This data set is the spatial distribution of soil POPs in the Tibetan Plateau, including OCPs, PCBs, PBDEs and PAHs. Fourty soil samples were taken from remote sites (i.e., away from towns, roads, or other human activity) in 8 soil zones of the Tibetan Plateau in 2007. The samples were collected using a stainless steel hand-held corer.Five cores (0-5 cm), taken over an area of ~100 m2, were bulked together to form one sample. The samples were wrapped in aluminum foil twice and sealed in two plastic bags to minimize the possibility for contamination. All the samples were analyzed at Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Chinese Academy of Sciences. The samples were Soxhlet-extracted, purified on an aluminium/silica column (i.d. 8 mm), a gel permeation chromatography (GPC) column subsequently, and were detected on a gas chromatograph with an ion-trap mass spectrometer (GC-MS, Finnigan Trace GC/PolarisQ) operating under MS–MS mode. A CP-Sil 8CB capillary column (50 m ×0.25 mm, film thickness 0.25 μm) was used for OCPs, PCBs and PBDEs, and a DB-5MS column (60 m ×0.25mm, film thickness 0.25 μm) was used for PAHs. Procedural blanks were prepared. The recoveries ranged from 53% to 130% for OCPs, and 58% to 92% for PAHs. The reported concentrations were not corrected for recoveries.
WANG Xiaoping
The distribution data of Central Asia desert oil and gas fields are in the form of vector data in ". SHP". Including the distribution of oil and gas fields and major urban settlements in the five Central Asian countries. The data is extracted and cut from modis-mcd12q product. The spatial resolution of the product is 500 m, and the time resolution is 1 year. IGBP global vegetation classification scheme is adopted as the classification standard. The scheme is divided into 17 land cover types, among which the urban data uses the construction and urban land in the scheme. The data can provide data support for the assessment and prevention of sandstorm disasters in Central Asia desert oil and gas fields and green town.
GAO Xin
The data set is the basic data of the Qinghai Tibet Plateau in 2015. The original data comes from the National Basic Geographic Information Center, and the data of the Qinghai Tibet plateau region is formed by splicing and clipping the segmented data. The data content includes 1:1 million provincial administrative divisions, 1:1 million roads and 1:250000 water system. The data attributes of administrative divisions include name, code and Pinyin; Road data attributes include: GB, RN, name, rteg and type (basic geographic information classification code, road code, road name, road grade and road type); Water system data attributes include: GB, hydc, name, period (basic geographic information classification code, water system name code, name, season).
YANG Yaping
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 distribution of the average roughness in Central Asia including three temperate deserts, the Karakum, Kyzylkum and Muyunkun Deserts, and one of the world's largest arid zones. This is the MODIS-NDVI data set calculated by using the median particle diameter and the vegetation coverage. The space and time resolutions are 500 m and 16 days, respectively. The time is from 01, January, 2017 to 18, December, 2017. The data set uses the the Geodetic coordinate system. It can be used for the investigation of the Desert oil and gas field, and oasis cities.
