The dataset of setting of the sampling plots and stripes in the Linze station foci experimental area was as follows: (1) Wulidun farmland quadrates (90m×90m), which was divided into nine subplots (30m×30m). Numbering of Cold and Arid Regions Environmental and Engineering Research Institute was different from that of BNU, in which the former was 1-9 from south to north, and the latter was A-I from north to south. (2) the west-east desert strip, which was composed of 20 neighbouring pairs of subplots (30×30m). They were numbered S0-S20 from the south corner on and N0-N20 from the north corner on; the common corner points in the middle were numbered M0-M20. Corner points were measured during the satellite or airplane overpass. (3) the north-south desert strip, which was composed of nine non-conterminous subplots (40m×40m, numbered from A1-A9) at intervals of 60m. Corner points and center points were measured during the satellite or airplane overpass. (4) three quadrates (30m×30m) of the transit zone, LY06，LY07，LY08 strips. Samples were selected following the zigzag line from the northwest corner and numbered 1-9. (5) the poplar forest (90×90m), which was divided into 9 subplots (30m×30m). (6) 6 desert strips with 17 sample points each. (7) maize plots (3m×3m) inside Linze station. Data including coordinates of each sample point were archived as Excel files.
0 2019-05-23
Biological productivity refers to the material production capacity of organisms and their groups or even larger scale (including ecosystem and biosphere). It changes with the environment. Therefore, it becomes an indicator of environmental change and the health of the earth system. Net primary productivity (NPP) of vegetation refers to the remaining part of total organic matter (GPP) produced by photosynthesis of green plants in unit time unit area after deducting autotrophic respiration (RA). The NPP products in Heihe River Basin mainly focus on the important parameters par and FPAR of the model of light energy utilization, and improve the algorithm and product production. The FPAR inversion model that distinguishes the direct radiation from the scattered radiation and the par inversion method based on the combination of static and polar orbit satellites are proposed. Finally, the net primary productivity data set of Heihe River Basin is produced by using the light utilization model. The algorithm improves the temporal and spatial resolution of data products, and the accuracy of products is also significantly improved.
0 2020-03-13
This data set is extracted from the second Glacier Inventory Data Set of China for Three River Source area. The file is SHP format. The attribute data are as follows: Glc_Name (glacier name), Drng_Code (basin code), FCGI_ID (first glacier catalogue code), GLIMS_ID (GLIMS glacier code), Mtn_Name (mountain system name), Pref_Name (administrative division), Glc_Long (glacier longitude), Glc_Lati (glacier latitude), Glc_Area (glacier area), Abs_Accu (absolute area accuracy), Rel_Accu (relative area accuracy), Deb_Area (surface Moraine Area), Deb_A_Accu (absolute accuracy of surface moraine Area), Deb_R_Accu (relative accuracy of surface moraine area)、Glc_Vol_A (estimation of glacier volume 1)、Glc_Vol_B (estimation of glacier volume 2)、Max_Elev (maximum glacier elevation)、Min_Elev (minimum glacier elevation)、Mean_Elev (average glacier elevation)、MA_Elev (median area height of glacier)、Mean_Slp (average glacier slope)、Mean_Asp (average glacier slope direction)、Prm_Image (major remote sensing data)、Aux_Image (auxiliary remote sensing data)、Rep_Date (glacier catalogue represents date)、Elev_Src (elevation data source)、Elev_Date (elevation represents date)、Compiler (glacier cataloguing editor)、Verifier (glacier cataloguing verifier).
0 2020-07-28
This dataset contains the automatic weather station (AWS) measurements from site No.6 in the flux observation matrix from 9 May to 21 September, 2012. The site (100.35970° E, 38.87116° N) was located in a cropland (maize surface) in Yingke irrigation district, which is near Zhangye, Gansu Province. The elevation is 1562.97 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity (HMP45AC; 5 m and 10 m, towards north), air pressure (CS100; 2 m), rain gauge (TE525M; 10 m), wind speed (010C; 5 m and 10 m, towards north), wind direction (020C; 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 (CS616; -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). The observations included the following: air temperature and humidity (Ta_5 m and Ta_10 m, RH_5 m and RH_10 m) (℃ and %, respectively), air pressure (press, hpa), precipitation (rain, mm), wind speed (Ws_5 m and 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
The dataset of ground truth measurements synchronizing with Envisat ASAR was obtained in the Linze grassland foci experimental area on Jul. 11, 2008. The data were in AP mode and VV/VH polarization combinations, and the overpass time was approximately at 11:26 BJT. Observations were carried out in the reed plot A, the saline plots B and C, the alfalfa plot D and the barley plot E, which were divided into 6×6 subsites, with each one spanning a 120×120 m2 plot. Soil gravimetric moisture, volumetric moisture, and soil bulk density after drying by using the cutting ring, the mean soil temperature from 0-5cm by the probe thermometer, and the canopy temperature and the land surface temperature by the hand-held infrared thermometer were measured in A, B and C; the soil temperature, soil moisture, the loss tangent, soil conductivity, the real part and the imaginary part of soil complex permittivity by the POGO soil sensor, the mean soil temperature from 0-5cm by the probe thermometer, the canopy temperature and the land surface temperature by the hand-held infrared thermometer in D and E. Data were archived in Excel file. See WATER: Dataset of setting of the sampling plots and stripes in the foci experimental area of Linze station for more information.
