Province in the southwest of Qinghai Tibet Plateau was analyzed by carbon and nitrogen stable isotopes.
DONG Guanghui, REN Lele
The alpine and anoxic environment of the Qinghai Tibet Plateau is a major challenge for human survival and life. When human beings boarded the Qinghai Tibet Plateau and adapted to the extreme environment of the plateau has always been a hot issue in the academic circles. At present, in the study of prehistoric culture of the Qinghai Tibet Plateau, except the northeast, most areas of the Qinghai Tibet Plateau have not established archaeological cultural sequences. Yajiang river basin is one of the areas with dense distribution of human activity relics, but there are few archaeological excavations and studies, and the activity history of the ancients in this area is not clear. Based on the systematic dating of cultural archaeological sites in Linzhi Area, Southeast Tibet, 33 carbon fourteenth age data were obtained.
YANG Xiaoyan, WANG Yanren
The data set of land desertification distribution in Sanjiangyuan area is derived from the desertification pattern and change data of Qinghai Tibet Plateau. This data is obtained based on the integration of remote sensing images, auxiliary data and other multi-source data. The main data used and referred to include: 1) remote sensing image data: Landsat was selected to extract the images from June to September as the main data source for land desertification monitoring on the Qinghai Tibet Plateau, and five images were selected to monitor land desertification in 1980, 1990, 2000, 2010 and 2015. 2) auxiliary data: terrain data, soil type data, vegetation type data Land use data, Google Earth image and other auxiliary data are important data in the interpretation of desertification land; 3) The indicators of desertification are wind erosion rate, percentage of quicksand area and vegetation coverage; 4) The area of the source area of the three rivers is 382312 km2. The data set is cut out from the land desertification distribution data of the Qinghai Tibet Plateau, so as to carry out the research and analysis of the source area of the three rivers separately; 5) This data format is ShapeFile format. It is recommended to use ArcMap to open data.
NAN Weige
Land cover data of typical mineral development project areas include land cover data set of Gannan Tibetan Autonomous Prefecture (2000), land cover data set of Gannan Tibetan Autonomous Prefecture (2010) and land cover data set of Gannan Tibetan Autonomous Prefecture (2020). The data format is shape file with a spatial resolution of 30m, including ten categories: cultivated land, forest land, grassland, shrub land, wetland, water body, tundra, artificial surface, bare land, glacier and permanent snow, and the time resolution is years. The data comes from globeland30 (global geographic information public product), http://www.globallandcover.com/ ）, obtained by mosaic and reorganization. The data accuracy evaluation of source data is led by Tongji University and Aerospace Information Innovation Research Institute of Chinese Academy of Sciences, and the overall accuracy of data exceeds 83.50%. The data set can provide high-precision basic geographic information for relevant research, and can be applied to the comprehensive effect assessment of land cover in typical mineral development areas of super large gold belt in Qilian Mountain metallogenic belt in the northeast of Qinghai Tibet Plateau. It has important applications in the environmental effect assessment of mineral development, natural disaster risk assessment and disaster prevention and reduction.
CHENG Hao
As the roof of the world, the water tower of Asia and the third pole of the world, the Qinghai Tibet Plateau is an important ecological security barrier for China and even Asia. With the rapid development of social economy, human activities have increased significantly, and the impact on the ecological environment is growing. In this paper, eight factors including cultivated land, construction land, National Road, provincial road, railway, expressway, GDP and population density were selected as the threat factors, and the attributes of the threat factors were determined based on the expert scoring method to evaluate the habitat quality of the Qinghai Tibet Plateau, so as to obtain six data sets of the habitat quality of the agricultural and pastoral areas of the Qinghai Tibet Plateau in 1990, 1995, 2000, 2005, 2010 and 2015. The production of habitat quality data sets will help to explore the habitat quality of the Qinghai Tibet Plateau and provide effective support for the government to formulate sustainable development policies of the Qinghai Tibet Plateau.
LIU Shiliang, LIU Yixuan, SUN Yongxiu, LI Mingqi
To collect, integrate and integrate data and information on human activities, geographical conditions, environmental quality, natural disasters, medical and health care, and natural resources in the Qinghai Tibet Plateau（ Meteorological data (air temperature, air pressure, wind speed, precipitation, evaporation, sunshine hours, air humidity) from 1980 to 2019, air oxygen content, solar radiation, 4 million digital landform data set, soil erosion, concentration data set of soil persistent organic pollutants in Qinghai Tibet Plateau, natural disasters, medical resources, economic data in Tibet and Qinghai Water resources data of Qinghai Tibet Plateau (1990, 1995, 2000, 2005, 2010, etc.)
XIN Zhongbao
Topographic relief is a comprehensive representation of regional altitude and surface cutting degree. Based on the definition and calculation formula of topographic relief under the background of China's human settlements assessment, the digital elevation model (Aster GDEM 30 m) data is resampled into 1 km, The data set includes: (1) kilometer grid spatial data of Tibetan Plateau topographic relief（ 2) Terrain suitability evaluation data of Qinghai Tibet Plateau. The data can be used to analyze the spatial difference of topographic relief of the Qinghai Tibet Plateau, which is of great significance to the study of human settlements and Natural Suitability of the Qinghai Tibet Plateau.
