Normalized Difference Vegetation Index (NDVI) has been widely used for monitoring vegetation. This dataset employed all available Landsat 5/7/8 data on the Qinghai-Tibetan Plateau (QTP) (> 100,000 scenes), and reconstructed high spatiotemporal NDVI time-series data (30-m and 8-d) during 2000-2020 on the TP (QTP-NDVI30) by using the MODIS-Landsat fusion algorithm (gap filling and Savitzky–Golay filtering；GF-SG). For the details of GF-SG, please refer to Chen et al. (2021). This dataset has been evaluated carefully. The quantitative assessments show that the reconstructed NDVI images have an average MAE value of 0.02, correlation coefficient of 0.96, and SSIM value of 0.94. We compared the reconstructed images in some typical areas with the PlanetScope 3-m images and found that the spatial details were well preserved by QTP-NDVI30. The geographic coordinate system of this dataset is GCS_WGS_84. The spatial range covers the vegetation area of the QTP, which is defined as the areas with average NDVI during July- September larger than 0.15.
CAO Ruyin , XU Zichao , CHEN Yang , SHEN Miaogen , CHEN Jin
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
This data set includes the PM2.5 mass concentration of atmospheric aerosol particles at Southeast Tibet station, Ali station, mostag station, Everest station and Namuco station (unit: mm) μ g/m3）。 Aerosol PM2.5 fine particles refer to particles with aerodynamic equivalent diameter less than or equal to 2.5 microns in the ambient air. It can be suspended in the air for a long time, which has an important impact on air quality and visibility. The higher its concentration in the air, the more serious the air pollution. The concentration characteristic data of PM2.5 is output at the frequency of obtaining a set of data every 5 minutes, which can realize the analysis of aerosol mass concentration at different time scales such as hour, day and night, season and interannual, which provides the analysis of changes and influencing factors of aerosol mass concentration at different locations in the Qinghai Tibet plateau at different time scales, as well as the evaluation of local air quality, It provides important data support. This data is an update of the published data set of PM2.5 concentration of aerosol particles at different stations on the Qinghai Tibet Plateau (2018 and 2019).
WU Guangjian
This data includes the image data of the second comprehensive field scientific investigation of the Qinghai Tibet Plateau. The image data includes the sample plot photos of the quadrats collected in the nature reserve during the scientific research, the images of forest ecosystem, grassland ecosystem and lake ecosystem in the nature reserve in Northwest Yunnan and Western Sichuan, the vegetation situation, wildlife habitat, and the data of animals, plants and fungi in the reserve. In addition, the image data also includes the sample collection process of the scientific research, the household survey of the scientific research team in the community survey and the image data of the interview with the local protection department. The data comes from UAV and camera shooting, which can provide evidence and reference for scientific research.
SU Xukun
1) Data content It includes the observation year, latitude and longitude, altitude, ecosystem type and soil layer (soc0-100 (kgcm-2); 0-100 represents soil layer), underground biomass content. 2) Data sources This part of the data is obtained from the literature, specific literature sources refer to the documentation. 3) Data quality description The data cover a wide range, including comprehensive indicators, showing the content of soil organic carbon under different soil layers, with high integrity and accuracy, which can meet the estimation of soil carbon storage of grassland in Qinghai Tibet Plateau. 4) Data application achievements and Prospects It provides basic data for predicting the carbon source sink effect of soil and realizing the sustainable development of ecosystem carbon in the future.
HU Zhongmin
1) Data content It includes the observation year, longitude and latitude, ecosystem type, annual rainfall, drought index, annual net primary productivity, aboveground biomass, underground biomass and other data. 2) Data sources One part is from literature (1980-1995), the other part is from field sampling (2005-2006). 3) Data quality description The data has a long observation year, a large time span, a wide coverage, and many indicators, which has high integrity and accuracy, and can meet the estimation of grassland carbon storage in the Qinghai Tibet Plateau. 4) Data application achievements and Prospects It provides basic data for predicting the carbon source sink effect and realizing the sustainable development of ecosystem carbon in the future.
HU Zhongmin
Carrying capacity refers to the carrying capacity of grassland calculated by actual carrying capacity and reasonable carrying capacity, that is, all overloading, balanced and non overloading. This data set includes two products: Grassland carrying capacity pressure index and grassland livestock balance index. Grassland carrying capacity pressure index = actual carrying capacity / reasonable carrying capacity, and grassland livestock balance index = (actual carrying capacity - reasonable carrying capacity) × 100% / reasonable carrying capacity, the actual carrying capacity data comes from the Qinghai Tibet Plateau actual carrying capacity data set (2000-2019), and the reasonable carrying capacity data comes from the Qinghai Tibet Plateau reasonable carrying capacity data set (2000-2019). This data set can analyze the temporal and spatial variation characteristics of livestock carrying status in the Qinghai Tibet Plateau, extract overgrazing areas, and evaluate the overload intensity of the Qinghai Tibet Plateau, which has important application value for ecological protection, monitoring and early warning of the Qinghai Tibet Plateau.
