Pan-third-polar environmental change and green silk road construction

Brief Introduction: Pan-third-polar environmental change and green silk road construction

Number of Datasets: 625

  • The comprehensive dataset of the Tibetan Plateau cryosphere (1997)

    The comprehensive dataset of the Tibetan Plateau cryosphere (1997)

    The contents of this data set are as follows: Ⅰ. Document (specific documents in the data set) Ⅱ. Fgmodel (model data) Ⅲ. Grid DEM, Hillshade (the digital elevation model and hillshade data) Ⅳ. Map (thumbnail) V. Meteoro (meteorological data) 1. Snowdpt (snow depth): (1) Data source: snow depth observation data and passive microwave data; (2) Attribute fields: geocoding, weather station number, weather station name, and cartographic symbols; (3) Main content: snow depth 2. Precitpt (precipitation): (1) Data source: Tibetan Plateau precipitation data; (2) Attribute fields: geocoding, weather station number, weather station name, and cartographic symbols; (3) Monthly average precipitation 3. Temprt (temperature): (1) Data source: Tibetan Plateau temperature data; (2) Attribute fields: geocoding, weather station number, weather station name, and cartographic symbols; (3) Monthly average temperature VI. QZHIGHW (Qinghai-Tibet Highway Data) Ⅶ. Vector two folders: Albers and Geo 1. frozengd (frozen soil type map): (1) Data source: Map of Snow, Ice, and Frozen Ground in China (1: 4000000), Map of Permafrost on the Qinghai-Tibetan Plateau (1:3000000); (2) Attribute fields: geocoding, zone name, annual average ground temperature (°C), permafrost thickness (m), and cartographic symbols; (3) Description of major geographical elements: permafrost and seasonally frozen soil 2. hydrogeo (hydrogeological map): (1) Data source: Geologic Map of China (1: 4000000); (2) Attribute fields: geocoding, hydrogeological classification, hydrogeological subcategories, and cartographic symbols; (3) Major geographical elements: hydrogeological phenomena 3. quadgeo (Quaternary geological map): (1) Data source: Quaternary geological Map of China (1:2500000); (2) Attribute fields: geocoding, sedimentary facies, geological time, sedimentary type, and cartographic symbols; (3) Major geographic elements: Quaternary geological type 4. lake (lake map): (1) Data source: Topographic Map of the Tibetan Plateau (1:4000000); (2) Attribute fields: geocoding, category, and cartographic symbols; (3) Major geographic elements: lake distribution 5. stream (drainage map): (1) Data source: Topographic Map of the Tibetan Plateau (1:4000000); (2) Major geographic elements: river distribution 6. vegetat (vegetation data): (1) Data source: Vegetation Map of China (1:4000000); (2) Attribute fields: geocoding, main category, subcategory, minor subcategory, and cartographic symbols; (3) Major geographical description: vegetation type 7. formap (frozen soil type map) 8. Quatgla (ancient glaciers) 9. station (weather station): (1) Data source: Tibetan Plateau meteorological station coordinate data; (2) Spatial distribution of meteorological stations Ⅷ. borehole (borehole drilling data) Code Description Drilling position Drilling histogram name 211122001 Drilling 1 mileage 1041KM+200M z1 211122002 Drilling 2 mileage 1041KM+800M z2 Data projection: Projection: Albers False_Easting: 0.000000 False_Northing: 0.000000 Central_Meridian: 90.000000 Standard_Parallel_1: 27.30.000000 Standard_Parallel_2: 37.30.000000 Latitude_Of_Origin: 0.000000 Linear Unit: Metre (1.000000) Please refer to the documentation for detailed data properties.

    2020-01-19 20150 12 View Details

  • Long-term serial data of snow area on the Tibetan Plateau (2007-2015)

    Long-term serial data of snow area on the Tibetan Plateau (2007-2015)

    The variation in the duration of snow on the Tibetan Plateau is relatively great, and the high mountainous areas around the plateau are rich in snow and ice resources. Taking full account of the terrain of the Tibetan Plateau and the snow characteristics in the mountains, the data set adopted AVHRR data to gradually realize generating data products for daily, ten-day, and monthly snow cover areas while maintaining the snow classification accuracy. These data included the daily/10-day/monthly snow cover area data for the Tibetan Plateau from 2007 to 2015, the average accuracy of which is 0.92. It can provide reliable data for snow changes during the historical periods of the Tibetan Plateau.

