The dataset of landuse types in Qilian Mountains National Park in 1985 is a vector dataset based on the remote sensing monitoring dataset of the current landuse situation in China by CAS, which is obtained through cropping and splicing operations. The data production production is vector data generated by manual visual interpretation using Landsat TM/ETM remote sensing images as the main data source. 3 datasets for 2000-2020 are raster datasets with 30m resolution based on GlobeLand30 global 30m ground cover data, obtained through mask extraction and other operations. The land use types of all datasets include 10 primary types of cropland, forest, shrubland, grassland, wetland, water, tundra, impervious surface, bareland, glacier, and permanent snow. The data products can detect most of the land cover changes caused by human activities, which is very important in practical applications. This data can be used to analyze the historical land use types in the Qilian Mountains region and to analyze the changes of land use types in the Qilian Mountains region in combination with the current landuse type data.
NIAN Yanyun
This data is the debris flow risk assessment data obtained from the analysis and Research on the debris flow disaster in the China Pakistan Economic Corridor, and the data source is the risk and vulnerability analysis results obtained from this study; The research method is based on the risk expression given by the United Nations Department of Humanitarian Affairs (1992): risk = hazard × Vulnerability, risk analysis of debris flow disaster in the study area.. The purpose of this data is to assess the risk of debris flow disaster in the China Pakistan Economic Corridor, understand the relationship between the intensity of major debris flow risk, and provide scientific guidance for the decision-making of local government departments in disaster prevention and mitigation and urban governance.
SU Fenghuan
This data is the debris flow risk assessment data obtained from the analysis and Research on the debris flow disaster in the China Pakistan Economic Corridor, and the data source is the risk and vulnerability analysis results obtained from this study; The research method is based on the risk expression given by the United Nations Department of Humanitarian Affairs (1992): risk = hazard × Vulnerability, risk analysis of debris flow disaster in the study area.. The purpose of this data is to assess the risk of debris flow disaster in the China Pakistan Economic Corridor, understand the relationship between the intensity of major debris flow risk, and provide scientific guidance for the decision-making of local government departments in disaster prevention and mitigation and urban governance.
SU Fenghuan
This data is the debris flow risk assessment data, which is obtained from the analysis and research of the debris flow disaster in the China Pakistan Economic Corridor. The sample data of debris flow is the detailed data of debris flow disaster through remote sensing interpretation and on-site verification. A risk assessment system is established to evaluate the debris flow risk in the study area by using the information method, and then the risk area is divided by using the natural breakpoint method. This data can be used to assess the risk of major debris flow disasters, understand the relationship between the risk degree of major debris flow, and provide scientific guidance for the decision-making of local government departments in disaster prevention and mitigation and urban governance.
SU Fenghuan
Net Primary Productivity (NPP) refers to the total amount of organic matter produced by photosynthesis in green plants per unit time and area. As the basis of water cycle, nutrient cycle and biodiversity change in terrestrial ecosystems, NPP is an important ecological indicator for estimating earth support capacity and evaluating sustainable development of terrestrial ecosystems. This data set includes the monthly synthesis of 30m*30m surface LAI products in Qilian mountain area in 2021. Max value composition (MVC) method was used to synthesize monthly NPP products on the surface using the reflectivity data of Landsat 8 and sentinel 2 channels from Red and NIR channels.
WU Junjun , LI Yi, ZHONG Bo
Leaf Area Index (LAI) is defined as half of the total Leaf Area within the unit projected surface Area, and is one of the core parameters used to describe vegetation. LAI controls many biological and physical processes of vegetation, such as photosynthesis, respiration, transpiration, carbon cycle and precipitation interception, and meanwhile provides quantitative information for the initial energy exchange on the surface of vegetation canopy. LAI is a very important parameter to study the structure and function of vegetation ecosystem. This data set includes the monthly synthesis of 30m LAI products in Qilian mountain area in 2021. Max value composition (MVC) method was used to synthesize monthly LAI products on the surface using the reflectivity data of Landsat 8 and sentinel 2 channels from Red and NIR channels.
WU Junjun , LI Yi, ZHONG Bo
Different forms of precipitation (snow, sleet, and rain) have divergent effects on the Earth’s surface water and energy fluxes. Therefore, discriminating between these forms is of significant importance, especially under a changing climate. We applied a state-of-the-art parameterization scheme with wet-bulb temperature, relative humidity, surface air pressure, and elevation as inputs, as well as observational gridded datasets with a maximum spatial resolution of 0.25◦, to generate a gridded dataset of different forms of daily precipitation (snow, sleet, and rain) and their temperature threshold across mainland China from 1961-2016. The annual snow, sleet, and rain amount were further calculated. The dataset may benefit various research communities, such as cryosphere science, hydrology, ecology, and climate change.