GAO Xin
This dataset contains five types of boundaries. 1. TPBoundary_ 2500m: Based on ETOPO5 Global Surface Relief, ENVI+IDL was used to extract data at an elevation of 2500m within the longitude (65~105E) and latitude (20~45N) range in the Tibetan Plateau. 2. TPBoundary_ 3000m: Based on ETOPO5 Global Surface Relief, ENVI+IDL was used to extract data at an elevation of 3000m within the longitude (65~105E) and latitude (20~45N) range in the Tibetan Plateau. 3. TPBoundary_ HF (high_frequency): This boundary is defined according to 2 previous studies. Bingyuan Li (1987) had a systematic discussion on the principles for determining the extent of the Tibetan Plateau and the specific boundaries. From the perspective of the formation and basic characteristics of the Tibetan Plateau, he proposed the basic principles for determining the extent of the Tibetan Plateau based on the geomorphological features, the plateau surface and its altitude, while considering the integrity of the mountain. Yili Zhang (2002) determined the extent and boundaries of the Tibetan Plateau based on the new results of research in related fields and years of field practice. He combined information technology methods to precisely locate and quantitatively analyze the extent and boundary location of the Tibetan Plateau, and concluded that the Tibetan Plateau in China extends from the Pamir Plateau in the west to the Hengduan Mountains in the east, from the southern edge of the Himalayas in the south to the northern side of the Kunlun-Qilian Mountains in the north. On April 14, 2017, the Ministry of Civil Affairs of the People's Republic of China issued the Announcement on Adding Geographical Names for Public Use in the Southern Tibetan Region (First Batch), adding six geographical names in the southern Tibetan region, including Wo’gyainling, Mila Ri, Qoidêngarbo Ri, Mainquka, Bümo La, and Namkapub Ri. ４. TPBoundary_ New (2021): Along with the in-depth research on the Tibetan Plateau, the improvement of multidisciplinary research and understanding inside and outside the plateau, and the progress of geographic big data and Earth observation science and technology, the development of the 2021 version of the Tibetan Plateau boundary data by Yili Zhang and et al. was completed based on the comprehensive analysis of ASTER GDEM and Google Earth remote sensing images. The range boundary starts from the northern foot of the West Kunlun Mountain-Qilian Mountain Range in the north and reaches the southern foot of the Himalayas and other mountain ranges in the south, with a maximum width of 1,560 km from north to south; from the western edge of the Hindu Kush Mountains and the Pamir Plateau in the west to the eastern edge of the Hengduan Mountains and other mountain ranges in the east, with a maximum length of about 3,360 km from east to west; the latitude and longitude range is 25°59′30″N~40°1′0″N, 67°40′37″E~104°40′57″E, with a total area of 3,083,400km2 and an average altitude of about 4,320m. Administratively, the Tibetan Plateau is distributed in nine countries, including China, India, Pakistan, Tajikistan, Afghanistan, Nepal, Bhutan, Myanmar, and Kyrgyzstan. ５. TPBoundary_ Rectangle: The rectangle was drawn according to the range of Lon (63~105E) and Lat (20~45N). The data are in latitude and longitude projection WGS84. As the basic data, the boundary of the Tibetan Plateau can be used as a reference basis for various geological data and scientific research on the Tibetan Plateau.
ZHANG Yili
The data set was produced based on the SRTM DEM data collected by Space Shuttle Radar terrain mission in 2016, the reference data such as river, lake and other water system auxiliary data , using the arcgis hydrological model to analyze and extract the river network. There are 12 sub-basins over the Tibet Plateau, including AmuDayra、Brahmaputra、Ganges、Hexi、Indus、Inner、Mekong、Qaidam、Salween、Tarim、Yangtze、Yellow. The outer boundary is based on the 2500-metre contour line and national boundaries.
ZHANG Guoqing
This dataset includes boundary and topographic data of Southeastern Tibetan Plateau (SETP): 1. SETP_ Boundary: we centered on the traditional SETP region (i.e., the Parlung Tsangpo River basin or Bomi County) and used the surrounding river network (e.g., the Yarlung Zangbo-Brahmaputra River, Nujiang-Salween River, and their tributaries) to delineate the boundary of the SETP. This region covers the Eastern Nyainqentanglha Ranges, Eastern Himalayas, and Western Hengduan Mountains and hosts the largest maritime glacier concentration across China. 2. Topographic data: Based on NASADEM provided by NASA Earthdata, we mosaicked the DEM, slope, aspect, profile curvature (profc) and water Mask (SWB) of SETP. 3. Hillshade: We produced the hillshde with a altitude angle of 45° from the NASADEM of SETP.
