The widely definition of seasonally frozen ground include seasonally frozen layer (seasonally frozen ground regions) and seasonally thaw layer (active layer in permafrost regions). So the area extent of seasonally frozen ground occupied more than 80% land surface over Northern Hemisphere. Soil freeze/thaw cycle is one special character of seasonally frozen ground, which covers area extent, depth, time duration, variation of soil freeze/thaw. These changes in seasonally frozen ground have substantial impacts on energy, water and carbon exchange between the atmosphere and the land surface, surface and sub-surface hydrologic processes, vegetation growth, the ecosystem, carbon dioxide cycle, agriculture, and engineering constructuion, as a whole.Based on the observations from sites, CRU air temperature, we used the Stefan solution to calculate the spatial distribution of active layer thickness and soil freeze depth during 1971-2000. These results are helpful to further study the physical mechanism between seasonally frozen ground and climate change, eco-hydrology process.

This data includes 1:4 million precision fault data within the scope of Qinghai Tibet Plateau in China. The attribute table fields include fault name, fault length, strike, dip, fault property, paleoearthquake, etc. The data comes from the Seismological Bureau. Later, by consulting a large number of fault related literature, the attribute of fault activity age is added on the basis of the original data. The accuracy of original data is reliable, and a special person is responsible for quality review; After review by many people, the data integrity, position accuracy and attribute accuracy meet the requirements of relevant technical regulations and standards, and the quality is excellent and reliable. The fault data can provide basic data support for some fault related research work in the Qinghai Tibet Plateau.

Basic Geographic Data Set of Resources and Environment in Central and Western Asia Region, includes six parts: administrative divisions map, topographic and geomorphological map, river system maps, precipitation map, temperature map and potential evapotranspiration map. The precipitation and temperature datasets are interpolated based on the ground observations, while the potential evapotranspiration dataset is calculated based on the Penman-Monteith equation. The precipitation, temperature and potential evapotranspiration datasets are resampled from the original 0.5° CRU dataset by using the linear interpolation method in ArcGIS software. This dataset is made based a large number of gauge observations with good quality control and homogeneity check. The results of the related studies (Deng and Chen, 2017; Li et al., 2017; Li et al., 2016) suggested that this dataset is applicable and satisfactory for the climatological studies. The data produced by the key laboratory of remote sensing and GIS, Xinjiang institute of ecology and geography, Chinese Academy of Sciences. Data production Supported by the Strategic Priority Research Program of Chinese Academy of Sciences, Grant No. XDA20030101.

Fraction of Absorbed Photosynthetically Active Radiation (FPAR) is a key physiological variable in the study of carbon cycling and is one of the basic variables to describe vegetation ecosystems. The classification results of surface vegetation types in Qinghai-Tibet Plateau region are obtained based on the Landsat reflectance data(30m spatial resolution). According to NDVI of different vegetation types, the remote sensing inversion model is constructed to produce the growing season FPAR products for each vegetation type. This product can be used as one of the parameters to calculate vegetation carbon sequestration and evaluate vegetation ecosystem status.

The dataset is the Landsat surface reflectance products from 1980s to 2019 over the Tibetan Plateau, it is the key input parameter of many surface geophysical parameters (such as leaf area index, chlorophyll and biomass). The dataset is retrieved based on Landsat level 4 products from China satellite remote sensing ground station, and it is retrived by using the atmospheric correction based on 6S model and BRDF correction model based on C-factor .The RMSE of geometric correction is less than 12m and the RMSD of surface reflectance is less than 5%. And the corresponding production of quality identification documents (QA) is also generated to identify the cloud, ice and snow.The Landsat surface reflectance play an important role in forest, water resources, climate change.

The data set includes county-level demographic data of 252 areas in Qinghai-Tibet Plateau in 1982, 1990, 2000, 2010 and 2018, and GDP data in 1988, 1995, 2000, 2010 and 2015. The demographic data includes registered population, resident population, urban population, rural population, male population, female population and non-agricultural population. GDP data includes total GDP output value and GDP output value of primary, secondary and tertiary industries. The data are helpful to study the impact of human activities on the ecological climate of Qinghai-Tibet Plateau, and to explore the urbanization development, urban and rural population mobility, resident population change, local birth rate and agricultural population change in Qinghai-Tibet Plateau. The data were obtained by contacting the local statistics bureau, relevant statistical yearbooks and annual statistical bulletins of various places during the second scientific investigation of Qinghai-Tibet Plateau.