SU Bo , ZHAO Hongyu
Mountain glaciers are important freshwater resources in Western China and its surrounding areas. It is at the drainage basin scale that mountain glaciers provide meltwater that humans exploit and utilize. Therefore, the determination of glacierized river basins is the basis for the research on glacier meltwater provisioning functions and their services. Based on the Randolph glacier inventory 6.0, Chinese Glacier Inventories, China's river basin classifications (collected from the Data Centre for Resources and Environmental Sciences, Chinese Academy of Sciences), and global-scale HydroBASINS (www.hydrosheds.org), the following dataset was generated by the intersection between river basins and glacier inventory: (1) Chinese glacierized macroscale and microscale river basins; (2) International glacierized macroscale river basin fed by China’s glaciers; (3) Glacierized macroscale river basin data across High Mountain Asia. This data takes the common river basin boundaries in China and the globe into account, which is poised to provide basic data for the study of historical and future glacier water resources in China and its surrounding areas.
SU Bo
The Second Tibetan Plateau Scientific Expedition and Research Task V Theme III "Conservation and Sustainable Utilization of Plateau Microbial Diversity" (2019QZKK0503) carried out more than 30 field scientific expeditions in the first and second years. Footprints cover most of the Tibetan Plateau, including the investigation of glaciers (such as Qiangyong Glacier, Tanggula Glacier, Everest East Rongbu glacier, Jiemayangzong Glacier, Palung 4 Glacier, etc.), lakes, soils, fungi, lichens, animals in Southeast Tibet, Qiangtang Plateau, Cocosili and Himalayan region. The dataset contains 6,471 photos and videos, including habitat photos, working photos, and scientific images collected during the first and second years of fieldwork.
LIU Yongqin
This dataset contains the LAI measurements from the Daman superstation in the middle reaches of the Heihe integrated observatory network from July 22 to September 5 in 2021. The site (100.376° E, 38.853°N) was located in the maize surface, near Zhangye city in Gansu Province. The elevation is 1556 m. There are 3 observation samples, each of which is about 30m×30m in size, and the latitude and longitude are (100.374°E, 38.855°N), (100.371° E, 38.854°N), (100.369°E, 38.854°N). Four sub-canopy nodes and one above-canopy node are arranged in each sample. The data is obtained from LAINet measurements; the four-steps are performed to obtain LAI: the raw data is light quantum (level 0); the daily LAI can be obtained using the software LAInet (level 1); further the invalid and null values are screened and using the 5 days moving averaged method to obtain the processed LAI (level 2); for the multi LAINet nodes observation, the averaged LAI of the nodes area is the final LAI (level 3). The released data are the post processed LAI products and stored using *.xls format. For more information, please refer to Liu et al. (2018) (for sites information), Qu et al. (2014) for data processing) in the Citation section.
LIU Shaomin, CHE Tao, Qu Yonghua, XU Ziwei, TAN Junlei
The dataset contains the phenological camera observation data of the Sidaoqiao Superstation in the downstream of Heihe integrated observatory network from May 2 to December 26, 2021. The instrument was developed and data processed by Beijing Normal University. The phenomenon camera integrates data acquisition and data transmission functions. The camera captures data by look-downward with a resolution of 1280×720. For the calculation of the greenness index and phenology, the relative greenness index (GCC, Green Chromatic Coordinate, calculated by GCC=G/(R+G+B)) needs to be calculated according to the region of interest, then the invalid value filling and filtering smoothing are performed, and finally the key phenological parameters are determined according to the growth curve fitting, such as the growth season start date, Peak, growth season end, etc. For coverage, first, select images with less intense illumination, then divide the image into vegetation and soil, calculate the proportion of vegetation pixels in each image in the calculation area. After the time series data is extracted, the original coverage data is smoothed and filtered according to the time window specified by the user, and the filtered result is the final time series coverage. This data set includes relative greenness index (Gcc). Please refer to Liu et al. (2018) for sites information in the Citation section.