ZHAO Fanyu, LONG Di, LI Xingdong, HUANG Qi, HAN Pengfei
1) The work of automatically dividing a wide and complex geospatial area or even a complete watershed into repeatable and geomorphically consistent topographic units is still in the stage of theoretical concept, and there are great challenges in practical operation. Terrain unit is a further subdivision of topography and geomorphology, which can ensure the maximum uniformity of geomorphic features in slope unit and the maximum heterogeneity between different units. It is suitable for geomorphic or hydrological modeling, landslide detection in remote sensing images, landslide sensitivity analysis and geological disaster risk assessment. 2) Slope unit is an important type of topographic unit. Slope unit is defined as the area surrounded by watershed and catchment line. In fact, the area surrounded by watershed and catchment line is often multiple slopes or even a small watershed. Theoretically, each slope unit needs to ensure the maximum internal homogeneity and the maximum heterogeneity between different units. The slope unit is an area with obviously different topographic characteristics from the adjacent area. These topographic characteristics can be based on the characteristics of catchment or drainage boundary, slope and slope direction, such as ridge line, valley line, platform boundary, valley bottom boundary and other geomorphic boundaries. According to the high-precision digital elevation model, the slope unit with appropriate scale and quality can be drawn manually, but the manual drawing method is time-consuming and error prone. The quality of the divided slope unit depends on the subjective experience of experts, which is suitable for small-scale areas and has no wide and universal application value. Aiming at the gap in practical operation in this field, we propose an innovative modeling software system to realize the optimal division of slope units. Automatic division system of slope unit based on confluence analysis and slope direction division v1 0, written in Python programming language, runs and calculates as the grass GIS interpolation module, and realizes the automatic division of slope units in a given digital elevation data and a set of predefined parameters. 4) Based on python programming language, the code is flexible and changeable, which is suitable for scientific personnel with different professional knowledge to make a wide range of customization and personalized customization. In addition, the software can provide high-quality slope unit division results, reflect the main geomorphic characteristics of the region, and provide a based evaluation unit for fine landslide disaster evaluation and prediction. It can serve regional land use planning, disaster risk assessment and management, disaster emergency response under extreme induced events (earthquake or rainfall, etc.), and has great practical guiding significance for the selection of landslide monitoring equipment and the reasonable and effective layout and operation of early warning network. It can be popularized and applied in areas with serious landslide development.
YANG Zhongkang
1) In mountainous areas, due to the complex topographic and geological background conditions, landslides are very easy to occur triggered by external factors such as rainfall, snow melting, earthquake and human engineering activities, resulting in the loss of life and property and the destruction of the natural environment. In order to meet the safety of project site construction, the rationality of land use planning and the urgent needs of disaster mitigation, it is necessary to carry out regional landslide sensitivity evaluation. When many different evaluation results are obtained by using a variety of different methods, how to effectively combine these results to obtain the optimal prediction is a technical problem that is still not difficult to solve at present. It is still very lack in determining the optimal strategy and operation execution of the optimal method for landslide sensitivity evaluation in a certain area. 2) Using the traditional classical multivariate classification technology, through the evaluation of model results and error quantification, the optimal evaluation model is combined to quickly realize the high-quality evaluation of regional landslide sensitivity. The source code is written based on the R language software platform. The user needs to prepare a local folder separately to read and store the software operation results. The user needs to remember the folder storage path and make corresponding settings in the software source code. 3) The source code designs two different modes to display the operation results of the model. The analysis results are output in the standard format of text and graphic format and the geospatial mode that needs spatial data and is displayed in the standard geographic format. 4) it is suitable for all people interested in landslide risk assessment. The software can be used efficiently by experienced researchers in Colleges and universities, and can also be used by government personnel and public welfare organizations in the field of land and environmental planning and management to obtain landslide sensitivity classification results conveniently, quickly, correctly and reliably. It can serve regional land use planning, disaster risk assessment and management, disaster emergency response under extreme induced events (earthquake or rainfall, etc.), and has great practical guiding significance for the selection of landslide monitoring equipment and the reasonable and effective layout and operation of early warning network. It can be popularized and applied in areas with serious landslide development
