• 黑河综合遥感联合试验:临泽草地加密观测区土壤水分剖面数据集

    The dataset of soil moisture profile observations (5cm, 10cm, 20cm and 40cm) was obtained in the Linze grassland foci experimental area from May 24 to Jun. 30, 2008. Four points, with various underlying surface and depth in each plot of A, B, C, D and E, were measured by the cutting ring. Data were archived in Excel and Word file. See WATER: Dataset of setting of the sampling plots and stripes in the foci experimental area of Linze station for more information.

    0 2019-05-23

  • 黑河综合遥感联合试验:临泽站加密观测区荒漠观测区C3/C4植被调查数据集

    The dataset of the discrimination of C3/C4 species was obtained by the handheld GPS and the digital camera in the Linze station foci experimental area on Jul. 10, 2008. Data fields included Gps, Longitude, Latitude, Photo_num and Describe (descriptions on C3/C4 vegetation and photos).

    0 2019-05-23

  • 黑河生态水文遥感试验:非均匀下垫面地表蒸散发的多尺度观测试验-通量观测矩阵数据集(2号点涡动相关仪)(2012)

    This dataset contains the flux measurements from site No.2 eddy covariance system (EC) in the flux observation matrix from 3 June to 21 September, 2012. The site (100.35406° E, 38.88695° N) was located in a cropland (maize surface) in Yingke irrigation district, which is near Zhangye, Gansu Province. The elevation is 1559.09 m. The EC was installed at a height of 3.7 m; the sampling rate was 10 Hz. The sonic anemometer faced north, and the separation distance between the sonic anemometer and the CO2/H2O gas analyzer (CSAT3&Li7500) was 0.15 m. Raw data acquired at 10 Hz were processed using the Edire post-processing software (University of Edinburgh, http://www.geos.ed.ac.uk/abs/research/micromet/EdiRe/), including spike detection, lag correction of H2O/CO2 relative to the vertical wind component, sonic virtual temperature correction, coordinate rotation (2-D rotation), corrections for density fluctuation (Webb-Pearman-Leuning correction), and frequency response correction. The EC data were subsequently averaged over 30 min periods. Moreover, the observation data quality was divided into three classes according to the quality assessment method of stationarity (Δst) and the integral turbulent characteristics test (ITC), which was proposed by Foken and Wichura [1996]: class 1 (level 0: Δst<30 and ITC<30), class 2 (level 1: Δst<100 and ITC<100), and class 3 (level 2: Δst>100 and ITC>100), representing high-, medium-, and low-quality data, respectively. In addition to the above processing steps, the half-hourly flux data were screened in a four-step procedure: (1) data from periods of sensor malfunction were rejected; (2) data before or after 1 h of precipitation were rejected; (3) incomplete 30 min data were rejected when the missing data constituted more than 3% of the 30 min raw record; and (4) data were rejected at night when the friction velocity (u*) was less than 0.1 m/s. There were 48 records per day; the missing data were replaced with -6999. Moreover, suspicious data were marked in red. The released data contained the following variables: data/time, wind direction (Wdir, °), wind speed (Wnd, m/s), the standard deviation of the lateral wind (Std_Uy, m/s), virtual temperature (Tv, ℃), H2O mass density (H2O, g/m^3), CO2 mass density (CO2, mg/m^3), friction velocity (ustar, m/s), stability (z/L), sensible heat flux (Hs, W/m^2), latent heat flux (LE, W/m^2), carbon dioxide flux (Fc, mg/ (m^2s)), quality assessment of the sensible heat flux (QA_Hs), quality assessment of the latent heat flux (QA_LE), and quality assessment of the carbon flux (QA_Fc). In this dataset, the time of 0:30 corresponds to the average data for the period between 0:00 and 0:30; the data were stored in *.xlsx format. For more information, please refer to Liu et al. (2016) (for multi-scale observation experiment or sites information), Xu et al. (2013) (for data processing) in the Citation section.

    0 2019-09-15

  • 黑河综合遥感联合试验:Envisat ASAR遥感数据集

    In 2007, 2008 and 2009, ENVISAT ASAR data 179 scenes, covering the whole Heihe River Basin. Among them, there were 63 in 2007, 71 in 2008 and 45 in 2009. Imaging mode and acquisition time are respectively: app can select polarization mode from August 15, 2007 to December 23, 2007, from January 02, 2008 to December 202009-02-15, 2008 to September 06, 2009; imp imaging mode from June 19, 2009 to July 12, 2009; WSM wide mode from January 1, 2007 to December 302008-01-01, 2007 to November 28, 2008, from March 13, 2009 to May 22, 2009. The product level is L1B, which is amplitude data without geometric correction. The ENVISAT ASAR remote sensing data set of Heihe comprehensive remote sensing joint experiment is mainly obtained through the China EU "dragon plan" project (Project No.: 5322 and 5344); the WSM wide model data in 2007 and January 2008 are obtained from Professor Bob Su of ITC; the 8-view app can be purchased from the earth observation and digital earth center of Chinese Academy of Sciences.