    2020-01-18 689 17 View Details

  • Ice elevation changes for typical glaciers on the QTP V1.0 (2000-2013)

    Ice elevation changes for typical glaciers on the QTP V1.0 (2000-2013)

    The continuous advancement of SAR interferometry technology makes it possible to obtain multitemporal DEMs with high precision in the glacial area. In particular, in 2000, the Shuttle Radar Topography Mission (SRTM) led by NASA provided DEM data covering the area from 56ºS to 60ºN; the TanDEM-X bistatic SAR interferometry system of DLR could provide the global DEM data with high resolution and precision. These high-quality, large-coverage SAR interferometry data, as well as published DEM data products, provided valuable information for using the multitemporal DEMs to detect changes in ice thickness. The temporal coverage of the ice thickness variation data of typical glaciers on the Tibetan Plateau was from 2000 to 2013, covering Puruogangri and the west Qilian Mountains with a spatial resolution of 30 meters. Using TanDEM-X bistatic InSAR data and a C-band SRTM DEM, the differential radar interferometry method was first used to generate a TanDEM-X DEM with high precision. Then, based on the precise registration of DEM, the DEM data obtained in different periods were compared. Lastly, the ice thickness changes were estimated. The format of the data set was GeoTIFF, and each typical glacier ice thickness change was stored in a folder. For details of the data, please refer to the Ice elevation changes for typical glaciers on the Tibetan Plateau - Data Description.

    2020-01-18 599 22 View Details

  • Historical dataset of chemical properties of soil profile in the Balkhash lake area (2010)

    Historical dataset of chemical properties of soil profile in the Balkhash lake area (2010)

    Content of data: the chamical property database of seven sites of soil profiles in Balkhash Lake Basin. Source of data: 2010 national science and technology cooperation project: the impact of climate change on land productivity in central Asia and soil investigation in balkhash lake region. Data quality: The soil profile was stratified and sampled according to soil genetics. The analysis and determination items included: organic matter content, soil total nitrogen, carbon-nitrogen ratio, carbonate content, calcium carbonate content, and cation exchange capacity (Ca \ Mg \ Na \ K \ total), pH value, soil available nutrients (available phosphorus, available potassium and alkaline nitrogen) and so on. Data application prospects: With precise coordinates, historical data can be compared. Note: Sample point 1 and sample point 2 are 20 m away; sample point 3 and sample point 4 are 50 m away.

    2020-01-16 81 0 View Details

  • Hourly meteorological forcing & land surface state dataset of Tibet Plateau with 10 km spatial resolution (2000-2010)

    Hourly meteorological forcing & land surface state dataset of Tibet Plateau with 10 km spatial resolution (2000-2010)

    The near surface atmospheric forcing and surface state data set of the Tibetan Plateau was yielded by WRF model, time range: 2000-2010, space range: 25-40 °N, 75-105 °E, time resolution: hourly, space resolution: 10 km, grid number: 150 * 300. There are 33 variables in total, including 11 near surface atmospheric variables: temperature at 2m height on the ground, specific humidity at 2m height on the ground, surface pressure, latitudinal component of 10m wind field on the ground, longitudinal component of 10m wind field on the ground, proportion of solid precipitation, cumulative cumulus convective precipitation, cumulative grid precipitation, downward shortwave radiation flux at the surface, downward length at the surface Wave radiation flux, cumulative potential evaporation. There are 19 surface state variables: soil temperature in each layer, soil moisture in each layer, liquid water content in each layer, heat flux of snow phase change, soil bottom temperature, surface runoff, underground runoff, vegetation proportion, surface heat flux, snow water equivalent, actual snow thickness, snow density, water in the canopy, surface temperature, albedo, background albedo, lower boundary Soil temperature, upward heat flux (sensible heat flux) at the surface and upward water flux (sensible heat flux) at the surface. There are three other variables: longitude, latitude and planetary boundary layer height.

