Soil moisture is an important boundary condition of earth-atmosphere exchanges, and it has been defined as an essential climate variable by GCOS. Vegetation optical depth is a physical variable to measure the attenuation of vegetation in microwave radiative transfer model, and it has been proved to be a good indicator of vegetation water content and biomass. This dataset uses the multi-channel collaborative algorithm (MCCA) to retrieve both soil moisture and polarized vegetation optical depth with SMAP brightness temperature. The algorithm uses a self-constraint relationship between land parameters and an analytical relationship between brightness temperature at different channels to perform the retrieval process. The MCCA does not depend on other auxiliary data on vegetation properties and can be applied to a variety of satellites. The soil moisture product from this dataset includes the soil moisture content in the unfrozen period and the liquid water content in the frozen period. Both horizontal- and vertical-polarization vegetation optical depth are retrieved. So far as we know, it is the first polarization-dependent vegetation optical depth product at L-band. This dataset was validated by 19 dense soil moisture observation networks (9 core validation sites used by SMAP team and 13 sites not used by them), and the widely used soil climate analysis network (SCAN). It was found that ubRMSE (unbiased root mean square error) of MCCA retrieved soil moisture is generally smaller than that of other SMAP products.
ZHAO Tianjie, PENG Zhiqing , YAO Panpan, SHI Jiancheng
This data uses a landslide hazard risk assessment model consisting of four modules: landslide hazard causative factors, landslide susceptibility model, exposed population and population casualty rate. The module of hazard-causing factors includes DEM, slope, rainfall, temperature, snow cover, GDP, and vegetation cover factors. The landslide hazard susceptibility model is a statistical analysis using a logistic regression model to obtain landslide susceptibility probability values. The population exposure module uses the landslide susceptibility values overlaid with population data. The population casualty rate module is based on the ratio of historical landslide casualties to the population exposed to landslides during the same period. Finally, by substituting the 2020 population data, the exposed population under different levels of landslide hazard susceptibility is calculated and multiplied with the historical period landslide hazard population casualty rate to assessIntegrated multi-hazard population risk in the peri-Himalayan and Asian water tower regions
Based on long-term series Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover products, daily snow cover products without data gaps at 500 m spatial resolution over the Tibetan Plateau from 2002 to 2021 were generated by employing a Hidden Markov Random Field (HMRF) modeling technique. This HMRF framework optimally integrates spectral, spatiotemporal, and environmental information together, which not only fills data gaps caused by frequent clouds, but also improves the accuracy of the original MODIS snow cover products. In particular, this technology incorporates solar radiation as an environmental contextual information to improve the accuracy of snow identification in mountainous areas. Validation with in situ observations and snow cover derived from Landsat-8 OLI images revealed that these new snow cover products achieved an accuracy of 98.31% and 92.44%, respectively. Specifically, the accuracy of the new snow products is higher during the snow transition period and in complex terrains with higher elevations as well as sunny slopes. These gap-free snow cover products effectively improve the spatiotemporal continuity and the low accuracy in complex terrains of the original MODIS snow products, and is thus the basis for the study of climate change and hydrological cycling in the TP.
HUANG Yan , XU Jianghui
The dataset includes lake ice phenology information of 132 lakes across the Tibetan Plateau (with area larger than 40 km2) from 1978 to 2016 (freeze-up start date, freeze-up end date, break-up start date, break-up end, completely ice-duration and ice duration). The data set uses the combination of model and remote sensing to obtain the phenological information. Firstly, Using the average lake surface temperature extracted by MOD11A2 as calibration data, daily scale long-time series lake surface temperature series was simulated based on an improved lake semi-physical model (air2water). Then the temperature threshold of lake ice phenology was determined by the mod10a1 snow cover product. Compared with the existing research results and data sets, the correlation (R-square) is higher than 0.75. Combined with the advantages of remote sensing and numerical model, this dataset provides support for the analysis of water-air interface exchange, water or heat balance, biochemical processes and their response to climate change of lakes on a large spatio-temporal scale across the Tibetan Plateau.
