Coupled Model Intercomparison Project Phase 5 (CMIP5) provides a multiple climate model environment, which can be used to predict the future climate change in the key nodes in the Belts and Road to deal with the environmental and climate problems. Key nodes in the Belt and Road are taken as the study regions of this dataset. The ability of 43 climate models in CMIP5 to predict the future climate change in the study regions was assessed and the optimal models under different scenarios were selected according to the RMSE between the prediction results and real observations. This dataset is composed of the prediciton results of precipitation and near-surface air temperature between 2006 and 2065 using the optimal models in monthly temporal frequncy. The spatial resolution of the dataset has been downscaled to 10 km using statistical downscaling method. Data of each period has three bands, namely maximum near-surface air temperature, minimum near-surface air temperature and precipitation. In this data set, the unit of precipitation is kg / (m ^ 2 * s), and the unit of near-surface air temperature is K. This dataset provides data basis for solving environmental and climate problems of the key nodes in the Belts and Road.
LI Xinyan, LING Feng
I. Overview This data set contains socio-economic statistics of counties (cities) in the upper reaches of the Yellow River from 2000 to 2005. The data set is divided into basic conditions, comprehensive economics, agriculture, industry and infrastructure, education, health and social security, 4 There are 30 basic categories, including all the socio-economic statistical indicators. Ⅱ. Data processing description The data is stored in excel format, classified by province, with basic socio-economic statistics for each county. Ⅲ. Data content description This data set contains four basic classifications, namely basic situation, comprehensive economy, agriculture, industry and infrastructure, education, health and social security. The basic information includes the administrative area, the number of townships (towns), the number of villagers' committees, the total number of households at the end of the year, the number of rural households, the rural population, the number of employees at the end of the year, the number of rural employees, and the number of agricultural, forestry, animal husbandry and sideline fishermen The total power of agricultural machinery and local telephone users; the total economic categories include: the value added of the primary industry, value added of the secondary industry, revenue within the local fiscal budget, fiscal expenditure, the balance of savings deposits of urban and rural residents, and loans of financial institutions at the end of the year Balance; major categories of agriculture, industry and capital construction include: grain output, cotton output, oil output, total meat output, number of industrial enterprises above designated size, total industrial output value above designated size, and capital investment completed; education, health and social security The major categories include the number of students in ordinary middle schools, the number of students in primary schools, the number of beds in hospitals and health centers, the number of beds in social welfare homes, and the number of beds in social welfare homes. In some remote areas, some data are missing. Ⅳ. Data usage description Through this data set, the socio-economic problems of counties (cities) in the upper reaches of the Yellow River can be analyzed, and the socio-economic driving forces of certain natural processes can be analyzed and researched through this data set.
XUE Xian, DU Heqiang
The data is a dataset of road distribution in Qinghai Lake basin, scale1: 250,000, projection: latitude and longitude, mainly including the spatial distribution and attribute data of main roads in Qinghai Lake basin, attribute fields: code (road code), name (road classification).
National Basic Geographic Information Center
Tarim River is the largest inland river in China, with a total length of 2179 kilometers. Tarim River Basin is one of the vulnerable areas of ecological environment in China. Due to the lack of coordination in material and energy matching, different regions show different vulnerability characteristics in macro. According to the relevant principles of ecological environment quality evaluation, combined with the ecological environment management of the Tarim River Basin. Data is road distribution data set of Tarim River Basin, scale: 250000, projection: longitude and latitude, mainly including spatial distribution and attribute data of main roads in Heihe River Basin, attribute fields: Code (road code), name (road classification) Collect and sort out the basic, meteorological, topographical and geomorphological data of the Tarim River Basin, and provide data support for the management of the Tarim River Basin.
National Basic Geographic Information Center
This data was derived from "1: 100,000 Land Use Data of China". Based on Landsat MSS, TM and ETM remote sensing data, 1: 100,000 Land Use Data of China was compiled within three years by a remote sensing scientific and technological team of 19 research institutes affiliated to the Chinese Academy of Sciences, which was organized by the “Remote Sensing Macroinvestigation and Dynamic Research on the National Resources and Environment", one of the major application programs in Chinese Academy of Sciences during the "Eighth Five-year Plan". This data adopts a hierarchical land cover classification system, which divides the country into 6 first-class categories (cultivated land, forest land, grassland, water area, urban and rural areas, industrial and mining areas, residential land and unused land) and 31 second-class categories. This is the most accurate land use data product in our country at present. It has already played an important role in national land resources survey, hydrology and ecological research.
LIU Jiyuan, ZHUANG Dafang, WANG Jianhua, ZHOU Wancun, WU Shixin
1) Initial data of community characteristics and main plant biological characteristics of the grass-animal equilibrium stage of the test grassland in 1983; 2) Livestock management data of 4-5 grazing grasslands; 3) Observation data of diversity, productivity and functional group of different grazing grassland communities; 4) Observation data on the height, coverage, biomass, and flower morphology, tillering, and leaf characteristics of main plants in different grazing gradient grasslands 5) Observation data of soil nutrients and litter in different grazing grasslands.