LIU Shaomin, Qu Yonghua, CHE Tao, XU Ziwei, REN Zhiguo
The dataset contains the phenological camera observation data of the Daman Superstation in the midstream of Heihe integrated observatory network from January 1 to December 31, 2021. The instrument was developed and data processed by Beijing Normal University. The phenomenon camera integrates data acquisition and data transmission functions. The camera captures data by look-downward with a resolution of 1280×720. For the calculation of the greenness index and phenology, the relative greenness index (GCC, Green Chromatic Coordinate, calculated by GCC=G/(R+G+B)) needs to be calculated according to the region of interest, then the invalid value filling and filtering smoothing are performed, and finally the key phenological parameters are determined according to the growth curve fitting, such as the growth season start date, Peak, growth season end, etc. For coverage, first, select images with less intense illumination, then divide the image into vegetation and soil, calculate the proportion of vegetation pixels in each image in the calculation area. After the time series data is extracted, the original coverage data is smoothed and filtered according to the time window specified by the user, and the filtered result is the final time series coverage. This data set includes relative greenness index (Gcc). Please refer to Liu et al. (2018) for sites information in the Citation section.
LIU Shaomin, Qu Yonghua, CHE Tao, XU Ziwei, TAN Junlei, REN Zhiguo
The dataset contains the phenological camera observation data of the Arou Superstation in the midstream of Heihe integrated observatory network from January 1 to December 31, 2021. The instrument was developed and data processed by Beijing Normal University. The phenomenon camera integrates data acquisition and data transmission functions. The camera captures data by look-downward with a resolution of 1280×720. For the calculation of the greenness index and phenology, the relative greenness index (GCC, Green Chromatic Coordinate, calculated by GCC=G/(R+G+B)) needs to be calculated according to the region of interest, then the invalid value filling and filtering smoothing are performed, and finally the key phenological parameters are determined according to the growth curve fitting, such as the growth season start date, Peak, growth season end, etc. For coverage, first, select images with less intense illumination, then divide the image into vegetation and soil, calculate the proportion of vegetation pixels in each image in the calculation area. After the time series data is extracted, the original coverage data is smoothed and filtered according to the time window specified by the user, and the filtered result is the final time series coverage. This data set includes relative greenness index (Gcc). Please refer to Liu et al. (2018) for sites information in the Citation section.
LIU Shaomin, Qu Yonghua, CHE Tao, XU Ziwei, ZHANG Yang
Forest is an important terrestrial ecosystem, accounting for about one-third of the total land area. It plays an important role in regulating climate, providing habitat for species, and maintaining global ecosystem balance. The dynamic change of the tree-canopy cover will affect the structure, composition, and function of the forest ecosystem. Landsat data were used to derive the 30-m tree-canopy cover dataset based on the machine learning method. The dataset of the rate of tree-canopy cover change in the Eastern Himalayas from 1990 to 2020 was generated using the annual tree-canopy cover data. The results show that the average tree-canopy cover in this region had increased from 40.67% (1990) to 43.43% (2020), an increase of 2.76%, indicating that the forests in the Eastern Himalayas improved in the past few decades.
WANG Chunling , WANG Jianbang , HE Zhuoyu , FENG Min
This data is the annual average runoff data from 1495 to 2018 of Khorog Hydrometric Station of gunte River, a tributary of Amu Darya River, reconstructed based on tree ring data. The data obtained from the tree ring hydrology research carried out by the Urumqi desert Meteorology Institute of the China Meteorological Administration and the Institute of water issues, hydropower and ecology of the National Academy of Sciences of Tajikistan can be used for scientific research such as water resources assessment and water conservancy projects in mountainous areas of Central Asia.
SHANG Huaming
Data content: groundwater temperature data of Nukus irrigation area from January 2021 to December 2021, unit: 0.1 ℃. Data source and processing method: this data is collected from the automatic groundwater monitoring station in Nukus irrigation area. Data quality description: this data is site data with a time resolution of 3 hours. Results and prospects of data application: combined with other meteorological and hydrological parameters, hydrogeological conditions, especially the recharge, runoff and discharge conditions of groundwater, can be further identified and studied to master the dynamic law of groundwater, so as to provide a scientific basis for the evaluation of groundwater resources, scientific management and the research and Prevention of environmental geological problems.
LIU Tie
Normalized Difference Vegetation Index (NDVI) is the sum of the reflectance values of the NIR band and the red band by the Difference ratio of the reflectance values of the NIR band and the red band. Vegetation index synthesis refers to the selection of the best representative of vegetation index within the appropriate synthesis cycle, and the synthesis of a vegetation index grid image with minimal influence on spatial resolution, atmospheric conditions, cloud conditions, observation geometry, and geometric accuracy and so on. This data set includes the monthly synthesis of 30m*30m surface vegetation index products in Qilian mountain area in 2021. Max value composition (MVC) method was used to synthesize monthly NDVI products on the surface using the reflectivity data of Landsat 8 and sentinel 2 channels from Red and NIR channels.