GUO Linan , WU Yanhong, ZHENG Hongxing, ZHANG Bing , CHI Haojing , FAN Lanxin
This database includes slope, aspect and digital elevation model (DEM) data of Qinghai Tibet Plateau. The data comes from the 30m * 30m resolution numerical elevation model data downloaded from the geospatial data cloud website. Using the surface analysis function of ArcGIS software, the slope and aspect information of the Qinghai Tibet Plateau are extracted. The data has been rechecked and reviewed by many people, and its data integrity, position accuracy and attribute accuracy meet the standards, with excellent and reliable quality. As one of the engineering geological conditions, this data is the basic data for the research on the development law of major engineering disturbance disasters and major natural disasters in the Qinghai Tibet Plateau and the analysis of susceptibility, risk and risk.
The fluctuation of a single lake level is a comprehensive reflection of water balance within the basin, while the regional consistent fluctuations of lake level can indicate the change of regional effective moisture. Previous researches were mainly focused on reconstructing effective moisture by multiproxy analyses of lake sediments, but lacked the quantitative studies on regional effective moisture variation. This dataset exhibits the Holocene effective moisture change in typical lake regions of the Tibetan Plateau and East and Central Asia, including Qinghai Lake, Chen Co, Bangong Co, etc., by constructing a virtual lake system, based on a lake energy balance model, a lake water balance model and a transient climate evolution model. The simulation results provide a new perspective for exploring the evolution of lakes on the millennial scale.
The data is the phytoplankton data of 70 points in 26 lakes in Tibet in 2020. The sampling time is from August to September. The sampling method is the conventional phytoplankton sampling method. 1.5 liters of samples are collected, fixed by Lugo's solution, siphoned and concentrated after static precipitation, and the results are examined by inverted microscope. The data includes the density data of different phytoplankton of 77 species / genus in 10 categories, including diatom, green algae, cyanobacteria, dinoflagellate, naked algae, cryptoalgae, brown algae, brown algae and CHAROPHYTA. This data is original and unprocessed. The unit is piece / L. The data can be used to characterize the composition and abundance of phytoplankton in the open water areas of these lakes, and can also be used to calculate the diversity of phytoplankton communities in these lakes.
Glacial mass balance is one of the most important glaciological parameters to characterize the accumulation and ablation of glaciers. Glacier mass balance is the link between climate and glacier change, and it is the direct reflection of glacier to the regional climate. Climate change leads to the corresponding changes in the material budget of glaciers, which in turn can lead to changes in the movement characteristics and thermal conditions of glaciers, and then lead to changes in the location, area and ice storage of glaciers. The monitoring method is to set a fixed mark flower pole on the glacier surface and regularly monitor the distance between the glacier surface and the top of the flower pole to calculate the amount of ice and snow melting; In the accumulation area, the snow pits or boreholes are excavated regularly to measure the snow density, analyze the characteristics of snow granular snow additional ice layer, and calculate the snow accumulation; Then, the single point monitoring results are drawn on the large-scale glacier topographic map, and the instantaneous, seasonal (such as winter and summer) and annual mass balance components of the whole glacier are calculated according to the net equilibrium contour method or contour zoning method. The data set is the annual mass balance data of different representative glaciers in the Qinghai Tibet Plateau and Tianshan Mountains, in millimeter water equivalent.
Glacier is the supply water source of rivers in the western mountainous area, and it is one of the most basic elements for people to survive and develop industry, agriculture and animal husbandry in the western region. Glaciers are not only valuable fresh water resources, but also the source of serious natural disasters in mountainous areas, such as sudden ice lake outburst flood, glacier debris flow and ice avalanche. Glacier hydrological monitoring is the basis for studying the characteristics of glacier melt water, the replenishment of glacier melt water to rivers, the relationship between glacier surface ablation and runoff, the process of ice runoff and confluence, and the calculation and prediction of floods and debris flows induced by glacier and seasonal snow melt water. Glacial hydrology refers to the water and heat conditions of glacial covered basins (i.e. glacial action areas), that is, the water and heat exchange between glaciers and their surrounding environment, the physical process of water accumulation and flow on the surface, inside and bottom of glaciers, the water balance of glaciers, the replenishment of glacial melt water to rivers, and the impact of water bodies in cold regions on climate change. At present, hydrological monitoring stations are mainly established at the outlet of the river basin to carry out field monitoring《 Glacial water resources of China (1991), hydrology of cold regions of China (2000) and glacial Hydrology (2001) summarize the early studies on glacial hydrology. China has carried out glacier hydrological monitoring on more than 20 glaciers in Tianshan, Karakorum, West Kunlun, Qilian, Tanggula, Nianqing Tanggula, gangrigab, Hengduan and Himalayas. This data set is the monthly runoff data of representative glaciers.