    2020-01-16 140 0 View Details

  • Bacteria distribution in Tibetan lakes (version 1.0) (2015)

    Bacteria distribution in Tibetan lakes (version 1.0) (2015)

    Microbial diversity data of lakes on the Tibetan Plateau. One hundred and thirty-eight samples were collected from July 1st to July 15th, 2015, from 28 lakes (Bamco, Baima Lake, Bange Salt Lake, Bangong Lake, Bengco, Bieruozeco, Cuoeco, Cuoe (Pingcuo North), Dawaco, Dangqiongco, Dangreyongco, Dongco, Eyacuoqiong, Gongzhuco, Guogenco, Jiarebuco, Mapangyongco, Namco, Nieerco (Salt Lake), Normaco, Pengyanco, Pengco, Qiangyong, Selinco, Wuruco, Wumaco, Zharinanmuco, and Zhaxico). The salinity gradients range from 0.07-118 ppm. The DNA extraction method: The DNA was extracted using an MO BIO PowerSoil DNA kit after the lake water was filtered onto a 0.45 membrane. The 16S rRNA gene fragment amplification primers were 515F (5'-GTGCCAGCMGCCGCGGTAA-3') and 909r (5'-GGACTACHVGGGTWTCTAAT-3'). The sequencing method was Illumina MiSeq PE250, and the raw data were analyzed by Mothur software, including quality filtering and chimera removal. The sequence classification was based on the Silva109 database, and archaea, eukaryotic and unknown source sequences have been removed. OTUs were classified by 97% similarity, and sequences that appear once in the database were then removed. Finally, each sample was resampled to 7,230 sequences/sample. GPS coordinates, evolutionary information, and environmental factors are listed in the data.

    2020-01-16 448 1 View Details

  • Meteorological data of the integrated observation and research station of Ngari for desert environment (2009-2017)

    Meteorological data of the integrated observation and research station of Ngari for desert environment (2009-2017)

    The data set includes meteorological data from the Ngari Desert Observation and Research Station from 2009 to 2017. It includes the following basic meteorological parameters: temperature (1.5 m from the ground, once every half hour, unit: Celsius), relative humidity (1.5 m from the ground, once every half hour, unit: %), wind speed (1.5 m from the ground, once every half hour, unit: m/s), wind direction (1.5 m from the ground, once every half hour, unit: degrees), atmospheric pressure (1.5 m from the ground, once every half hour, unit: hPa), precipitation (once every 24 hours, unit: mm), water vapour pressure (unit: kPa), evaporation (unit: mm), downward shortwave radiation (unit: W/m2), upward shortwave radiation (unit: W/m2), downward longwave radiation (unit: W/m2), upward longwave radiation (unit: W/m2), net radiation (unit: W/m2), surface albedo (unit: %). The temporal resolution of the data is one day. The data were directly downloaded from the Ngari automatic weather station. The precipitation data represent daily precipitation measured by the automatic rain and snow gauge and corrected based on manual observations. The other observation data are the daily mean value of the measurements taken every half hour. Instrument models of different observations: temperature and humidity: HMP45C air temperature and humidity probe; precipitation: T200-B rain and snow gauge sensor; wind speed and direction: Vaisala 05013 wind speed and direction sensor; net radiation: Kipp Zonen NR01 net radiation sensor; atmospheric pressure: Vaisala PTB210 atmospheric pressure sensor; collector model: CR 1000; acquisition interval: 30 minutes. The data table is processed and quality controlled by a particular person based on observation records. Observations and data acquisition are carried out in strict accordance with the instrument operating specifications, and some data with obvious errors are removed when processing the data table.

    2020-01-13 790 37 View Details

  • Aerosol optical property dataset of the Tibetan Plateau by ground-based observation (2009-2016)

    Aerosol optical property dataset of the Tibetan Plateau by ground-based observation (2009-2016)

    The measurement data of the sun spectrophotometer can be directly used to perform inversion on the optical thickness of the non-water vapor channel, Rayleigh scattering, aerosol optical thickness, and moisture content of the atmospheric air column (using the measurement data at 936 nm of the water vapor channel). The aerosol optical property data set of the Tibetan Plateau by ground-based observations was obtained by adopting the Cimel 318 sun photometer, and both the Mt. Qomolangma and Namco stations were involved. The temporal coverage of the data is from 2009 to 2016, and the temporal resolution is one day. The sun photometer has eight observation channels from visible light to near infrared. The center wavelengths are 340, 380, 440, 500, 670, 870, 940 and 1120 nm. The field angle of the instrument is 1.2°, and the sun tracking accuracy is 0.1°. According to the direct solar radiation, the aerosol optical thickness of 6 bands can be obtained, and the estimated accuracy is 0.01 to 0.02. Finally, the AERONET unified inversion algorithm was used to obtain aerosol optical thickness, Angstrom index, particle size spectrum, single scattering albedo, phase function, birefringence index, asymmetry factor, etc.