WU Junjun , LI Yi, ZHONG Bo
This data is obtained through observation at Namucuo multi cycle comprehensive observation and research station of Chinese Academy of Sciences (2019) and Tibetan southeast alpine environment comprehensive observation and research station of Chinese Academy of Sciences (2021), including the earth atmosphere exchange flux or vertical gradient of species such as O3, NOx, HONO, H2O and HCHO. The time range is from April 28, 2019 to July 10, 2019 (Namuco station) and from May 2, 2021 to May 13, 2021 (Southeast Tibet station). The data consists of five documents. Documents 1-4 are the flux data and H2O vertical gradient, HONO vertical gradient and NO2 vertical gradient observed at Namuco station in 2019. Document 5 is the flux data observed at Southeast Tibet station in 2021. During the monitoring period, data was missing due to instrument status problems. This data has broad application prospects and can serve graduate students and scientists with backgrounds such as atmospheric science, climatology, and ecology.
YE Chunxiang
Forest change (including forest loss and gain) is a complex ecological process influenced by natural and human activities, and has important impacts on global material cycles and energy flows. Based on long-term tree-canopy cover (TCC) data, the Bi-temporal class-probabilities model was used to detect forest changes, and a dataset of forest change of the Natural Forest Conversion Program area in northeast China from 1986 to 2018 was obtained (spatial resolution 30 meters with a temporal resolution of 1 year). The method of stratified random sampling was used to select 1000 points in the reserve and visual interpretation was carried out to evaluate the accuracy of forest change. The results show that the accuracy of forest loss (producer's accuracy = 85.21%; user's accuracy = 84.26%) and forest restoration (producer's accuracy = 87.74%; user's accuracy = 88.31%) are both high, which can effectively reflect the forest change status of the protected area.
WANG Jianbang , HE Zhuoyu , WANG Chunling , FENG Min, PANG Yong, YU Tao , LI Xin
The data set is a three-dimensional lithospheric stress field model in the Sichuan-Yunnan region, which is constrained by GPS velocity field and focal mechanism solution. A 3D finite element model of regional lithospheric deformation is constructed by using the lithospheric structure fracture information in Sichuan-Yunnan region. The velocity boundary constraints of the model are given by integrating the regional GPS velocity published in the existing researches and the latest observation. At the same time, the stress field of the model is constrained by the focal mechanism solution of regional small and medium earthquakes and mantle convection. A comprehensive simulation model of current crustal deformation and stress field in Sichuan-Yunnan region is constructed. The model can be used for further study on valuable scientific issues such as the mechanism of the large earthquakes preparation, tectonic evolution of the lithosphere in Sichuan-Yunnan region and the eastward extrusion of the Tibetan Plateau.
XIONG Xiong
The data set is the S-wave radial anisotropic model in Sichuan-Yunnan region obtained by applying ambient noise tomography. First, the seismic waveform data is applied from National Earthquake Data Center and IRIS, and collected from deployed seismic stations. Using the collected seismic waveform data, we intercept waveform per each day and remove the mean and trend and filter the waveform. We invert the S-wave radial anisotropic model in Sichuan-Yunnan region by applying the ambient noise tomography. The model can be used for further study on valuable scientific issues such as the mechanism of the large earthquakes preparation, tectonic evolution of the lithosphere in Sichuan-Yunnan region and the eastward extrusion of the Tibetan Plateau.
GAO Yuan
The data set is the three-dimensional S-wave velocity and azimuthal anisotropic model in Sanjiang region obtained by applying ambient noise tomography. First, the seismic waveform data is applied from National Earthquake Data Center and collected from deployed seismic stations. Using the collected seismic waveform data, we intercept waveform per each day and remove the mean and trend and filter the waveform. We invert the three-dimensional S-wave velocity and azimuthal anisotropic model in Sanjiang region by applying the ambient noise tomography. The model can be used for further study on valuable scientific issues such as the mechanism of the large earthquakes preparation, tectonic evolution of the lithosphere in Sichuan-Yunnan region and the eastward extrusion of the Tibetan Plateau.
GAO Yuan
The data set is the three-dimensional S-wave velocity and azimuthal anisotropic model in Sichuan-Yunnan region obtained by applying ambient noise tomography. First, the seismic waveform data is applied from National Earthquake Data Center and collected from deployed seismic stations. Using the collected seismic waveform data, we intercept waveform per each day and remove the mean and trend and filter the waveform. We invert the three-dimensional S-wave velocity and azimuthal anisotropic model in Sichuan-Yunnan region by applying the ambient noise tomography. The model can be used for further study on valuable scientific issues such as the mechanism of the large earthquakes preparation, tectonic evolution of the lithosphere in Sichuan-Yunnan region and the eastward extrusion of the Tibetan Plateau.
