• 天山北麓诸河流域水库分布数据集(2000)

    The data is the reservoir distribution dataset of the north slope of Tianshan River Basin, which is comprehensively prepared by using topographic map and remote sensing image. The scale is 250000, and the projection is latitude and longitude. The data includes spatial data and attribute data, and the attribute field is Name (reservoir name), reflecting the reservoir distribution status of River Basin in the northern foot of Tianshan Mountain around 2000.

    0 2020-06-01

  • 青藏高原积雪覆盖数据集——多源融合算法(2008-2010)

    This dataset is the snow cover dataset based on the MODIS fractional snow cover mapping algorithm Coupled Regional Approach (CRA). The CRA algorithm mainly consists of three parts. (1) First, the N-FINDR (Volume Iterative Approach) and OSP (Orthogonal Subspace Projection) are used to automatically extract the endmember according to the settings (extracting 30 end endmembers). (2) On the basis of automatic extraction, combined with the IGBG land cover type map, six types of endmembers of snow, vegetation, cloud, soil, rock and water are selected by the manual screening method, and an annual spectrum database is established according to the 2009 image. There are 3 spectra in the early, middle and late months and 36 spectra a year. (3) The established spectral database is used as a priori knowledge, and based on prior knowledge, the fully constrained linear unmixing method (FCLS) for subpixel decomposition is used to obtain the fractional snow cover products. The NDSI ratio algorithm with improved topographic effect is used to obtain the snow cover area, the spatiotemporal data are then interpolated, and, finally, the multisource data fusion with the AMSR-E microwave snow depth product is undertaken. The dataset adopts a latitude and longitude (Geographic) projection method. The datum is WGS84, and the spatial resolution is 0.005°. It provides the daily cloudless snow cover area map of the Tibetan Plateau from 2008 to 2010. The data set is stored by year and consists of 3 folders from 2008 to 2010. Each folder contains the classification results of the daily snow cover of the current year. It is a tif file with the naming rule YYYY***.tif, in which YYYY represents the year (2008-2010), and *** represents the day (001~365/ 366). It can be opened directly with ARCGIS or ENVI.

    0 2019-09-15

  • 黑河流域不同荒漠类型植被年生态调查资料(2013)

    At the end of September and the beginning of October, 2013, desert plants in typical areas of heihe basin stopped their growth period to conduct year-end ecological survey. There are altogether 8 survey and observation fields, which are: piedmont desert, piedmont gobi, middle reaches desert, middle reaches gobi, middle reaches desert, lower reaches desert, lower reaches gobi and lower reaches desert, with a size of 40m×40m. Three 20m×20m large quadrats were fixed in each observation field, named S1, S2 and S3, and regular shrub surveys were conducted.Each large quadrat was fixed with 4 5m x 5m small quadrats, named A, B, C, D, for the herbal survey.

    0 2020-03-15

  • 南极先锋植物覆盖分类数据(2017-2018)

    The Antarctic Peninsula is also called "Palmer peninsula" or "Graham land". Located in the southwest polar continent, it is the largest peninsula in the Antarctic continent and the farthest peninsula extending northward into the ocean (63 ° south latitude), bordering the Weddell Sea and berengske sea in the East and West. The Antarctic Peninsula is known as the "tropics" of Antarctica. This is a typical sub polar marine climate. Compared with the Antarctic continent, it is one of the warmest and wettest regions in Antarctica. There are a small number of pioneer plants distributed on the islands in the marginal area, mainly bryophytes and lichens. The plant abundance data products of Antarctic Peninsula and its surrounding areas are matched with remote sensing images through measured spectra, and the end element spectra of moss, lichen, rock, sea and snow are extracted with pure pixel PPI. The linear mixture model (LMM) is applied to calculate. The vegetation coverage of Fildes Peninsula is obtained according to the linear relationship between the vegetation coverage and the abundance.

    0 2019-10-26

  • 荒漠植物群落地上和地下生物量及分布特征调查资料(2014)

    In the previous project, three different types of desert investigation and observation sites in the lower reaches of Heihe River were set up. Different kinds of desert plants with the same average growth and size as the observation site were selected for the above ground biomass and underground biomass total root survey. The dry weight was the dry weight at 80 ℃, and the root shoot ratio was the dry weight ratio of the underground biomass to the aboveground biomass. Species: Elaeagnus angustifolia, red sand, black fruit wolfberry, bubble thorn, bitter beans, Peganum, Tamarix and so on.

    0 2020-06-01

  • 黑河流域大满灌区三次灌水农田及周边土壤剖面含水率数据(2013)

    According to the characteristics of the selected field and its surrounding areas, one Trime pipe was arranged in the corn field, and three Trime pipes were arranged in the direction perpendicular to the field path. When the soil moisture content was monitored in the vertical direction of TDR, it was monitored downward in every 10cm.It is located in the farmland of daman irrigated area. The data include the soil moisture content of the farmland and its surrounding areas (TDR monitoring) after three irrigation of the selected farmland in yingke irrigated area, which is encrypted and monitored every 3 hours within 24 hours, 3 groups every day for 5 days, 2 groups every day for 5-10 days, and 1 group every day for 10-15 days.