LIU Bintao
The actual carrying capacity refers to the number of livestock in a certain area of grassland in a certain period of time. The actual carrying capacity is obtained from the statistical yearbooks of the provinces (autonomous regions) and cities (prefectures) of the Qinghai Tibet Plateau and the statistical data provided by the animal husbandry management departments. In the statistical data, there are a variety of statistical dimensions, such as the number of stocks on hand, the number of stocks on hand, the ratio of stocks on hand, and the number of livestock at the end of the year, etc. Based on the multivariate linear regression between the actual livestock carrying capacity and population density, NPP and topographic relief in the statistical yearbook, the spatial model of actual livestock carrying capacity was established, and the grid data of actual livestock carrying capacity (sheep unit, mu / km2) was obtained. The time series was from 2000 to 2019, and the spatial resolution was 250 meters. Using the statistical data of Guoluo, Yushu, Changdu, Naqu, ABA, Ganzi and Gannan in the core pastoral areas of the Qinghai Tibet Plateau, the results show that the average absolute error of spatialization is 27.48 mu / km2, and the average relative error is 13.79%. This data set can analyze the temporal and spatial variation characteristics of the actual livestock carrying capacity of the Qinghai Tibet Plateau, evaluate the grassland carrying capacity characteristics of the Qinghai Tibet Plateau, and extract the overgrazing areas, which has important application value for ecological protection, monitoring and early warning of the Qinghai Tibet Plateau.
LIU Bintao
Reasonable carrying capacity, also known as theoretical carrying capacity, refers to the maximum number of domestic animals that can be carried by a certain grassland area in a certain period of time under the premise of moderate grazing (or mowing) and maintaining sustainable production of grassland to meet the needs of normal growth, reproduction and production of livestock. Based on the MODIS inversion data of forage yield (fresh weight, kg / hm2), the reasonable carrying capacity of grassland (sheep unit, mu / km2) was evaluated according to the code for calculation of grassland carrying capacity and grass livestock balance (DB 51 / t1480-2012) and calculation of reasonable carrying capacity of natural grassland (NY / T 635-2015), The time series is 2000-2019, and the spatial resolution is 250m. This data set can analyze the temporal and spatial variation characteristics of the theoretical carrying capacity under the condition of rational utilization of grassland in the Qinghai Tibet Plateau, evaluate the carrying capacity characteristics of grassland in the Qinghai Tibet Plateau, and extract the overgrazing areas, which has important application value for ecological protection, monitoring and early warning of the Qinghai Tibet Plateau.
LIU Bintao
Grassland yield is an important ecological parameter of grassland, which is an important basis for monitoring grassland productivity, Estimating Grassland reasonable carrying capacity and evaluating grassland carrying status. Based on the grassland data collected in July and August, MODIS NDVI, precipitation and terrain parameters, multivariate statistical equations were established to invert the total grass yield (kg / hm2) and edible grass yield (kg / hm2). The time series is 2000-2019, and the spatial resolution is 250 meters. Based on the data of 50 quadrats distributed in Sichuan, Tibet, Qinghai, Gansu and other regions, the results show that the average absolute error of total grass yield is 734.75kg/hm2, and the average relative error is 24.85%. The average absolute error of edible grass yield is 715.81kg/hm2, and the average relative error is 30.52%. Due to the complexity of grassland types, high spatial heterogeneity and scale mismatch between the measured grassland quadrats and MODIS image pixels, this accuracy can meet the requirements of remote sensing monitoring of grassland in large areas. This data set can analyze the spatiotemporal variation characteristics of grassland productivity in the Qinghai Tibet Plateau, evaluate the carrying capacity characteristics of grassland in the Qinghai Tibet Plateau, and extract the overgrazing areas, which has important application value for ecological protection, monitoring and early warning of the Qinghai Tibet Plateau.