GAO Yuan
The data set is the uppermost mantle Pn anisotropic model in Sichuan-Yunnan region obtained by applying Pn-wave tomography. First, the seismic waveform data is applied from National Earthquake Data Center and collected from deployed seismic stations. Using the collected seismic waveform data, we intercept Pn waveform as seismic events and remove the mean and trend and filter the waveform. We invert the uppermost mantle Pn anisotropic model in Sichuan-Yunnan region by applying the Pn-wave tomography. The model can be used for further study on valuable scientific issues such as the mechanism of the large earthquakes preparation, tectonic evolution of the lithosphere in Sichuan-Yunnan region and the eastward extrusion of the Tibetan Plateau.
GAO Yuan
The data set is the lithospheric anisotropic model in Sichuan-Yunnan region obtained by applying XKS splitting method. First, the seismic waveform data is applied from National Earthquake Data Center and collected from deployed seismic stations. Using the collected seismic waveform data, we intercept XKS waveform as seismic events and remove the mean and trend and filter the waveform. We invert the lithospheric anisotropic model in Sichuan-Yunnan region by applying the XKS splitting method. The model can be used for further study on valuable scientific issues such as the mechanism of the large earthquakes preparation, tectonic evolution of the lithosphere in Sichuan-Yunnan region and the eastward extrusion of the Tibetan Plateau.
GAO Yuan
The data set is the crustal anisotropic model in Sichuan-Yunnan region obtained by applying Pms receiver functions method. First, the seismic waveform data is applied from National Earthquake Data Center and collected from deployed seismic stations. Using the collected seismic waveform data, we intercept waveform as seismic events and remove the mean and trend and filter the waveform. We invert the crustal anisotropic model in Sichuan-Yunnan region by applying the Pms receiver functions method. The model can be used for further study on valuable scientific issues such as the mechanism of the large earthquakes preparation, tectonic evolution of the lithosphere in Sichuan-Yunnan region and the eastward extrusion of the Tibetan Plateau.
GAO Yuan
The data set is the upper crustal anisotropic model in Sichuan-Yunnan region obtained by applying S-wave splitting method. First, the seismic waveform data is applied from National Earthquake Data Center and collected from deployed seismic stations. Using the collected seismic waveform data, we intercept waveform as seismic events and remove the mean and trend and filter the waveform. We invert the upper crustal anisotropic model in Sichuan-Yunnan region by applying the S-wave splitting method. The model can be used for further study on valuable scientific issues such as the mechanism of the large earthquakes preparation, tectonic evolution of the lithosphere in Sichuan-Yunnan region and the eastward extrusion of the Tibetan Plateau.
GAO Yuan
This data set is the information of a linear seismic array in Daliangshan area in Western Sichuan. The observation time is from december2018 to October 2020. The array is near the NE-SW trend. This array reaches the Sichuan basin to Yibin area to the east, and reaches the Yanyuan basin in Daliangshan area to the west. Each station uses Trillium posthole/horizon 120 broadband seismometer and Centaur data collector. A total of 40 seismic stations are deployed, with an average station spacing of only 10km. This array is used to collect and record high-quality seismic waveforms. Instrument maintenance and data acquisition are carried out every three months.
AI Yinshuang
The data set is the dispersion curves results of seismic stations in Sichuan-Yunnan region obtained by using ambient noise and teleseismic surface waveforms. First, the seismic waveform data is collected from seismic stations deployed in the Sichuan-Yunnan region. Using the collected seismic waveform data, we intercept waveform of each day from each station. After removing the mean and trend and filtering, we invert the dispersion curves of seismic stations in Sichuan-Yunnan region by using the ambient noise and teleseismic surface waveforms based on time-frequency analysis. The model can be used for further study on valuable scientific issues such as the mechanism of the large earthquakes preparation, tectonic evolution of the lithosphere in Sichuan-Yunnan region and the eastward extrusion of the Tibetan Plateau.
AI Yinshuang
The data set is the subsurface interface model in Sichuan-Yunnan region obtained by applying the ambient noise, teleseismic surface wave and body wave joint inversion. First, the seismic waveform data is applied from National Earthquake Data Center. Using the collected seismic waveform data, we remove the mean and trend and filter the waveform. We invert the subsurface interface model in Sichuan-Yunnan region by applying the ambient noise, teleseismic surface wave and body wave joint inversion. The model can be used for further study on valuable scientific issues such as the mechanism of the large earthquakes preparation, tectonic evolution of the lithosphere in Sichuan-Yunnan region and the eastward extrusion of the Tibetan Plateau.