YANG Zhongkang
This data set includes the social, economic, resource and other relevant index data of Gansu, Qinghai, Sichuan, Tibet, Xinjiang and Yunnan in the Qinghai Tibet Plateau from 2000 to 2015. The data are derived from Gansu statistical yearbook, Qinghai statistical yearbook, Sichuan statistical yearbook, Xizang statistical yearbook, Xinjiang statistical yearbook, Yunnan statistical Yearbook China county (city) socio economic statistical yearbook And China economic network, guotai'an, etc. The statistical scale is county-level unit scale, including 26 county-level units such as Yumen City, Aksai Kazak Autonomous Region and Subei Mongolian Autonomous County in Gansu Province, 41 county-level units such as Delingha City, Ulan county and Tianjun County in Qinghai Province, 46 counties such as Shiqu County, Ruoergai County and ABA County in Sichuan Province, and 78 counties such as Ritu County, Gaize county and bango County in Tibet, 14 counties including Wuqia County, aktao county and Shache County in Xinjiang Province, and 9 counties including Deqin County, Zhongdian county and Fugong County in Yunnan Province; Variables include County GDP, added value of primary industry, added value of secondary industry, added value of tertiary industry, total industrial output value of Industrial Enterprises above Designated Size, total retail sales of social consumer goods, balance of residents' savings deposits, grain output, total sown area of crops, number of students in ordinary middle schools and land area. The data set can be used to evaluate the social, economic and resource status of the Qinghai Tibet Plateau.
CHEN Yizhong
Taking villages and towns as the basic division unit, the division map of agricultural development in the Tibetan Plateau comprehensively considers climate, topography, vegetation type and coverage, land use type and proportion, distribution of nature reserves, key points of ecological protection and direction of agricultural development, puts forward the zoning scheme of agricultural and animal husbandry regulation for ecological protection in Qinghai Tibet Plateau, and divides the Qinghai Tibet Plateau into 8 areas (3 areas are based on ecological protection) The protection areas are the key limited control areas of agriculture and animal husbandry, 5 moderate development areas of agriculture and 23 small areas, and the zoning is named by the way of protection + development direction of agriculture and animal husbandry. The purpose of the zoning map is to develop agriculture and animal husbandry moderately on the basis of effective ecological protection, which can provide reference information for the protection of ecological security barrier function and sustainable management.
LV Changhe, LIU Yaqun
This dataset is the spatial distribution map of the marshes in the source area of the Yellow River near the Zaling Lake-Eling Lake, covering an area of about 21,000 square kilometers. The data set is classified by the Landsat 8 image through an expert decision tree and corrected by manual visual interpretation. The spatial resolution of the image is 30m, using the WGS 1984 UTM projected coordinate system, and the data format is grid format. The image is divided into five types of land, the land type 1 is “water body”, the land type 2 is “high-cover vegetation”, the land type 3 is “naked land”, and the land type 4 is “low-cover vegetation”, and the land type 5 is For "marsh", low-coverage vegetation and high-coverage vegetation are distinguished by vegetation coverage. The threshold is 0.1 to 0.4 for low-cover vegetation and 0.4 to 1 for high-cover vegetation.
Geomatics Center of Qinghai Province
Based on China's daily meteorological elements data set and National Geographic basic data, the extreme precipitation, extreme temperature, drought intensity, drought frequency and other indicators in Hengduan Mountain area were calculated by using rclimdex, nspei and bilinear interpolation methods. The data set includes basic data set of disaster pregnant environment, basic data set of extreme precipitation index, basic data set of extreme temperature index, basic data set of drought intensity and frequency. The data set can provide a basic index system for regional extreme high temperature, precipitation and drought risk assessment.