XIAO Chiwei, LI Peng, FENG Zhiming
The data set records the basic information of cultivated land in the Tibet Autonomous Region and contains two data tables. Among them, the data table 1 has 7 fields, and the data table has 5 fields, respectively recording the cultivated land area, dry land area, paddy field area, effective irrigation area, and national infrastructure area of Tibet Autonomous Region and each district and county from 1959 to 2016. , The units are all hectares. The data comes from: "Tibet Statistical Yearbook" and "Tibetan Social and Economic Statistical Yearbook", with the same accuracy as the statistical yearbook extracted from the data. This data set has important value for understanding the situation of cultivated land in the Tibet Autonomous Region, evaluating the level of cultivated land utilization, and researching agricultural production and food security.
SU Zhengan
The data set records the land and natural resources of Qinghai Province, and the data is divided by land and natural resources. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set consists of five data tables Land and natural resources 1998.xls Land and natural resources 1999.xls Land and natural resources 2000.xls Natural resources 2001.xls Natural resources 2002. XLS, data table structure is the same. For example, the 1998 data table of land and natural resources has three fields: Field 1: Indicators Field 2: Unit Field 3: 1998
Qinghai Provincial Bureau of Statistics
The data set records the per capita income and expenditure of households in Qinghai Province from 2007 to 2013. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set contains six data tables with the same structure. For example, there are six fields in the data table from 1978 to 2004 Field 1: Project Field 2: 2007 Field 3: 2008 Field 4: 2009 Field 5: 2010 Field 6: 2011
Qinghai Provincial Bureau of Statistics
The data set is mainly included the population, arable land and animal husbandry data of Qinghai Province and Tibet Autonomous Region in the past 100 years. The data mainly comes from historical documents and modern statistics. The data quality is more reliable. It mainly provides arguments for the majority of researchers in the development of agriculture and animal husbandry on the Qinghai-Tibet Plateau.
LIU Fenggui
This dataset includes year-on-year data on urban construction land changes in five countries in Central Asia (Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan) from 1985 to 2018. The data has a spatial resolution of 30m and a temporal resolution of one year. It is derived from the Global Artificial Impervious Area (GAIA) change data extracted from Landsat images from 1985 to 2018 (Gong Peng et al.). The researchers evaluated 7 sets of data every 5 years from 1985 to 2015. The average overall accuracy is over 90%, and it is the only urban construction land dataset spanning 30 years.
XU Xiaofan, TAN Minghong
Based on the future population forecast data, urban expansion driving factor data (road network density, residential area, night light, GDP) and so on, the future urban expansion model is used to simulate and predict the urban expansion pattern and land use distribution of Xining City in 2050. The data set contains four data results corresponding to the urban pattern of Xining in 2050 under different scenarios. They are maintaining the status quo (BAU), urban compact development (infill), continuing the existing pattern and protecting cultivated land (protect), compact development and protecting cultivated land (infill).
SHEN Shi
Based on the future population forecast data, urban expansion driving factor data (road network density, residential area, night light, GDP) and so on, the future urban expansion model is used to simulate and predict the urban expansion pattern and land use distribution of Xining City in 2050. The data set contains four data results corresponding to the urban pattern of Xining in 2050 under different scenarios. They are maintaining the status quo (BAU), urban compact development (infill), continuing the existing pattern and protecting cultivated land (protect), compact development and protecting cultivated land (infill)_ There are four.
SHEN Shi
Based on the future population forecast data, urban expansion driving factor data (road network density, residential area, night light, GDP) and so on, the future urban expansion model is used to simulate and predict the urban expansion pattern and land use distribution of Xining City in 2050. The data set contains four data results corresponding to the urban pattern of Xining in 2050 under different scenarios. They are maintaining the status quo (BAU), urban compact development (infill), continuing the existing pattern and protecting cultivated land (protect), compact development and protecting cultivated land (infill).
SHEN Shi
Based on the future population forecast data, urban expansion driving factor data (road network density, residential area, night light, GDP) and so on, the future urban expansion model is used to simulate and predict the urban expansion pattern and land use distribution of Xining City in 2050. The data set contains four data results corresponding to the urban pattern of Xining in 2050 under different scenarios. They are maintaining the status quo (BAU), urban compact development (infill), continuing the existing pattern and protecting cultivated land (protect), compact development and protecting cultivated land (infill).
SHEN Shi
Based on the future population forecast data, urban expansion driving factor data (road network density, residential area, night light, GDP) and so on, the future urban expansion model is used to simulate and predict the urban expansion pattern and land use distribution of Xining City in 2050. The data set contains four data results corresponding to the urban pattern of Xining in 2050 under different scenarios. They are maintaining the status quo (BAU), urban compact development (infill), continuing the existing pattern and protecting cultivated land (protect), compact development, and protecting cultivated land (infill).
SHEN Shi