AI Yinshuang
The data set is the three-dimensional S-wave velocity model in Sichuan-Yunnan region obtained by applying the ambient noise tomography. First, the seismic waveform data is applied from National Earthquake Data Center. Using the collected seismic waveform data, we intercept waveform of each day from each station. After removing the mean and trend and filtering, we invert the three-dimensional S-wave attenuation model in Sichuan-Yunnan region by applying the ambient noise tomography. The model can be used for further study on valuable scientific issues such as the mechanism of the large earthquakes preparation, tectonic evolution of the lithosphere in Sichuan-Yunnan region and the eastward extrusion of the Tibetan Plateau.
AI Yinshuang
The data set is the three-dimensional lithospheric velocity model in Sichuan-Yunnan region obtained by applying the full-waveform adjoint tomography. First, the seismic waveform data is applied from National Earthquake Data Center. Using the collected seismic waveform data, we intercept the seismic phase data with high signal-to-noise ratio according to the seismic events. After removing the mean and trend and filtering, the data are used to obtain the three-dimensional lithospheric velocity model in Sichuan-Yunnan region by applying the waveform adjoint tomography. The model can be used for further study on valuable scientific issues such as the mechanism of the preparation of large earthquakes and tectonic evolution of the lithosphere in Sichuan-Yunnan region and the eastward extrusion of the Tibetan Plateau.
YANG Dinghui
The data set is the three-dimensional crustal velocity model in Sichuan-Yunnan region obtained by applying the full-waveform adjoint tomography. First, the seismic waveform data is applied from National Earthquake Data Center. Using the collected seismic waveform data, we intercept the seismic phase data with high signal-to-noise ratio according to the seismic events, and extract the amplitude information after removing the mean and trend and filtering. Finally, the amplitude data are used to obtain the three-dimensional crustal velocity model in Sichuan-Yunnan region by applying the waveform adjoint tomography. The model can be used for further study on valuable scientific issues such as the mechanism of the preparation of large earthquakes and tectonic evolution of the lithosphere in Sichuan-Yunnan region and the eastward extrusion of the Tibetan Plateau.
YANG Dinghui
The data set is the three-dimensional upper mantle S-wave Q model in Sichuan-Yunnan region obtained by applying the full-waveform adjoint tomography. First, the seismic waveform data is applied from National Earthquake Data Center. Using the collected seismic waveform data, we intercept the S-wave seismic phase data with high signal-to-noise ratio according to the seismic events, and extract the S-wave amplitude information after removing the mean and trend and filtering. Finally, the S-wave amplitude data are used to obtain the three-dimensional S-wave attenuation model in Sichuan-Yunnan region by applying the waveform adjoint tomography. The model can be used for further study on valuable scientific issues such as the tectonic evolution of the lithosphere in Sichuan-Yunnan region and the eastward extrusion of the Tibetan Plateau.
YANG Dinghui
The data set is the three-dimensional lithospheric S-wave Q-value model data in the surrounding areas of Sichuan and Yunnan obtained by using the full waveform based adjoint attenuation imaging method. First, apply to the data backup center of the national seismological network for obtaining the seismic waveform data. Using the collected seismic waveform data, intercept the S-wave seismic phase data with high signal-to-noise ratio according to the seismic events, and extract the S-wave amplitude information after de averaging, de trending, waveform pinching and filtering. Finally, the S-wave amplitude data are inverted by using the waveform accompanying attenuation imaging method to obtain the three-dimensional S-wave attenuation model in Sichuan and Yunnan. The model data set can be used to further study important scientific issues such as the tectonic evolution of the lithosphere in Sichuan Yunnan region and the extension of the Qinghai Tibet Plateau.
YANG Dinghui
This data set includes major and trace elements and zircon U-Pb isotope data of Mesozoic sedimentary rocks in Baoshan block, Tengchong, Yunnan Province. The sampling time is 2018, and the area is near lameng Town, Baoshan District, Tengchong, Yunnan. The rock samples include 8 sedimentary rock samples. This data provides key information for understanding the evolution of the middle Tethys structure between Tengchong and Baoshan, and limits the closing time of the middle Tethys ocean to the late Jurassic, which is of great significance for discussing the evolution process of the Tethys structure. The whole rock major and trace elements of rock samples were tested by fluorescence spectrometer (XRF) and plasma mass spectrometer (ICP-MS), and zircon U-Pb was dated by laser ablation plasma mass spectrometer (LA-ICP-MS). The testing units include Institute of Geology and Geophysics, Chinese Academy of Sciences and Institute of Qinghai Tibet Plateau. The related articles of this data set have been published in the Journal of Asian Earth Sciences, and the data results are true and reliable.