LIU Bintao
This data set is hyperspectral observation data of typical vegetation along Sichuan Tibet Railway in September 2019, using the airborne spectrometer of Dajiang M600 resonon imaging system. Including the hyperspectral data observed in the grassland area of Lhasa in 2019, with its own latitude and longitude. The hyperspectral survey was mainly sunny. Before flight, whiteboard calibration was carried out; when data were collected, there was a target (that is, the standard reflective cloth suitable for the grass), which was used for spectral calibration; there were ground mark points (that is, letters with foam plates), and the longitude and latitude coordinates of each mark were recorded for geometric precise calibration. The DN value recorded by Hyperspectral camera of UAV can be converted into reflectivity by using Spectron Pro software. Hyperspectral data is used to extract spectral characteristics of different vegetation types, vegetation classification, inversion of vegetation coverage and so on.
ZHOU Guangsheng, JI Yuhe, LV Xiaomin, SONG Xingyang
Grassland actual net primary production (NPPa) was calculated by CASA model. CASA model was calculated with the combination of satellite-observed NDVI and climate (e.g. temperature, precipitation and radiation) as the driving factors, and other factors, such as land-use change and human harvest from plant material, were reflected by the changes of NDVI. CASA NPP was determined by two variables, absorbed photosynthetically active radiation’ (APAR) and the light-use efficiency (LUE). Grassland potential net primary production (NPPp) was calculated by TEM model. TEM is one of process-based ecosystem model, which was driven by spatially referenced information on vegetation type, climate, elevation, soils, and water availability to calculate the monthly carbon and nitrogen fluxes and pool sizes of terrestrial ecosystems. TEM can be only applied in mature and undisturbed ecosystem without take the effects of land use into consideration due to it was used to make equilibrium predications. Grassland potential aboveground biomass (AGBp) was estimated by random forest (RF) algorithm, using 345 AGB observation data in fenced grasslands and their corresponding climate data, soil data, and topographical data.
NIU Ben, ZHANG Xianzhou
This data is derived from the Supplementary Tables of the paper: Chen, F. H., Welker, F., Shen, C. C., Bailey, S. E., Bergmann, I., Davis, S., Xia, H., Wang, H., Fischer, R., Freidline, S. E., Yu, T. L., Skinner, M. M., Stelzer, S., Dong, G. R., Fu, Q. M., Dong, G. H., Wang, J., Zhang, D. J., & Hublin, J. J. (2019). A late Middle Pleistocene Denisovan mandible from the Tibetan Plateau. Nature, 569, 409-412. This research is another breakthrough made by academician Fahu Chen and his team over the years research of human activities and environmental adaptation on the Tibetan Plateau. The research team analyzed the newly discovered hominid mandible fossils in Xiahe County, Gansu Province, China, and identified it belongs to Denisovan of the Tibetan Plateau, which suggested to call Xiahe Denisovan. The team conducted a multidisciplinary analysis of the fossil, including chronology, physique morphology, molecular archaeology, living environment and human adaptation. It is the first Denisovan fossil found outside the Denisova Cave in the Altai Mountains and the earliest evidence of human activity on the Tibetan Plateau (160 kyr BP). This study provides key evidence for further study of Denisovans' physical characteristics and distribution in East Asia, it also provides evidence of a deep evolutionary history of these archaic hominins within the challenging environment of the Tibetan Plateau. This data contains 6 tables, table name and contents are as follows: t1: Distances in mm between meshes generated from CT versus photoscans (PS). t2: Measurements of the Xiahe mandible after reconstruction. t3: Comparative Dental metrics. t4: Comparative crown morphology. t5: Uniprot accession numbers for protein sequences of extant primates used in the phylogenetic analyses. t6: Specimen names and numbers.
CHEN Fahu
The data set includes the spatial distribution of grass yield in the Qinghai-Tibetan Plateau in 1980, 1990, 2000, 2010, and 2017. The gross primary productivity (GPP) of grassland in the Qinghai-Tibetan Plateau was simulated based on the ecological hydrological dynamic model VIP (vegetation interface process) with independent intellectual property of Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences. The net primary productivity (NPP) was estimated by empirical coefficient, and converted it into dry matter, and then the hay yield was estimated by root-shoot ratio. The spatial resolution is 1km. The data set will provide the basis for grassland resource management, development, utilization and the formulation of the strategy of "grass for livestock".
MO Xingguo
This dataset subsumes sustainable livestock carrying capacity in 2000, 2010, and 2018 and overgrazing rate in 1980, 1990, 2000, 2010, and 2017 at county level over Qinghai Tibet Plateau. Based on the NPP data simulated by VIP (vehicle interface process), an eco hydrological model with independent intellectual property of the institute of geographic sciences and nature resources research(IGSNRR), Chinese academy of Sciences(CAS), the grass yield data (1km resolution) is obtained. Grass yield is then calculated at county level, and corresponding sustainable livestock carring capacity is calculated according to the sustainable livestock capacity calculation standard of China(NY / T 635-2015). Overgrazing rate is calculated based on actual livestock carring capacity at county level.The dataset will provide reference for grassland restoration, management and utilization strategies.
