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
Taking the villages or towns as the basic division unit, taking into account the forest topography (elevation, slope), vegetation type and coverage, land use status and agricultural utilization type, distribution of natural reserves, key points of ecological protection and agricultural development direction, the preliminary scheme of the agricultural and animal husbandry regulation and Control Division of the ecological protection on the Qinghai Tibet Plateau is proposed, which divides the Qinghai Tibet Plateau into 8 regions (3 regions With ecological protection as the key agricultural and animal husbandry limited control area, 5 agricultural moderate development areas) and 23 residential areas, the way of protection + agricultural and animal husbandry development direction is adopted in the naming of zones. Based on the effective protection of ecology and the moderate development of agriculture and animal husbandry in the Qinghai Tibet Plateau, the map can provide reference information for the protection of ecological security barrier function and sustainable management.
LV Changhe, LIU Yaqun
The data set analyzes the spatial and temporal distribution, impact and loss of typical global flood disasters from 2018 to 2019. In 2018, there were 109 flood disasters in the world, with a death toll of 1995. The total number of people affected was 12.62 million. The direct economic loss was about 4.5 billion US dollars, which was at a low level in the past 30 years. The number of global flood incidents in 2018 was higher in the first half of the year than in the second half of the year, and the frequency of occurrence was higher from May to July. Therefore, based on three typical disaster events such as the hurricane flood in Florence in the United States in 2018, the flooding of the Niger River in Nigeria in 2018, and the Shouguang flood in Shandong Province in 2018, the disaster background, hazard factors, and disaster situation were analyzed. .
JIANG Zijie, JIANG Weiguo, WU Jianjun, ZHOU Hongmin
This data is originated from the 1:100,000 national basic geographic database, which was open freely for public by the National Basic Geographic Information Center in November 2017. The boundary of the Qinghai-Tibet Plateau was spliced and clipped as a whole, so as to facilitate the study on the Qinghai-Tibet plateau. This data set is the 1:100,000 administrative boundaries of the qinghai-tibet plateau, including National_Tibet_line、 Province_Tibet、City_Tibet、County_Tibet_poly and County_Tibet_line. Administrative boundary layer (County_Tibet_poly) property name and definition: Item Properties Describe Example PAC Administrative division code 513230 NAME The name of the County line name Administrative boundary layer (BOUL) attribute name and definition: Item Properties Describe Example GB classification code 630200 Administrative boundary layer (County_Tibet_line) attribute item meaning: Item Properties Describe Example GB 630200 Provincial boundary GB 640200 Prefectural, municipal and state administrative boundaries GB 650201 county administrative boundaries (determined)
National Basic Geographic Information Center
This dataset contains monthly and daily 0.01°×0.01° (2018) LST products in Qilian Mountain Area. The dataset was produced based on MYD21A1 LST products at a resolution of 0.01° along with some auxiliary datasets. The auxiliary datasets include Lat/Lon and the Julian Day information. MYD21A1 is the official LST product of MODIS, and the data is divided into day and night, using TES algorithm. Download URL: https://urs.earthdata.nasa.gov.
LI Hua
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 is the boundary vector data of county-level administrative units in Tibetan Plateau in 2015. The data is in Shapefile format and includes provincial administrative units such as Tibet Autonomous Region, Qinghai Province, Gansu Province, Yunnan Province, Xinjiang Uygur Autonomous Region, and Sichuan Province. The county-level administrative unit boundary within the plateau can be used for the geographical background research of the urbanization and ecological environment interaction stress of the Qinghai-Tibet Plateau. It is the basic geographic data for the statistics of the urbanization indicators of the county-level units of the Qinghai-Tibet Plateau. The data is obtained by means of data capture and collected through the administrative interface data acquisition API interface provided by the high-tech map. The data set uses the geographic coordinate system of WGS84.
DU Yunyan
Antarctic administrative boundary datasets consist of the properties of the state boundaries of the Antarctic states (properties properties), and the corresponding names and types of those properties :(CITY_POP), (ENG_NAME), (CNTRY_NAME), (TYPE), (CNTRY_CODE), (YEAR). The data comes from the 1:100,000 ADC_WorldMap global data set，The data through topology, warehousing and other data quality inspection，Data through the topology, into the library，It's comprehensive, up-to-date and seamless geodigital data. The world map coordinate system is latitude and longitude, WGS84 datum surface，Antarctic specific projection parameters（South_Pole_Stereographic）.
ADC WorldMap
This dataset is the boundary vector data of the prefecture-level administrative units in the Qinghai-Tibet Plateau in 2015. The data is in the Shapefile format and includes provincial-level administrative units such as the Tibet Autonomous Region, Qinghai Province, Gansu Province, Yunnan Province, and Xinjiang Uygur Autonomous Region in the Qinghai-Tibet Plateau. The 38 prefecture-level administrative units can be used for the geographical background research of the urbanization and ecological environment interaction stress of the Qinghai-Tibet Plateau. It is the basic geographic data for the statistics of urbanization indicators such as social, economic and population levels of the Qinghai-Tibet Plateau. The data is obtained by means of data capture and collected through the administrative interface data acquisition API interface provided by the high-tech map. The data set uses the geographic coordinate system of WGS84.