    2020-01-12 550 6 View Details

  • A permafrost thermal type map on the Tibetan Plateau (2000-2010)

    A permafrost thermal type map on the Tibetan Plateau (2000-2010)

    The past frozen soil map of the Tibetan Plateau was based on a small number of temperature station observations and used a classification system based on continuity. This data set used the geographically weighted regression model (GWR) to synthesize MODIS surface temperature, leaf area index, snow cover ratio and multimodel soil moisture forecast products of the National Meteorological Information Center through spatiotemporal reconstruction. In addition, precipitation observations of more than 40 meteorological stations, the precipitation products of FY2 satellite observations and the multiyear average temperature observation data of 152 meteorological stations from 2000 to 2010 were integrated to simulate the average temperature data of the Tibetan Plateau, and the permafrost thermal condition classification system was used to classify permafrost into several types: Very cold, Cold, Cool, Warm, Very warm, and Likely thawing. The map shows that, after deducting lakes and glaciers, the total area of permafrost on the Tibetan Plateau is approximately 1,071,900 square kilometers. Verification shows that this map has higher accuracy. It can provide support for future planning and design of frozen soil projects and environmental management.

    2020-01-12 569 25 View Details

  • A new map of permafrost distribution on the Tibetan Plateau (2017)

    A new map of permafrost distribution on the Tibetan Plateau (2017)

    The Tibetan Plateau (TP) has the largest areas of permafrost terrain in the mid- and low-latitude regions of the world. Some permafrost distribution maps have been compiled but, due to limited data sources, ambiguous criteria, inadequate validation, and deficiency of high-quality spatial data sets, there is high uncertainty in the mapping of the permafrost distribution on the TP. We generated a new permafrost map based on freezing and thawing indices from modified Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperatures (LSTs)、The temperature at the top of permafrost (TTOP) model was applied to simulate the permafrost distribution , validated this map using various ground-based data sets. The properties of frozen soil include: Seasonally frozen ground、Permafrost、Unfrozen ground. The results provide more detailed information on the permafrost distribution and basic data for use in future research on the Tibetan Plateau permafrost.

    2020-01-12 1175 68 View Details

  • A dataset of area change for the Karuola glacier (1972-2017)

    A dataset of area change for the Karuola glacier (1972-2017)

    The Karuola Glacier of Tibet is located at the junction of Langkazi County, the Shannan Area of the Tibetan Autonomous Region and Jiangzi County of the Shigatse Region. Latitude: 28°54'23.30′′~28°56'50.95′′N, Longitude 90°11′42.21′′~90°09′26.23′′E. It is a continental glacier with an average elevation of 5042 meters. It is the north-south spreading part of the Ningjingangsang peak. Based on the integration of the first glacier inventory data of China from the Cold and Arid Regions Environmental and Engineering Research Institute,Chinese Academy of Sciences, the 1:100,000 inventory data of the Yarlu Zangbu River Basin Glacier from the Sharing Platform for the Earth Systematic Science Data, and Google Earth remote sensing image and field survey data, the dataset was obtained with the help of ArcGIS, ENVI and other software by the following steps: first, the research and development of the data was achieved by band combination, research area clipping, manual visual interpretation and other techniques, and the accuracy of the obtained data was then verified. This dataset includes a total of 25 statistics of vector and area data of Tibet’s Karuola Glacier. It recorded the changes at the borders of Karuola Glacier in the past 45 years and could be used as reference data for the study of glacier and climate changes on the Tibetan Plateau.