The data set records the total socio-demographic data of five central Asian countries from 1991 to 2017.Population indicators including annual population, estimated life expectancy, total fertility rate (1000 people), and total mortality (1000 people), infant mortality, maternal mortality, the total marriage rates, the overall divorce rate, migration of all flow balance, the number of medical institutions, hospital beds (m), the number of preschool institutions (a), kindergarten school student number (m) number, number of middle school, high school students (m), the number of the university, the number of students, institutions of higher learning, the number of students of institutions of higher learning.The data are from the statistical yearbooks of five central Asian countries.

Kilometer-level spatially complete (seamless) land surface temperature products have a wide range of applications needs in climate change and other fields. Satellite retrieved LST has high reliability. Integrating the LST retrieved from thermal infrared and microwave remote sensing observation is an effective way to obtain the SLT with certain accuracy and spatial integrity. Based on this guiding ideology, the author developed a framework for retrieving 1km and seamless LST over China landmass, and generated the LST data set accordingly (2002-2020) Firstly, a look-up table based empirical retrieval algorithm is developed for retrieving microwave LST from AMSR-E/AMSR2 observations. Then, AMSR-E/AMSR2 LST is downscaled by using geographic weighted regression to obtain 1km LST. Finally, the multi-scale Kalman filter is used to fuse AMSR-E/AMSR2 LST and MODIS LST to generate a 1km seamless LST data set. The ground valuation results show that the root mean square error (RMSE) of the 1km seamless LST is about 3K. In addition, the spatial distribution of the 1km seamless LST is consistent with MODIS LST and CLDAS LST.

The data set records the dynamic statistical data of groundwater level in the monitoring area of Golmud City, Qinghai Province from 2012 to 2018, and the statistics are classified according to the year and quantity. The data were collected from the official website of the Department of natural resources of Qinghai Province. The data set contains seven data tables, which are the dynamic statistics of groundwater level in Golmud monitoring area in 2012, 2013, 2014, 2015, 2016, 2017 and 2018, with the same structure. For example, the data table in 2012 has five fields: Field 1: year Field 2: Potassium view5 Field 3: View 4 Field 4: View 39 Field 5: Potassium view 1

The data coverage area is Sichuan Tibet traffic corridor, which is vector line data. The data defines its active period and names it. The strike, nature, active period and exposure of the fault are described. However, the content is missing, and the secondary fault zone is not named. There are 590 linear elements within the Sichuan Tibet traffic corridor in this data set, but some linear elements are multiple elements of the same fault zone. The active fault zone is often the combination zone of different plates and different blocks. It is a relatively weak zone of the crust, which is easy to induce extremely serious earthquake disasters. It is also a concentrated development zone of geological disasters such as collapse, landslide and debris flow. The judgment of the location and nature of fault zone is of great significance to the risk susceptibility evaluation of geological disasters, and it is the key factor to study geological disasters.

Aiming at the 179000 km2 area of the pan three rivers parallel flow area of the Qinghai Tibet Plateau, InSAR deformation observation is carried out through three kinds of SAR data: sentinel-1 lifting orbit and palsar-1 lifting orbit. According to the obtained InSAR deformation image, it is comprehensively interpreted in combination with geomorphic and optical image features. A total of 949 active landslides below 4000m above sea level were identified. It should be noted that due to the difference of observation angle, sensitivity and observation phase of different SAR data, there are some differences in the interpretation of the same landslide with different data. The scope and boundary of the landslide need to be corrected with the help of ground and optical images. The concept of landslide InSAR recognition scale is different from the traditional spatial resolution and mainly depends on the deformation intensity. Therefore, some landslides with small scale but prominent deformation characteristics and strong integrity compared with the background can also be interpreted (with SAR intensity map, topographic shadow map and optical remote sensing image as ground object reference). The minimum interpretation area can reach several pixels. For example, a highway slope landslide with only 4 pixels is interpreted with reference to the highway along the Nujiang River.

The Qinghai Tibet Plateau belongs to the plateau mountain climate. The temperature and its seasonal variation have been one of the hot spots in the global climate change research. The data includes the temperature data of Qinghai Tibet Plateau, with spatial resolution of 1km * 1km, temporal resolution of month and year, and time coverage of 2000, 2005, 2010 and 2015. The data are obtained by Kring interpolation on the data of national weather station in Qinghai Tibet Plateau. The data can be used to analyze the temporal and spatial distribution of air temperature in the Qinghai Tibet Plateau. In addition, the data can also be used to analyze the law of temperature change with time in the Qinghai Tibet Plateau, which is of great significance to the study of the ecological environment of the Qinghai Tibet Plateau.