YANG Wei, LI Zhongqin, WANG Ninglian, QIN Xiang
Lakes collect runoff, sediment and nutrients from upstream watersheds and are an important "destination" of material migration at the watershed scale. Therefore, the attributes of lake water and sediment are affected by catchment attributes (e.g. climate, terrain and vegetation conditions) to a large degree. This dataset delineates the watershed boundaries of 1525 Lakes (with an area from 0.2 to 4503 square kilometers) on the Tibetan Plateau, and calculates 721 catchment-scale attributes on the aspects of lake body, terrain, climate, vegetation, soil/geology and anthropogenic activities. This is the first dataset of lake-catchment characteristics on the Tibetan Plateau, which can provide foundamental data for the study of lakes in the Tibetan Plateau.
This data set takes the freezing index calculated by the long-time scale (1901-2016) temperature provided by UEA-CRU and UDEL as the input data, calculates the soil freezing depth of Yarlung Zangbo River Basin through Stefan empirical formula, and interpolates the 30-year scale average soil freezing depth data set output by simulation. This data set takes the freezing index calculated by the long-time scale (1901-2016) temperature provided by UEA-CRU and UDEL as the input data, calculates the soil freezing depth of Yarlung Zangbo River Basin through Stefan empirical formula, and interpolates the 30-year scale average soil freezing depth data set output by simulation.
LIU Lei , LUO Dongliang , WANG Lei
This data set is a code file set of TCA (triple collision analysis) algorithm, which is used to generate the global daily-scale soil moisture fusion dataset from 2011 to 2018.
XIE Qiuxia, XIE Qiuxia, XIE Qiuxia, XIE Qiuxia, XIE Qiuxia, XIE Qiuxia, XIE Qiuxia, XIE Qiuxia, XIE Qiuxia, JIA Li , HU Guangcheng
This data is the disturbance disaster data of 1:250000 major projects in the Qinghai Tibet Plateau. For the scope of disaster interpretation, line engineering (national highway, high-speed, railway and Power Grid Engineering) and hydropower engineering are bounded by the first watershed on both sides of the project; Mine, oilfield and port projects are bounded by 1km away from the project. Engineering disturbance disasters can be divided into two categories: ① landslide, collapse and debris flow disasters induced by engineering construction; ② For natural disasters that may affect the project, it is stipulated that all natural disasters within the above interpretation scope belong to category ② engineering disturbance disasters. The data includes the location, length, width, height difference, distribution elevation, genetic type, inducing factors, occurrence time, lithology and other elements of landslide, disaster related projects and project construction years. Based on Google Earth image and 1:500000 geological diagram, 6176 disaster points were interpreted; Google Earth is mainly used for disturbance disaster interpretation, and combined with field investigation to verify the interpretation results, ArcGIS is used to generate disaster distribution map; The data comes from Google Earth high-resolution images, with high accuracy of original data. In the process of generating disaster files, the interpretation specifications are strictly followed, and special personnel are assigned to review, so the data quality is reliable; Based on the collected data, the disaster risk analysis of the study area can be carried out to provide theoretical guidance for the smooth operation of the built projects and the construction of the line projects not built / under construction.
This data set is daily surface albedo product over Tibet plateau region from 2002 to 2020 with a spatial resolution of 0.00425°. The MODIS reflectance data product was used to retrieve the Extended Multi-Sensor Combined BRDF Inversion (EMCBI) Model which has coupled with topographic effects with assistance of a BRDF priori-knowledge. The daily BRDF was retrieved in a 5-day period to collect multi-angular information from MODIS observations. And then the daily albedo is estimated, where the black sky albedo was calculated at local noon. MODIS surface reflectance data (MOD09GA and MYD09GA) are downloaded from the official website. The albedo product is quality-controlled with better temporal and spatial continuity in Tibet plateau area. The validation results show that it meets the accuracy requirements of albedo application with higher precisions comparing to the other similar products. And thus, this product is useful for the long-term environmental monitoring and radiation energy budget research study.