    2020-01-12 458 6 View Details

  • Frozen ground map of China based on a Map of the Glaciers, Frozen Ground and Deserts in China (1981-2006)

    Frozen ground map of China based on a Map of the Glaciers, Frozen Ground and Deserts in China (1981-2006)

    These data are a digitization of the frozen soil distribution map of the Map of the Glaciers, Frozen Ground and Deserts in China (1:4,000,000). Considering the unification with the global frozen soil classification system, the permafrost is divided into the following five types: (1) Discontinuous permafrost: continuous coefficient 50%-90% (2) Island permafrost: continuous coefficient <50% (3) Plateau discontinuous permafrost: continuous coefficient 50%-90% (4) Plateau island permafrost: continuous coefficient 50%-90% (5) Mountain permafrost The compilation basis of the frozen soil map includes (1) the measured field survey data and exploration of frozen soil; (2) aerial image and satellite image interpretation; (3) TOPO30 1-km resolution ground elevation data; and (4) and temperature and ground temperature data. The distribution of frozen soil on the Tibetan Plateau adopted the research results of Zhuotong Nan et al. (2002). Using the average annual temperature data of 76 boreholes along the Qinghai-Tibet Highway, a statistical regression analysis was performed to obtain the relation between annual mean ground temperature, latitude and elevation. Based on the relation combined with GTOPO30 elevation data (global 1-km digital elevation model data developed by the Earth Resources Observation and Technology Center of the U.S Geological Survey), the annual average ground temperature distribution over the entire Tibetan Plateau was simulated. Taking the annual average ground temperature of 0.5 °C as the boundary between permafrost and seasonal frozen soil and the Map of Snow Ice and Frozen Ground in China (1:4,000,000) (Yafeng Shi, et al., 1988) as a reference, the boundary between the plateau discontinuous permafrost and plateau island permafrost was determined. In addition, taking the Distributions Map of Permafrost in Daxiao Hinganling Northeast China (Dongxin Guo, et al. 1981), the Distribution Map of Permafrost and Ground Ice in Circum-Arctic (Brown et al. 1997) and the latest field data as references, the permafrost boundary of northeast China has been revised; the mountain permafrost boundary in the northwest mostly adopted the boundary delineated in the Map of Snow Ice and Frozen Ground in China (1:4,000,000) (Yafeng Shi, et al., 1988). According to this data set, permafrost area in China is approximately 1.75×106 km2, accounting for 18.25% of the territory of China, among which the mountain permafrost area is 0.29×106 km2, which accounts for 3.03% of the territory of China. For more information, please refer to the Map of the Glaciers, Frozen Ground and Deserts in China (1:4,000,000) specification (Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, 2006).

    2020-01-11 14504 13 View Details

  • Meteorological observation data from the integrated observation and research station of the alpine environment in Southeast Tibet (2007-2017)

    Meteorological observation data from the integrated observation and research station of the alpine environment in Southeast Tibet (2007-2017)

    This data set includes daily average data of atmospheric temperature, relative humidity, precipitation, wind speed, wind direction, net radiance, and atmospheric pressure from 1 January 2007 to 31 December 2016 derived from the Integrated Observation and Research Station of the Alpine Environment in Southeast Tibet. The data set has been used by students and researchers in the fields of meteorology, atmospheric environment and ecological research. The units of the various meteorological elements are as follows: temperature °C; precipitation mm; relative humidity %; wind speed m/s; wind direction °; net radiance W/m2; pressure hPa; and particulate matter with aerodynamic diameter less than 2.5 μm μg/m3. All the data are the daily averages calculated from the raw observations. Observations and data collection were carried out in strict accordance with the instrument operating specifications and the guidelines published in relevant academic journals; data with obvious errors were eliminated during processing, and null values were used to represent the missing data. In 2015, due to issues related to the age of the observation probe at the station, only the wind speed data for the last 8 months were retained.

    2020-01-10 597 28 View Details

  • Data on soil temperature, humidity and carbon Flux obtained from a station in southeast Tibet (2007-2017)

    Data on soil temperature, humidity and carbon Flux obtained from a station in southeast Tibet (2007-2017)

    This data set includes daily average data on soil temperature, humidity and carbon flux obtained from a station in Southeast Tibet from 2007 to December 2016. The data collection site is the atmospheric environment observation site of the Integrated Observation and Research Station of the Alpine Environment in Southeast Tibet, which is run by the Chinese Academy of Sciences. The site is located at longitude 94°44'18", latitude 29°45'56" and is at an elevation of 3326 m. The observation instrument models are as follows: Soil temperature: Campbell Co 107; Soil humidity: Campbell Co CS616; Carbon flux: Collector model: C3000, Measurement interval: 10 seconds; The observations and data collection were performed in strict accordance with the instrument operating specifications, and the data have been published in relevant academic journals. Data with obvious errors were removed, and missing data were replaced with null values. Observation of the soil thermal flux was stopped in 2013. In 2015, due to damage to the station probe, soil temperature and humidity data were recorded only for the first two months, the probe was repaired in April 2016.