    0 2020-03-10

  • 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(1号点自动气象站)

    This dataset contains the automatic weather station (AWS) measurements from site No.1 in the flux observation matrix from 10 June to 17 September, 2012. The site (100.3582° E, 38.8932° N) was located in a cropland (vegetable surface) in the Yingke irrigation district, which is near Zhangye, Gansu Province. The elevation is 1552.75 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity (HMP155; 5 m, towards north), air pressure (PTB110; 2 m), rain gauge (TR525M; 10 m), wind speed and direction (03002; 10 m, towards north), a four-component radiometer (CNR4; 6 m, towards south), two infrared temperature sensors (SI-111; 6 m, vertically downward), soil temperature profile (109ss-L; 0, -0.02, -0.04, -0.1, -0.2, -0.4, -0.6, and -1.0 m), soil moisture profile (SM300; -0.02, -0.04, -0.1, -0.2, -0.4, -0.6, and -1.0 m), and soil heat flux (HFP01; 3 duplicates with one below the vegetation and the other between plants, 0.06 m). One of the infrared temperature sensors (IRT_2) was adjusted to a zenith angle of 50° after 6 August. The observations included the following: air temperature and humidity (Ta_5 m and RH_5 m) (℃ and %, respectively), air pressure (press, hpa), precipitation (rain, mm), wind speed (Ws_10 m, m/s), wind direction (WD_10 m, °), four-component radiation (DR, incoming shortwave radiation; UR, outgoing shortwave radiation; DLR_Cor, incoming longwave radiation; ULR_Cor, outgoing longwave radiation; Rn, net radiation; W/m^2), infrared temperature (IRT_1 and IR_2, ℃), soil heat flux (Gs_1, below the vegetation; Gs_2 and Gs_3, W/m^2), soil temperature profile (Ts_0 cm, Ts_2 cm, Ts_4 cm, Ts_10 cm, Ts_20 cm, Ts_40 cm, Ts_60 cm, and Ts_100 cm, ℃), and soil moisture profile (Ms_2 cm, Ms_4 cm, Ms_10 cm, Ms_20 cm, Ms_40 cm, Ms_60 cm, and Ms_100 cm, %). The data processing and quality control steps were as follows. (1) The AWS data were averaged over intervals of 10 min; therefore, there were 144 records per day. The missing data were filled with -6999. (2) Data in duplicate records were rejected. (3) Unphysical data were rejected. (4) In this dataset, the time of 0:10 corresponds to the average data for the period between 0:00 and 0:10; the data were stored in *.xlsx format. (5) Finally, the naming convention was AWS+ site no. Moreover, suspicious data were marked in red. 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

  • 黑河流域分水历程调查资料

    Hydrological data of Heihe River: investigation data of water diversion process of Heihe River. Methods: field investigation, interview, data collection and electronization; Content overview: this data includes the documents, documents and research reports obtained from the investigation of the water diversion process of Heihe River by Tsinghua University, mainly including the interview records of Mr. Zhou Kan, the party who made the water diversion plan. Time and space: 1950-2010; Heihe River Basin

    0 2020-07-28

  • 黑河综合遥感联合试验:盈科绿洲与花寨子荒漠加密观测区作物管理参数调查(2008)

    The dataset of crop management survey was obtained in the Yingke oasis and Huazhaizi desert steppe foci experimental areas on Oct. 29, 30 and 31, 2008. Observation items included the observation date, the information of experimental area, the farming year, test breeds types, the sowing date, seeding quantity, planting density, the harvest date, the yield, the farming date, fertilizer, irrigation, desinsection, the key growth period, GPS, and the crop management. Data were archived in MS Office Word.

    0 2019-09-12

  • 祁连山综合观测网:青海湖流域地表过程综合观测网(青海湖湖面涡动相关仪-2018)

    This dataset contains the flux measurements from the Qinghai Lake eddy covariance system (EC) belonging to the Qinghai Lake basin integrated observatory network from January 2 to October 18 in 2018. The site (100° 29' 59.726'' E, 36° 35' 27.337'' N) was located on the Yulei Platform in Erlangjian scenic area, Qinghai Province. The elevation is 3209m. The EC was installed at a height of 16.1m, and 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 (Gill&Li7500A) was about 0.17 m. The raw data acquired at 10 Hz were processed using the Eddypro post-processing software, including the 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. 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): class 1-3 (high quality), class 4-6 (good), class 7-8 (poor, better than gap filling data), class9 (rejected). 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 collected 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, and the missing data were replaced with -6999. Data during October 13 to December 31, 2018 were absent due to the unavailable collecting condition in winter. 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/m3), CO2 mass density (CO2, mg/m3), friction velocity (ustar, m/s), stability (z/L), sensible heat flux (Hs, W/m2), latent heat flux (LE, W/m2), carbon dioxide flux (Fc, mg/ (m2s)), 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 *.xls format. Detailed information can be found in the suggested references.

    0 2020-07-25