YOU Dongqin, YOU Dongqin, TANG Yong, TANG Yong, TANG Yong, HAN Yuan HAN Yuan
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.
To understand the potential impact of projected climate changes on the vulnerable agriculture in Central Asia (CA) in the future, six agroclimatic indicators are calculated based on the 9km-resolution dynamical downscaled results of three different global climate models and a high-resolution projection dataset of agroclimatic indicators over CA is produced. These indicators are growing season length (GSL, days), biologically effective degree days (BEDD, ℃), frost days (FD, days), summer days (SU, days), warm spell duration index (WSDI, days), and tropical nights (TR, days). The periods are 1986-2005 and 2031-2050. The spatial resolution is 0.1°. As all the indicators except WSDI are defined with absolute temperature thresholds and particularly sensitive to the systematics biases in the model data, the quantile mapping (QM) method is applied to correct the simulated temperature. Results show the QM method largely reduces the biases in all the indicators. GSL, SU, WSDI, and TR will significantly increase over CA and FD will decrease. However, changes in BEDD are spatially heterogeneous, with the increases in northern CA and the mountainous areas and decreases in the southern and middle part of the plain areas. This dataset can be applied for assessing the future risks in the local agriculture for climate changes and will be beneficial to adaption and mitigation actions for food security in this region.
QIU Yuan QIU Yuan
The vegetation type map was created by the random forest (RF) classification approach, based on 319 ground-truth samples, combined with a set of input variables derived from the visible, infrared, and thermal Landsat-8 images. According to vegetation characteristics, four types include alpine swamp meadow (ASM), alpine meadow (AM), alpine steppe (AS), and alpine desert (AD) were classified in this map. Based on a spatial resolution of 30 m, the map can provide more detailed vegetation information.
ZHOU Defu, ZOU Defu, ZOU Defu, Zhao Lin, ZHAO Lin, Liu Guangyue, LIU Guangyue, Du Erji, DU Erji, LI Zhibin , LI Zhibin, Wu Tonghua, WU Xiaodong, CHEN Jie CHEN Jie
This data is the land cover data at 30m resolution of Southeast Asia in 2015. The data format of the data is NetCDF, and the variable name is "land cover type". The data was obtained by mosaicing and extracting the From-GLC data. Several land cover types, such as snow and ice that do not exist in Southeast Asia were eliminated.The legend were reintegrated to match the new data. The data provide information of 8 land cover types: cropland, forest, grassland, shrub, wetland, water, city and bare land. The overall accuracy of the data is 71% (Gong et al., 2019). The data can provide the land cover information of Southeast Asia for hydrological models and regional climate models.
The energy supply resilience of the countries along the Belt and Road reflects the level of energy supply resilience of the countries along the Belt and Road, and the higher the value of the data, the stronger the energy supply resilience of the countries along the Belt and Road. "The energy supply resilience data for countries along the "Belt and Road" are prepared with reference to the International Energy Agency (IEA) national energy statistics (https://www.iea.org/data-and-statistics), using the 2000-2019 The energy supply resilience product was prepared based on sensitivity and adaptability analysis, using year-by-year data on coal, oil and natural gas supply in countries along the "Belt and Road", and taking into account the year-by-year changes of each energy source.
Population age structure resilience reflects the level of population age structure resilience in the countries along the Belt and Road. The World Bank's statistical database was used to prepare the data on the resilience of the population age structure of the countries along the Belt and Road. Based on the sensitivity and adaptability analysis, a comprehensive diagnosis was made based on the year-on-year change of each indicator, and the product on the resilience of population age structure was prepared.
Contact SupportNorthwest Institute of Eco-Environment and Resources, CAS 0931-4967287 firstname.lastname@example.org
LinksNational Tibetan Plateau Data Center
A Big Earth Data Platform for Three Poles © 2018-2020 No.05000491 | All Rights Reserved ｜ No.11010502040845
Tech Support: westdc.cn