DU Yunyan
Arctic administrative boundary data sets include Arctic_National, Arctic_Provincial, and Arctic_Prefecture vector spatial data sets of arcti-bound countries and Its corresponding name, TYPE related attribute data :(LOCAL_NAME), (ENG_NAME), (CNTRY_NAME), (TYPE), (CNTRY_CODE), (CONTINENT) The data comes from the 1:1,000,000 ADC_WorldMap global data set, which is a comprehensive, up-to-date and seamless geographic digital data. The world map coordinate system is latitude and longitude, WGS84 datum surface, and the arctic data set is the special projection parameter for the arctic (North_Pole_Stereographic).
ADC WorldMap
This dataset is the boundary vector data of the provincial-level administrative units in the Qinghai-Tibet Plateau in 2015. The data is in the Shapefile format and includes provincial administrative units such as Tibet Autonomous Region, Qinghai Province, Gansu Province, Yunnan Province, Xinjiang Uygur Autonomous Region, and Sichuan Province. The administrative boundary within the plateau can be used for the geographical background research of the urbanization and ecological environment interaction stress of the Qinghai-Tibet Plateau. It is the basic geographic data for the statistics of the urbanization indicators of the provincial, forest, and population sectors of the Qinghai-Tibet Plateau. The data is obtained by means of data capture and collected through the administrative interface data acquisition API interface provided by the high-tech map. The data set uses the geographic coordinate system of WGS84.
DU Yunyan
The two regions of North Pole are defined by the Arctic Monitoring and Assessment Programme (AMAP) working group and Arctic Human Development Report (AHDR). The AMAP Arctic’s geographical coverage extends from the High Arctic to the sub Arctic areas of Canada, the Kingdom of Denmark (Greenland and the Faroe Islands), Finland, Iceland, Norway, the Russian Federation, Sweden and the United States, including associated marine areas. The AHDR Arctic encompasses all of Alaska, Canada North of 60°N together with northern Quebec and Labrador, all of Greenland, the Faroe Islands, and Iceland, and the northernmost counties of Norway, Sweden and Finland. The situation in Russia is harder to describe in simple terms. The area included, as demarcated by demographers, encompasses the Murmansk Oblast, the Nenets, YamaloNenets, Taimyr, and Chukotka autonomus okrugs, Vorkuta City in the Komi Republic, Norilsk and Igsrka in Krasnoyarsky Kray, and those parts of the Sakha Republic whose boundaries lie closest to the Arctic Circle.
Arctic Monitoring And Assessment Programme
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
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.
This data set is the concentrations of atmospheric and water POPs in Nam Co, including time series of gas phase OCP, PCBs, PAHs and particulate PAHs in the atmosphere; dissolve and particulate POPs in water. An active air sampler (AAS) was deployed on the roof of Nam Co Monitoring and Research Station for Multisphere Interactions (NCMORS) and the air monitoring was conducted for two consecutive years from September 2012 to September 2014. The flow rate of AAS was 60 L min-1 and the air samples were collected every 2 weeks with a volume of approximately 600 m3 for each sample. The air stream passes first through glass fiber filters (GFFs 0.7 μm, Whatman) to collect the total suspended particulates (TSP) and then through polyurethane foam (PUF, 7.5×6 cm diameter) to retain the POPs in gas phase. Fifteen sites around the Nam Co Lake (surface lake water, 0–1 m depth) were selected to obtain the spatial distribution of POPs in lake water. The water samples (200 L) were filtered with GFFs to obtain the total suspended particulate matter (SPM), and then pumped through an XAD-2 resin column to collect the dissolved phase compounds. 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 and PCBs and a DB-5MS column (60 m ×0.25mm, film thickness 0.25 μm) was used for PAHs. Field blanks and procedural blanks were prepared. The recoveries ranged from 64% to 112% for OCPs, and 65% to 92% forPAHs. The reported concentrations were not corrected for recoveries.
WANG Xiaoping
Land use data of Dushanbe, with a resolution of 30 meters, was in the form of TIF and the time was 1990.03.03 and 2018.03.16, respectively.Data source GLC, the raw data of its global land cover data comes from Envisat satellite and is captured by MERIS (Medium Resolution Imaging Spectrometer) sensor.There are currently two issues, GlobCover (Global Land Cover Map) and GlobCover (Global Land Cover Product).
ESA Glob Cover, MA Haitao, HUANG Jinchuan
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 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
Land use data of Bishkek, with a resolution of 30 meters, was in the form of TIF and the time was 1990.03.30 and 2018.04.12, respectively.Data source GLC, the raw data of its global land cover data comes from Envisat satellite and is captured by MERIS (Medium Resolution Imaging Spectrometer) sensor.There are currently two issues, GlobCover (Global Land Cover Map) and GlobCover (Global Land Cover Product).
ESA Glob Cover, HUANG Jinchuan, MA Haitao
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