    2020-01-10 399 17 View Details

  • Water level and water temperature data for Ranwu Lake in Southeast Tibet (2009-2017)

    Water level and water temperature data for Ranwu Lake in Southeast Tibet (2009-2017)

    This data set contains the daily values of water temperature and water level change in Ranwu Lake in Tibet from May 15, 2009, to December 31, 2016. Observation instrument model: an automatic HOBO water level and temperature logger U20-001-01; acquisition time: 30 minutes. The data were collected automatically. The observations and data collection were performed in strict accordance with the instrument operating specifications, and the data have been published in relevant academic journals. Data with obvious errors were removed, and the missing data were replaced by null values. Data collection location: Ranwu Lake, southeast Tibet Middle lake outlet: longitude: 96°46'16"; latitude: 29°29'28"; elevation: 3928 m. Lower Lake outlet: longitude: 96°38'52"; latitude: 29°28'52"; elevation: 3923 m. Laigu upper Lake: longitude: 94°49'49"; latitude: 29°18'07"; elevation: 4025 m. This data contains fileds as follows: Field 1: Site Number Data type: Alphanumeric characters (50) Field 2: Time Data type: Date type Field 3: Water temperature, °C Data type: Double-precision floating-point format Field 4: Relative water level, cm Data type: Double-precision floating-point format

    2020-01-10 418 13 View Details

  • Shergyla Mountain meteorological data (2005-2017)

    Shergyla Mountain meteorological data (2005-2017)

    Shergyla Mountain meteorological data, Record the surface near Linzhi(1.2-1.5m) conventional meteorological observation.The dataset records the meteorological data at the eastern slope of Shergyla Mountain from 2005 to 2016, and North-facing slope from 2005 to 2012.Including daily average data of temperature, relative humidity, precipitation. Data collected near the eastern slope timberline of Shergyla Mountain, Latitude:29°39′25.2″N; Longitude:94°42′25.62″E; Altitude:4390m, and collected near the north-facing slope of Shergyla Mountain, Latitude:29°35′50.9″N; Longitude:94°36′42.7″E; Altitude:4390m. Collector: Campbell Co CR1000. Collection time interval:30min. Digital automatic data collection, daily average value of artificial calculation. It includes the following basic meteorological parameters: North-facing slope data: Wind speed,Unit m/s Temperature,Unit ℃ Relative Humidity,Unit % Atmospheric pressure,Unit hPa Global radiation,Unit w/m2 Soil heat flux,Unit w/m2 Soil temperature,Unit ℃ Soil moisture,Unit % Precipitation,Unit mm Thickness of snow, Unit cm Ecology station data: Temperature,Unit ℃ Relative Humidity,Unit % Atmospheric pressure,Unit hPa Wind speed,Unit m/s Precipitation,Unit mm Snow Depth,Unit cm Radiation,Unit w/m2 Soil moisture content,Unit % Soil heat flux,Unit w/m2

    2020-01-10 434 38 View Details

  • Dataset of high-resolution (3 hour, 10 km) global surface solar radiation (1983-2017)

    Dataset of high-resolution (3 hour, 10 km) global surface solar radiation (1983-2017)

    The dataset is a 34-year (1983.7-2017.6) high-resolution (3 h, 10 km) global SSR (surface solar radiation) dataset, which can be used for hydrological modeling, land surface modeling and engineering application. The dataset was produced based on ISCCP-HXG cloud products, ERA5 reanalysis data, and MODIS aerosol and albedo products with an improved physical parameterization scheme. Validation and comparisons with other global satellite radiation products indicate that our SSR estimates were generally better than those of the ISCCP flux dataset (ISCCP-FD), the global energy and water cycle experiment surface radiation budget (GEWEX-SRB), and the Earth's Radiant Energy System (CERES). This SSR dataset will contribute to the land-surface process simulations and the photovoltaic applications in the future.