    0 2020-03-09

  • 冻土环境对青藏铁路工程建设的影响及工程的环境效应数据集(2002-2004)

    The project “The impact of the frozen soil environment on the construction of the Qinghai-Tibet Railway and the environmental effects of the construction” is part of the “Environmental and Ecological Science in West China” programme supported by the National Natural Science Foundation of China. The person in charge of the project is Wei Ma, a researcher at the Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences. The project ran from January 2002 to December 2004. Data collected in this project included the following: Monitoring data of the active layer in the Beiluhe River Basin (1) Description of the active layer in the Beiluhe River Basin (2) Subsurface moisture data from the Beiluhe River Basin, 2002.9.28-2003.8.10 (Excel file) * Site 1 - Grassland moisture data * Site 2 – Removed turf moisture data * Site 3 - Natural turf moisture data * Site 4 - Gravel moisture data * Site 5 - Insulation moisture data (3) Subsurface temperature data from the Beiluhe River Basin, 0207-0408 Excel file * Temperature data for the ballast surface * Temperature data for insulation materials * Temperature data for a surface without vegetation * Temperature data for a grassland surface * Temperature data for a grit and pebble surface Data on the impact of construction on the ecological environment were obtained at Fenghuoshan, Tuotuohe, and Wudaoliang. Sample survey included plant type, abundance, community coverage, total coverage, aboveground biomass ratio and soil structure. The moisture content at different depths of the soil was detected using a time domain reflectometer (TDR). A set of soil samples was collected at a depth of 0-100 cm at each sample site. An EKKO100 ground-penetrating radar detector was used to continuously sample 1-1.5 km long sections parallel to the road to determine the upper limit depth of the frozen soil. 3. Predicted data: The temperature of the frozen soil at different depths and times was predicted in response to temperature increases of 1 degree and 2 degrees over the next 50 years based on initial surface temperatures of -0.5, -1.5, -2.5, -3.5, and -4.5 degrees. 4. The frozen soil parameters of the Qinghai-Tibet Railway were as follows: location, railway mileage, total mileage (km), frozen soil type mileage, mileage of zones with an average temperature conducive to permafrost, frozen soil with high temperatures and high ice contents, frozen soils with high temperatures and low ice contents, frozen soils with low temperatures and high ice contents, frozen soils with low temperatures and low ice contents, and melting area.

    0 2019-09-14

  • 青藏高原地区MODIS逐日无云积雪产品(2002-2010)

    This data is 2002.07.04-2010.12.31 MODIS daily cloudless snow products in the Tibetan Plateau. Due to the snow and cloud reflection characteristics, the use of optical remote sensing to monitor snow is severely disturbed by the weather. This product is based on the most commonly used cloud removal algorithm, using the MODIS daily snow product and passive microwave data AMSR-E snow water equivalent product, and the daily cloudless snow product in the Tibetan Plateau is developed. The accuracy is relatively high. This product has important value for real-time monitoring of snow cover dynamic changes on the Tibetan Plateau. Projection method: Albers Conical Equal Area Datum: D_Krasovsky_1940 Spatial resolution: 500 m Data format: tif Naming rules: maYYMMDD.tif, where ma represents the data name; YY represents the year (01 represents 2001, 02 represents 2002 ...); MM represents the month (01 represents January, 02 represents February ...); DD represents the day (01 Means 1st, 02 means 2nd ...).

    0 2020-06-08

  • 黑河综合遥感联合试验:排露沟流域加密观测区降雨截留观测数据

    The dataset of precipitation and canopy interception observations was obtained in the Pailugou watershed foci experimental area from Jul. 4 to Sep. 28, 2007, and May 8 to Sep. 27, 2008, respectively. 18 interception slots were set in three plots and the detailed information was as follows: Plot number slot number in the Qinghai spruce forest Ⅰ 1, 2, 3, 4, 5, 6 Ⅱ 7, 8, 9, 10, 11, 12 Ⅲ A, B, C, D, E, F Observation items included controlled rainfall, the forest throughfall, the stem flow and the moss and litter interception barrel throughfall.

    0 2019-05-23

  • 青海省1:10万土地利用数据集(1995)

    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.

    0 2020-06-10

  • 黑河流域1:100万植被类型图(2001)

    The data is the digitization of the Heihe River basin part of the 1:1 million Vegetation Atlas of China, 1:1000, 000 Vegetation Atlas of China is edited by academician Hou Xueyu, a famous vegetation ecologist (Hou Xueyu, 2001). It is jointly compiled by more than 250 experts from 53 units such as research institutes of Chinese Academy of Sciences, relevant ministries and commissions, relevant departments of various provinces and regions, colleges and universities. It is another summative achievement of vegetation ecologists in China over 40 years after the publication of monographs such as vegetation of China Basic map of natural resources and natural conditions of the family. It is based on the rich first-hand information accumulated by vegetation surveys carried out throughout the country over the past half century, and the materials obtained by modern technologies such as aerial remote sensing and satellite images, as well as the latest research achievements in geology, soil science and climatology. It reflects in detail the distribution of vegetation units of 11 vegetation type groups, 796 formations and sub formations of 54 vegetation types, horizontal and vertical zonal distribution laws, and also reflects the actual distribution of more than 2000 dominant species of plants, major crops and cash crops in China, as well as the close relationship between dominant species and soil and ground geology. The atlas is a kind of realistic vegetation map, reflecting the recent quality of vegetation in China.

    0 2020-06-05

  • 黑河流域上游土壤含水量数据

    1. The data set is the soil water content data set of the upper reaches of Heihe River Basin, and the data is the measured data of location points from 2013 to 2014. 2. The infiltration data is measured with ech2o. Including 5 layers of soil moisture content and soil temperature 3. Some instruments lack of data due to insufficient battery life, broken roads, stolen instruments and other reasons

    0 2020-06-03