Typical case dataset of major global flood disasters (2018.01-2018.12)
  • 2019-09-30
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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. .

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Natural places names dataset at 1:250,000 in Sanjiangyuan Region (2015)
  • 2019-09-15
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This data originates from the National Geographic Information Resources Catalogue Service System, which was provided free to the public by the National Basic Geographic Information Center in November 2017. We have spliced and cut the source of the three rivers as a whole, so as to facilitate the use of the study of the source area of the three rivers. The data trend is 2015. This data set includes 1:250,000 natural place names (AANP) in Sanjiangyuan area, including traffic element names, memorial sites and historic sites, mountain names, water system names, marine geographical names, natural geographical names, etc. Natural Place Name Data (AANP) Attribute Item Names and Definitions: Attribute Item Description Fill in Example NAME Name Ramsay Laboniwa PINYIN Chinese Pinyin Lamusailabaoniwa CLASS Toponymic Classification Code HB

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Basic geographic dataset of resources and environment in Central and Western Asia Region
  • 2019-09-15
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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.

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Surface DEM for typical glaciers on the Tibetan Plateau (Version 1.0) (2003)
  • 2019-09-15
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The DEMs of the typical glaciers on the Tibetan Plateau were provided by the bistatic InSAR method. The data were collected on November 21, 2013. It covered Puruogangri and west Qilian Mountains with a spatial resolution of 10 meters, and an elevation accuracy of 0.8 m which met the requirements of national 1:10 000 topographic mapping. Considering the characteristics of the bistatic InSAR in terms of imaging geometry and phase unwrapping, based on the TanDEM-X bistatic InSAR data, and adopting the improved SAR interference processing method, the surface DEMs of the two typical glaciers above were generated with high resolution and precision. The data set was in GeoTIFF format, and each typical glacial DEM was stored in a folder. For details of the data, please refer to the Surface DEMs for typical glaciers on the Tibetan Plateau - Data Description.

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Digital elevation model of China (1KM)
  • 2019-09-15
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DEM is the English abbreviation of Digital Elevation Model, which is the important original data of watershed topography and feature recognition.DEM is based on the principle that the watershed is divided into cells of m rows and n columns, the average elevation of each quadrilateral is calculated, and then the elevation is stored in a two-dimensional matrix.Since DEM data can reflect local topographic features with a certain resolution, a large amount of surface morphology information can be extracted through DEM, which includes slope, slope direction and relationship between cells of watershed grid cells, etc..At the same time, the surface flow path, river network and watershed boundary can be determined according to certain algorithm.Therefore, to extract watershed features from DEM, a good watershed structure pattern is the premise and key of the design algorithm. Elevation data map 1km data formed according to 1:250,000 contour lines and elevation points in China, including DEM, hillshade, Slope and Aspect maps. Data set projection: Two projection methods: Equal Area projection Albers Conical Equal Area (105, 25, 47) Geodetic coordinates WGS84 coordinate system

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The places names dataset at 1:250,000 in Sanjiangyuan region (2015)
  • 2019-09-15
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This data comes from the National Geographic Information Resources Catalogue Service System, which was provided free to the public by the National Basic Geographic Information Center in November 2017. We have spliced and cut the source of the three rivers as a whole, so as to facilitate the use of the study of the source area of the three rivers. The data trend is 2015. This data set includes 1:250,000 residential place names (AANP) in Sanjiangyuan area, including administrative place names at all levels and urban and rural residential place names. Names and Definitions of Attribute Items of Residential Place Name Data (AANP): Attribute Item Description Fill in Example NAME Name Quanqu Village PINYIN Chinese Pinyin Quanqucun CLASS Geographical Name Classification Code AK GNID Place Name Code 632524000000 XZNAME Township Name Ziketan Township

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The administrative divisions in Tibet Autonomous Region (1992-2016)
  • 2019-09-15
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The data set records the Chinese name, English name and the affiliation between the districts and counties in Tibet. The data were derived from the Tibet Society and Economics Statistical Yearbook and the Tibet Statistical Yearbook. The accuracy of the data is consistent with that of the statistical yearbook. This data set contains two tables: Table 1: The table of administrative divisions in Tibet contains 5 fields. Field 1: Regions Interpretation: Chinese names of the regions Field 2: English names of the regions Interpretation: English names of the regions Field 3: Districts and counties Interpretation: Chinese names of the districts and counties Field 4: English names of the districts and counties Interpretation: English names of the districts and counties Field 5: Land area Unit: square kilometers Table 2: The table of division changes of each county contains 5 fields. Field 1: Districts and counties Field 2: Year Field 3: Area Unit: square kilometers Field 4: Number of townships Field 5: Number of Village Committees

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Dataset of concentrations of atmospheric and water POPs in Nam Co (2012-2014)
  • 2019-09-15
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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.

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The digital elevation model of the Tibetan Plateau (2000)
  • 2019-09-15
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This data set is a digital elevation model of the Tibetan Plateau and can be used to assist in analysis and research of basic geographic information for the Tibetan Plateau. The raw data were the Shuttle Radar Topography Mission (SRTM) data, which were provided by Global Land Cover Network (GLCN), and the raw data were framing data , using the WGS84 coordinate system, including latitude and longitude, with a spatial resolution of 3″. After the mosaic processing, the Nodata (null data) generated in the mosaic process were interpolated and filled. After filling, the projection conversion process was performed to generate data as Albers equal area conical projection. After the conversion projection, the spatial resolution of the data was 90 m. Finally, the boundary of the Tibetan Plateau was used for cutting to obtain DEM data. This data table has two fields. Field 1: value Data type: long integer Interpretation: altitude elevation Unit: m Field 2: count Data type: long integer Interpretation: The number of map spots corresponding to the altitude elevation Data accuracy: spatial resolution: 90 m

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