ZHAO Chengzhang
The data is the railway distribution map of the north slope of Tianshan River Basin, with a scale of 25000 and the projection is longitude and latitude. the data includes spatial data and attribute data, and the attribute field is code (railway code).
National Basic Geographic Information Center
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.
The data set is the qaidam river basin administrative boundary vector map, scale 250000, projection: longitude and latitude, the data contains spatial data and attribute data, mainly the qaidam river basin county boundary name and administrative code.
WU Lizong
Shule River Basin is one of the three inland river basins in Hexi corridor. In recent years, with the obvious change of climate and the aggravation of human activities, the shortage of water resources and the problem of ecological environment in Shule River Basin have become increasingly prominent. It is of great significance to study the runoff change of Shule River Basin in the future climate situation for making rational water resources planning and ecological environment protection. The data set is the administrative boundary vector map of Shule River Basin, with a scale of 250000. The data includes spatial data and attribute data. The attribute fields are name (county boundary name) and code (administrative code). Collect and sort out the basic, meteorological, topographical and geomorphic data of Shule River Basin, and provide data support for the management of Shule River Basin.
National Basic Geographic Information Center
The data set of prokaryotic microorganism distribution in the snow and ice of the Arctic Antarctic and the Tibetan Plateau provides the bacterial 16S ribosomal RNA gene sequence collected by the experimental group led by Yongqin Liu from the NCBI database during 2010 to 2018. The keywords for NCBI database search are Antarctic, Arctic Tibetan, and Glacier. The collected sequences were calculated using the DOTOUR software to obtain the similarities between sequences, the sequences with similarities above 97% were clustered into one OTU, and the OTU representative sequence was defined. The OTU representative sequence was compared with the RDP database by the "Classifier" software and was identified as level one when the reliability exceeded 80%. After acquiring the sequence, the GPS coordinates of the sample were obtained by reading the sample information in the sequence file. These data contain the sequence of 16S ribosomal RNA gene fragments for each sequence, evolutionary classification, and sample GPS coordinates. Compared with sequences based on high-throughput sequencing, these data have a longer sequence and more accurate classification. It is significant for comparing the evolutionary information of three-pole microorganisms and understanding the evolution of psychrophilic microorganisms.
JI Mukan
The data include the night light data of Tibetan Plateau with a spatial resolution of 1km*1km, a temporal resolution of 5 years and a time coverage of 2000, 2005 and 2010.The data came from Version 4 dmsp-ols products. DMSP/OLS sensors took a unique approach to collect radiation signals generated by night lights and firelight.DMSP/OLS sensors, working at night, can detect low-intensity lights emitted by urban lights, even small-scale residential areas and traffic flows, and distinguish them from dark rural backgrounds.Therefore, DMSP/OLS nighttime light images can be used as a representation of human activities and become a good data source for human activity monitoring and research.
FANG Huajun
The dataset includes vector map of the lakes larger than 1k㎡ on Tibetan Plateau in 1970s, 1990, 2000, 2010. The lake boundry data was extracted from remote sensing image like Landsat MSS, TM, ETM+, by means of visual interpretation. The data type is vector data, and it's attribute class includes Area (km²). The Projected Coordinate System is Albers Conical Equal Area. It is mainly used in the study of changes in lakes, hydrological and meteorological on the Tibetan Plateau.
ZHANG Guoqing
The data set includes: population and GDP data of the arctic (1990-2015) and county-level population and GDP data of the third pole region (gansu, qinghai and Tibet) (1970-2016). Socio-economic statistical attributes include: population (ten thousand), GDP (ten thousand yuan), total industrial and agricultural output (ten thousand yuan), total agricultural output (ten thousand yuan), and total industrial output (ten thousand yuan). The arctic population data are mainly derived from the world populationProspects: 2017 revision by the Department of economic and social affairs, which divides the total population by region and country. The data of the third pole mainly refer to the statistical yearbook of gansu province, qinghai province and Tibet autonomous region.County records of gansu, qinghai and Tibet autonomous regions.
Department of Economic and Social Affairs, National Bureau of Statistics, Qinghai Provincial Bureau of Statistics
It is summarized that the agricultural and socio-economic status of the five Central Asian countries (Kazakhstan, Kyrgyzstan, Tajikistan, Uzbekistan and Turkmenistan) in 2016. This data comes from the statistical yearbook of five Central Asian countries, including six elements: total population, cultivated land area, grain production area, GDP, proportion of agricultural GDP to total GDP, proportion of industrial GDP to total GDP, and forest area. Detailed statistics of the six socio-economic elements of the five Central Asian countries. It can be seen from the statistics that there are different emphases among the six elements of the five Central Asian countries. This data provides basic data for the project, facilitates the subsequent analysis of the ecological and social situation in Central Asia, and provides data support for the project data analysis.