MO Xingguo
According to the characteristics of the Qinghai Tibet Plateau and the principles of scientificity, systematization, integrity, operability, measurability, conciseness and independence, the human activity intensity evaluation index system suitable for the Qinghai Tibet Plateau has been constructed, which mainly includes the main human activities such as agricultural and animal husbandry activities, industrial and mining development, urbanization development, tourism activities, major ecological engineering construction, pollutant discharge, etc, On the basis of remote sensing data, ground observation data, meteorological data and social statistical yearbook data, the positive and negative effects of human activities are quantitatively evaluated by AHP, and the intensity and change characteristics of human activities are comprehensively evaluated. The data can not only help to enhance the understanding of the role of human activities in the vegetation change in the sensitive areas of global change, but also provide theoretical basis for the sustainable development of social economy in the Qinghai Tibet Plateau, and provide scientific basis for protecting the ecological environment of the plateau and building a national ecological security barrier.
ZHANG Haiyan, XIN Liangjie, FAN Jiangwen, YUAN Xiu
Geographical distribution of major ecological protection and construction projects on the Tibetan plateau. There are four main projects, i.e. forest protection and construction project, grassland protection and construction project, desertification control project, soil erosion comprehensive control project. Processing method: classified summary, and the county as a unit of the regional distribution.
Da Wei
1、Based on field eddy correlation (EC) measurement data, using the standard data processing method for EC data, including despiking, coordinate rotation, air density corrections, outlier rejection, and friction velocity threshold (u*) corrections, gap filled, and NEE partition. The dataset collects carbon flux data and microclimate measurement data from 2003 to 2016 in three typical alpine grassland ecosystems on the Qinghai-Tibet Plateau, including Damxung alpine meadow, Haibei alpine meadow ，Naqu alpine meadow，Zoige alpine grassland，Qilian mountion grassland . The time resolution of data is high (30 min), and the interpolation of data is complete throughout the year. This dataset can be applied to carbon flux assessment, comparison and prediction in these alpine meadows, attribution of climate factors affecting carbon flux, validation of model simulation results, etc. 2、Based on the MCDGF43 dataset, we produce the visible and near-infared albedo of Tibetan Plateau, using the standard data processing of hdf to tif , including the moasic, resample and masked by Tibetan Plateau's boundary. The time resolution of dataset is 8 days and the spatial resolution is 500 meters, which span the period of 2003-2016.
ZHANG Yangjian, SU Peixi, YANG Yan
This data set includes biomass survey data observed from the carbon flux station in the Guoluo Army Ranch in Qinghai from 2005 to 2009. Carbon flux data observation method: vorticity-related observation instruments were used for automatic recording; biomass observation method: harvest method, weighing in a 60-degree oven for 48 hours. The carbon flux data were automatically recorded by the instruments and manually checked. Observations and data collection were carried out in strict accordance with the instrument operating specifications and were published in relevant academic journals. During the data observation process, the operation of the instrument and the selection of the observational objects were in strict accordance with professional requirements, and the data could be applied to plant leaf photosynthetic parameter simulation and production estimation. 1) Biological observational data of the Guoluo meadow ecosystem: Date, site number, vegetation type, plot number, aboveground biomass (g/m²), underground biomass (g/m²), total biomass (g/m²) 2) Carbon flux observational data of the Guoluo meadow ecosystem: Site number, date, vegetation type, soil type, water vapor flux (w/m²), carbon flux (mg/m²·S) The fixed point observation data are of high precision.
ZHAO Xinquan
This data set includes carbon flux data and soil moisture data obtained from the Swamp Meadow Carbon Flux Station in Dangxiong. The temporal coverage is from 2009 to 2010. The temporal resolution of carbon flux data is 4 hours, and it records data from 00:00 to 20:00; the temporal resolution of the soil moisture data is 1 day. All data were automatically recorded by the vorticity-related observing instruments and manually checked. The observation and collection of the data were performed in strict accordance with the instrument operating specifications. During the data observation process, the operation of the instrument and the selection of the observation object were strictly in accordance with professional requirements. The data were collected at Dangxiong Wetland Carbon Flux Observatory of Lhasa Agro-ecological Station of Chinese Academy of Sciences, longitude: 91°07’; latitude: 30°50’; and altitude: 4333 m. The data set can be used in simulations of plant leaf photosynthetic parameter and evaluations of productivity to study the water and carbon processes of wetland ecosystems and their responses to climate change.
SHI Peili
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