ZHANG Jiuyuan
This data set consists of multi-scale and high-resolution seismic wave velocity, attenuation, anisotropy, interface and stress field model of the crust, lithosphere and upper mantle beneath the Sichuan-Yunnan area. The velocity and attenuation models are mainly obtained by applying waveform adjoint tomography, double difference tomography and ambient noise tomography methods. The anisotropic models are mainly obtained by applying shear wave splitting, receiver functions and ambient noise methods. The interface structure is mainly obtained by receiver functions. The stress field model is mainly restrained by GPS velocity field and focal mechanism. Some of the used seismic waveform are from published data, and some are obtained from deployed seismic stations. The model data set can be used for further study on valuable scientific issues such as the mechanism of the occurrence of large earthquakes and the tectonic evolution of the lithosphere beneath the Chuandian Block, and the dynamic mechanism of the eastward extrusion of the Tibetan Plateau.
PEI Shunping
The data from the Digital Mountain Map of China depicts the spatial pattern and complex morphological characteristics of mountains in China from a macro scale, including the mountains’ spatial distribution, classification, morphological elements and area ratio. It is a set of basic data that can be used for mountain zoning, mountain genetic classification and resource environment correlation analysis. Mountains carry great natural resource supply, provide ecological service and regulation functions, and play an important part in eco-civilization construction and socioeconomic development in China. Lately，Prof. Li Ainong of the Institute of Mountain Hazards and Environment, CAS, developed this data set based on the spatial definition of mountains, an a topography adaptive slide window method for the relief amplitude. The data include: (1) Spatial distribution of mountains in China; (2) Mountain classification; (3) Main mountain ranges (with range alignment, relief grade and ridge morphology); (4)Main mountain peaks; (5)Mountain proportion table of the provinces/autonomous regions/municipalities of China; (6) Contour zoning data; (7) General situation of mountain formation; (8)Mountain division and zoning data; (9) List of main mountain peaks. The spatial resolution of the original DEM source is about 90m. And the boundaries of mountains have been revised with multisource remote sensing data, which has good spatial consistency with the relief shading map. The cartographic generalization accuracy of mountain ranges and relevant features is 1:1 000 000. Mountain features in this data set have higher spatial resolution and pertinence, which are available for the zonality of mountain environment and mountain hazards, and the spatial analysis for ecological, production and living spaces in mountain areas, surpporting macro decision-making on mountain areas' development in China. p
NAN Xi , LI Ainong , DENG Wei
Data files are in 7Z compressed package format, which can be decompressed and opened by 7-zip software. There are three files in total, namely file 1, text version of grassland Degradation classification on The Qinghai-Tibet Plateau, file type is Word, and file 2, named As Map, with seven maps in total. The type of the image is PNG, and the name of the image is the trend rate of average NDVI change in the growing season of grass, grassland, meadow, grassland, alpine vegetation, desert and swamp on the Tibetan Plateau from 2010 to 2019. File 3. The folder named as data is filled with pictures. There are 7 kinds of pictures with the same names as above.
ZHOU Huakun
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.
ZHU Juntao
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.
ZHU Juntao
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.
ZHU Juntao
This dataset contains daily 0.05°×0.05° land surface soil moisture products in Qilian Mountain Area in 2021. The dataset was produced by utilizing the optimized wavelet-coupled-RF downscaling model (RF-OWCM) to downscale the SMAP L3 Radiometer Global Daily 36 km EASE-Grid Soil Moisture (SMAP L3, V8). The auxiliary datasets participating in the downscaling model include the MUltiscale Satellite remotE Sensing (MUSES) LAI/FVC product, the daily 1-km all-weather land surface temperature dataset for the Chinese landmass and its surrounding areas (TRIMS LST-TP;) and Lat/Lon information.
CHAI Linna, ZHU Zhongli, LIU Shaomin
This data set is a geochemical data set of granitoids in hengduan Mountain area. The total amount and components of rare earth elements in the kangdian paleocontinent, Ailaoshan-Jinshajiang, Lincang-Zuo Gong and Luxi-Tengchong granite belts in Hengduan Mountain area are studied. The ree abundance, variation and distribution patterns of various rocks are discussed, and the genetic types of granites are preliminarily discussed. Isotope geochemistry study, using strontium and neodymium isotope system tracing method, it is helpful to understand the genesis and material source of granitoids. For this reason, the isotopic compositions of strontium and neodymium in the granitoids of the four rock belts, including diorite, granodiorite, porphyritic biotite monzonite, potassic feldspar granite, alkali feldspar granite, hornblende biotite monzonite porphyry and alkali feldspar syenite, have been studied. It is helpful to study the geochemical related aspects of granites.