LIU Tie
The data is the reservoir distribution dataset of the north slope of Tianshan River Basin, which is comprehensively prepared by using topographic map and remote sensing image. The scale is 250000, and the projection is latitude and longitude. The data includes spatial data and attribute data, and the attribute field is Name (reservoir name), reflecting the reservoir distribution status of River Basin in the northern foot of Tianshan Mountain around 2000.
National Basic Geographic Information Center
Shule River Basin is one of the three inland river basins in Hexi corridor. In recent years, with the obvious change of climate and the aggravation of human activities, the shortage of water resources and the problem of ecological environment in Shule River Basin have become increasingly prominent. It is of great significance to study the runoff change of Shule River Basin in the future climate situation for making rational water resources planning and ecological environment protection. The Shule River basin boundary is cut from "China's 1:100000 desert sand data set". Taking the 2000 TM image as the data source, it interprets, extracts, revises, and uses remote sensing and geographic information system technology to combine with the 1:100000 scale mapping requirements to carry out thematic mapping of desert, sand and gravel gobi. Data attribute table: Area (area), perimeter (perimeter), ash_ (sequence code), class (desert code), ash_id (desert code). The desert code is as follows: mobile sand 2341010, semi mobile sand 2341020, semi fixed sand 2341030, Gobi 2342000, salt alkali land 2343000. Collect and sort out the basic, meteorological, topographical and geomorphic data of Shule River Basin, and provide data support for the management of Shule River Basin.
The Tibetan Plateau in China covers six provinces including Tibet, Qinghai, Xinjiang, Yunnan, Gansu and Sichuan, including Tibet and Qinghai, as well as parts of Xinjiang, Yunnan, Gansu and Sichuan. The research on water and soil resources matching aims to reveal the equilibrium and abundance of water resources and land resources in a certain regional scale. The higher the level of consistency between regional water resources and the allocation of cultivated land resources, the higher the matching degree, and the superior the basic conditions of agricultural production. The general agricultural water resource measurement method based on the unit area of cultivated land is used to reflect the quantitative relationship between the water supply of agricultural production in the study area and the spatial suitability of cultivated land resources. The Excel file of the data set contains the generalized agricultural soil and water resource matching coefficient data of the Tibetan Plateau municipal administrative region in China from 2008 to 2015, the vector data is the boundary data of the Tibetan Plateau municipal administrative region in China in 2004, and the raster data pixel value is the generalized agricultural soil and water resource matching coefficient of the year in the region.
DONG Qianjin, DONG Lingxiao
This data set contains the statistical information of natural disasters in Qinghai Tibet Plateau in the past 50 years (1950-2002), including drought, snow disaster, frost disaster, hail, flood, wind disaster, lightning disaster, cold wave and strong cooling, low temperature and freezing damage, gale sandstorm, insect disaster, rodent damage and other meteorological disasters. Qinghai and Tibet are the main parts of the Qinghai Tibet Plateau. The Qinghai Tibet Plateau is one of the Centers for the formation and evolution of biological species in China. It is also a sensitive area and fragile zone for the international scientific and technological circles to study climate and ecological environment changes. Its complex terrain conditions, high altitude and severe climate conditions determine that the ecological environment is very fragile, It has become the most frequent area of natural disasters in China. The data were extracted from "China Meteorological Disaster Canon · Qinghai volume" and "China Meteorological Disaster Canon · Tibet Volume", which were manually input, summarized and proofread.
Statistical Bureau Statistical Bureau
The glacial bacterial resource database of the Tibetan Plateau provides the bacterial 16S ribosomal RNA gene sequences of several glaciers, which are seven glaciers of the Tibetan Plateau separated by an experimental group led by Yongqin Liu during 2010 to 2018 (East Rongbuk Glacier of Mt. Qomolangma, Tianshan Glacier No.1, Guliya Glacier, Laohugou Glacier, Muztagh Ata Glacier, Qiyi Glacier and Yuzhufeng Glacier), the Malan Glacier separated by Shurong Xiang and the Puruogangri Glacier separated by Xinfang Zhang. After the glacier samples were collected, they were taken to the Ecological Laboratory of the Institute of Tibetan Plateau Research of the Chinese Academy of Sciences in Beijing and the National Cryosphere Laboratory in Lanzhou. After applying the spread plate method, the samples were cultured at different temperatures (4-25 °C) for 20 days to 90 days, and single colonies were picked out for purification. After the DNA was extracted from the isolated bacteria, the 16S ribosomal RNA gene fragment was amplified with 27F/1492R primer and sequenced using the Sanger method. The 16S ribosomal RNA gene sequence was compared with the RDP database using the "Classifier" software and identified as level one when the reliability exceeded 80%. These data contain the 16S ribosomal RNA gene fragment sequence and glacier sources of each sequence. Compared with sequences based on high-throughput sequencing, these data have a longer sequence and more accurate classification and can better serve in glacier microbiology research.
JI Mukan
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