    2020-01-10 3819 219 View Details

  • Long-term surface soil freeze-thaw states dataset of China using the dual-index algorithm (1978-2015)

    Long-term surface soil freeze-thaw states dataset of China using the dual-index algorithm (1978-2015)

    This dataset uses daily temperature data from SMMR (1978-1987), SSM/I (1987-2009) and SSMIS (2009-2015). It is generated by the dual-index (TB, 37v, SG) freeze-thaw discrimination algorithm. The classification results include the frozen surface, the thawed surface, the deserts and water bodies. The data coverage is the main part of China’s mainland, with a spatial resolution of 25.067525 km via the EASE-Grid projection method, and it is stored in ASCIIGRID format. All the ASCII files in this data set can be opened directly with a text program such as Notepad. Except for the head file, the body content is numerically characterized by the freeze/thaw status of the surface soil: 1 for frozen, 2 for thawed, 3 for desert, and 4 for precipitation. If you want to use the icon for display, we recommend using the ArcView + 3D or Spatial Analyst extension module for reading; in the process of reading, a grid format file will be generated, and the displayed grid file is the graphical expression of the ASCII file. The read method comprises the following. [1] Add the 3D or Spatial Analyst extension module to the ArcView software and then create a new View. [2] Activate View, click File menu, and select the Import Data Source option. When the Import Data Source selection box pops up, select ASCII Raster in the Select import file type box. When the dialog box for selecting the source ASCII file automatically pops up, click to find any ASCII file in the data set, and then press OK. [3] Type the name of the Grid file in the Output Grid dialog box (it is recommended that a meaningful file name is used for later viewing) and click the path to store the Grid file, press OK again, and then press Yes (to select integer data) and Yes (to put the generated grid file into the current view). The generated files can be edited according to the Grid file standard. This completes the process of displaying an ASCII file into a Grid file. [4] In the batch processing, the ASCIGRID command of ARCINFO can be used to write AML files, and then use the Run command to complete the process in the Grid module: Usage: ASCIIGRID <in_ascii_file> <out_grid> {INT | FLOAT}. The production of this data is supported by the following Natural Science Foundation Projects: Environmental and Ecological Science Data Center of West China (90502010), Land Data Assimilation System of West China (90202014) and Active and Passive Microwave Radiation Transmission Simulation and Radiation Scattering Characteristics of the Frozen Soil (41071226).

    2020-01-09 6581 99 View Details

  • Geomorphological map of Nima and Lunpola Basins in Tibetan Plateau

    Geomorphological map of Nima and Lunpola Basins in Tibetan Plateau

    This data set comprises pictures of geological sections and landscape of Nima Basin and Lunpola Basin in the north of Tibetan Plateau which produced on achievement of geological survey in these years. The process of section pictures drawing comprises: measurement of different stratas by hand; identify and description of stratas by experienced geological researcher; picture production with software, based on information collected above. Landscape pictures were drew from satellite maps as base map, then added texts with software. All the pictures are clear, detailed and comprehensive. They are very critical for research on geology, geomorphology of the important localities in the north of Tibetan Plateau, such as Nima Basin and Lunpola Basin, and necessary for paleo-altimetry and uplift of Tibetan Plateau.

    2019-12-18 168 0 View Details

  • Water resources data of the Qinghai Tibet Plateau (1990-2010)

    Water resources data of the Qinghai Tibet Plateau (1990-2010)

    This data set is the water resources data of the Qinghai Tibet Plateau from 1990 to 2010, which is the sum of renewable surface and groundwater resources. The data is in vector format and the spatial resolution is in the scale of prefecture level administrative units. The data is obtained by checking the results of VIC (variable injection capacity) hydrological model. The simulated water resources are the sum of the surface runoff and underground runoff in the output results of hydrological simulation. The simulation results are verified by comparing with the runoff data of the measured stations. According to the statistics of water resources at the provincial level in China water resources bulletin, a correction coefficient α is introduced at the provincial level, so that the product of water resources and α in the hydrological model simulation province is equal to the statistics of water resources. Then the amount of water resources in the administrative unit is the product of the total amount of water resources and α.

    2019-12-06 204 7 View Details