SUN Peng
As the roof of the world, the water tower of Asia and the third pole of the world, the Qinghai Tibet Plateau is an important ecological security barrier for China and even Asia. With the rapid development of social economy, human activities have increased significantly, and the impact on the ecological environment is growing. In this paper, eight factors including cultivated land, construction land, National Road, provincial road, railway, expressway, GDP and population density were selected as the threat factors, and the attributes of the threat factors were determined based on the expert scoring method to evaluate the habitat quality of the Qinghai Tibet Plateau, so as to obtain six data sets of the habitat quality of the agricultural and pastoral areas of the Qinghai Tibet Plateau in 1990, 1995, 2000, 2005, 2010 and 2015. The production of habitat quality data sets will help to explore the habitat quality of the Qinghai Tibet Plateau and provide effective support for the government to formulate sustainable development policies of the Qinghai Tibet Plateau.
LIU Shiliang, LIU Yixuan, SUN Yongxiu, LI Mingqi
The natural resources dataset of the Qinghai-Tibetan Plateau covers 215 counties in this area. The observation intervals are 5 years from 2000-2015. The indicators are rainfall, temperature, humidity, population, and land area. The data sources are meteorological station data, regional statistical yearbook, etc., which are expressed by Excel. This data provides a reference for understanding the natural background conditions on the county scale in the Qinghai Tibet Plateau.
FENG Xiaoming
The Three-River-Source National Park with an area of 123,100 km2 and include three sub regions, they are source region of the Yangtze River in the national park, source region of Yellow River in the national park and source region of Lancang River in the national park. The national park is located between longitude 89°50'57" -- 99°14'57", latitude 32°22'36" -- 36°47'53". It accounts for 31.16% of the total area of Three-River-Source region. This data set is generated by digitizing the location map of Three-River-Source national park in the comprehensive planning of Three-River-Source national park. The data include the boundary for the national park. Data format is Shapefile. Arcmap is recommended to open the data.
WANG Xufeng
The data set contains the boundaries of the three source regions of the Yellow River, the Yangtze River and the Lancang River, the boundary of the whole Sanjiangyuan region and the boundaries of the counties within the basin. The observation projects include the boundaries of the three source regions of the Yellow River, the Yangtze River and the Lancang River, the boundary of the whole Sanjiangyuan region and the boundaries of the counties within the basin.
WEI Yanqiang, Establishing Developing and Applying of the Space-Air-Field Integrated Eco-Monitoring and Data Infrastructure of the Three-River-Source National Park
The data set records the administrative divisions of Qinghai Province, and the data are divided according to the administrative divisions of Qinghai Province. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set consists of 9 data tables Administrative divisions of the whole province (end of 2001). Xls Administrative divisions of the whole province (end of 2002). Xls Administrative divisions of the whole province (end of 2003). Xls Provincial administrative divisions (end of 2006). Xls Provincial administrative divisions (end of 2007). Xls Provincial administrative divisions (end of 2008). Xls Provincial administrative divisions (end of 2009). Xls Provincial administrative divisions (end of 2013). Xls Administrative divisions of the whole province (end of 2004). Xls The data table structure is the same. For example, there are five fields in the data table of the provincial administrative divisions (at the end of 2001) Field 1: Region Field 2: land area (km2) Field 3: number of administrative units at county level Field 4: name of county administrative unit (region) Field 5: sub district office
Qinghai Provincial Bureau of Statistics
Based on the vulnerability assessment framework of "exposure sensitivity adaptability", the vulnerability assessment index system of agricultural and pastoral areas in Qinghai Tibet Plateau was constructed. The index system data includes meteorological data, soil data, vegetation data, terrain data and socio-economic data, with a total of 12 data indicators, mainly from the national Qinghai Tibet Plateau scientific data center and the resource and environmental science data center of the Chinese Academy of Sciences. Based on the questionnaire survey of six experts in related fields, the weight of the indicators is determined by using the analytic hierarchy process (AHP). Finally, four 1km grid data are formed involving ecological exposure, sensitivity, adaptability and ecological vulnerability in the agricultural and pastoral areas of the Qinghai Tibet Plateau. The data can provide a reference for the identification of ecological vulnerable areas in the Qinghai Tibet Plateau.
ZHAN Jinyan, TENG Yanmin, LIU Shiliang
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