ZHANG Yuquan , XIE Yingwen
This data set contains the meteorological data of Pengbo irrigation area in Tibet from 2019 to 2022, including rainfall, temperature and relative humidity data, as well as the measured soil moisture and soil temperature data of highland barley, oat and grassland. The data interval is recorded in hours, and the measured time is from 2019 to 2022. The data of soil temperature and soil moisture are relatively detailed, which can reflect the change law of soil moisture and temperature at different time scales of time, day, month, season and year, and can also better meet the calibration and verification requirements of farmland water and heat transport model. The data set also includes crop evapotranspiration data and leakage data, which is helpful to analyze the water consumption of crops in the whole growth period and the water consumption and leakage at different growth stages in the alpine region of Tibet, and plays an important role in clarifying the water balance of different farmland systems. The meteorological, soil moisture, soil temperature, transpiration and leakage data of Pengbo irrigation area in Tibet provided by this data set are helpful to reveal the water transformation process at the farmland scale and irrigation area scale, and fully understand the water and heat transfer process and crop growth state of SPAC system in the high cold region of Tibet.
TANG Pengcheng
This dataset contains the glacier outlines in Qilian Mountain Area in 2015. The dataset was produced based on classical band ratio criterion and manual editing. Chinese GF series images collected in 2018 were used as basic data for glacier extraction. Sentinel-2 images, Google images and Map World images were employed as reference data for manual adjusting. The dataset was stored in SHP format and attached with the attributions of coordinates, glacier ID and glacier area. Consisting of 1 season, the dataset has a spatial resolution of 2 meters. The accuracy is about 1 pixel (±2 meter). The dataset directly reflects the glacier distribution within the Qilian Mountain in 2018, and can be used for quantitative estimation of glacier mass balance and the quantitative assessment of glacier change’s impact on basin runoff.
Li Jia Li Jia LI Jia LI Jia
This dataset contains the glacier outlines in Qilian Mountain Area in 2019. The dataset was produced based on classical band ratio criterion and manual editing. Chinese GF series images collected in 2019 were used as basic data for glacier extraction. Sentinel-2 images, Google images and Map World images were employed as reference data for manual adjusting. The dataset was stored in SHP format and attached with the attributions of coordinates, glacier ID and glacier area. Consisting of 1 season, the dataset has a spatial resolution of 2 meters. The accuracy is about 1 pixel (±2 meter). The dataset directly reflects the glacier distribution within the Qilian Mountain in 2019, and can be used for quantitative estimation of glacier mass balance and the quantitative assessment of glacier change’s impact on basin runoff.
Li Jia Li Jia LI Jia LI Jia
This dataset contains the glacier outlines in Qilian Mountain Area in 2020. The dataset was produced based on classical band ratio criterion and manual editing. Chinese GF series images collected in 2020 were used as basic data for glacier extraction. Sentinel-2 images, Google images and Map World images were employed as reference data for manual adjusting. The dataset was stored in SHP format and attached with the attributions of coordinates, glacier ID and glacier area. Consisting of 1 season, the dataset has a spatial resolution of 2 meters. The accuracy is about 1 pixel (±2 meter). The dataset directly reflects the glacier distribution within the Qilian Mountain in 2020, and can be used for quantitative estimation of glacier mass balance and the quantitative assessment of glacier change’s impact on basin runoff.
Li Jia Li Jia LI Jia LI Jia
Through the joint inversion of seismic waveforms and InSAR coseismic displacement data, our study revealed the spatiotemporal and spatial source rupture processprocesses of the two strong earthquakes that occurred in struck the eastern Tibetan Plateau atin May 2021. The results show that the Yangbi earthquake, which occurred in along the southeastern margin of the TibetTibetan Plateau, was a Mw6.1 event with characterized by unilateral right-dextral strike-slip rupture and 8s an 8 s duration. The In addition, the Maduo earthquake, which occurred in the interior of the Tibetan Plateau, was a Mw7.5 event with characterized by left-sinistral lateral-strike- slip extendedextending along both sides of the earthquake seismogenic fault and 36sa 36 s duration. The rupture properties of these two strong earthquakes reflect the deformation characteristics of different parts of the eastern Tibetan Plateau,. and also These events also caused the increase of the Coulomb stress of the surrounding active faults to increase, so we should pay attention to the risk potential of future earthquakes should be evaluated.
WANG Weimin