0 2019-09-11
This dataset contains the flux measurements from the Subalpine shrub eddy covariance system (EC) belonging to the Qinghai Lake basin integrated observatory network from April 28 to December 31 in 2019. The site (100°6'3.62"E, 37°31'15.67" N ) was located near Dasi, Shaliuhe Town, Gangcha County, Qinghai Province. The elevation is 3495m. The EC was installed at a height of 2.5m, 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. The released data contained the following variables: DATE/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). The quality marks of sensible heat flux, latent heat flux and carbon flux are divided into three levels (quality marks 0 have good data quality, 1 have good data quality and 2 have poor data quality). 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 2020-07-28
1. Data overview In 2011, the manual observation data set of standard meteorological field of Qilian station was used to observe various meteorological elements at 8:00, 14:00 and 20:00 every day. 2. Data content Data content includes dry bulb temperature, wet bulb temperature, maximum temperature, minimum temperature, surface temperature (0cm), shallow surface temperature (5cm, 10cm, 15cm, 20cm), maximum ground temperature and minimum ground temperature. 3. Time and space Geographic coordinates: longitude: 99.9e; latitude: 38.3n; altitude: 2980m
0 2020-03-11
Firstly, the canopy reflectance is expressed as a function of a series of parameters, such as Lai / fAPAR, wavelength, soil and leaf reflectance, aggregation index, incidence and observation angle. For several key parameters, the parameter table is established as the input of inversion. Then input the surface reflectance data and land cover data after preprocessing, and use the LUT method to retrieve the fAPAR products. See the reference for detailed algorithm. Image format: TIF Image size: about 1m per scene Time frame: 2012 Time resolution: month by month Spatial resolution: 1km
0 2020-03-10
This data set includes the continuous observation data set of soil texture, roughness and surface temperature measured by vehicle borne microwave radiometer from November 17 to 18, 2013 in Wuxing village farmland, Ganzhou District, Zhangye City, Gansu Province. The surface temperature and humidity include four layers of temperature sensor at the soil depth of 1cm, 5cm, 10cm, 20cm, and the observation of soil temperature and soil moisture data at the soil depth of 0-5cm. The time frequency of routine observation of soil temperature and humidity is 5 minutes. Data details: 1. Time: November 17-18, 2013 2. data: Brightness temperature: observed by vehicle mounted multi frequency passive microwave radiometer, including 6.925, 18.7 and 36.5ghz V polarization and H polarization data (10.65ghz band damage) Soil temperature: use sensor installed on dt80 to measure 1cm, 5cm, 10cm, 20cm soil temperature Soil moisture: use h-probe sensor to measure 0-5cm soil moisture, the probe can measure 0-5cm soil temperature at the same time Soil texture: soil samples measured in Beijing Normal University Soil roughness: measured by roughness meter provided by northeast geography 3. Data size: 3.6m 4. Data format:. Xls
0 2020-03-13
This data set contains the vortex correlator observation data of zhangye wetland station in the middle reaches of heihe meteorological observation network from January 15, 2014 to December 31, 2014.The site is located in zhangye city, gansu province.The latitude and longitude of the observation point is 100.44640E, 38.97514N, and the altitude is 1460.00m.The height of the vortex correlation instrument is 5.2m, the sampling frequency is 10Hz, the ultrasonic direction is due to the north, and the distance between the ultrasonic wind speed and temperature instrument (Gill) and the CO2/H2O analyzer (Li7500A) is 25cm. The original observation data of vorticity correlativity is 10Hz, and the released data is the data of 30 minutes processed by Eddypro software. The main steps of its processing include: outfield value elimination, delay time correction, Angle correction, coordinate rotation (secondary coordinate rotation), frequency response correction, ultrasonic virtual temperature correction and density (WPL) correction.Quality assessment for each intercompared to at the same time, mainly is the atmospheric stability (Δ st) and turbulent characteristics of similarity (ITC) test.The 30min pass value output by Eddypro software was also screened.(2) data of 1h before and after precipitation were excluded;(3) the missing rate of 10Hz original data is more than 10% every 30min;(4) the observed data of weak turbulence at night were excluded (u* less than 0.1m/s).The average period of observation data was 30 minutes, 48 data a day, and the missing data was marked as -6999.Suspicious data caused by instrument drift and other reasons are marked in red. Among them, the memory card error occurred from January 1, 2014 to January 15, 2014, during which the data is missing. Observations published include:Date/Time for the Date/Time, wind Wdir (°), Wnd horizontal wind speed (m/s), standard deviation Std_Uy lateral wind speed (m/s), ultrasonic virtual temperature Tv (℃), the water vapor density H2O (g/m3), carbon dioxide concentration CO2 (mg/m3), friction velocity Ustar) (m/s), stability Z/L (dimensionless), sensible heat flux Hs (W/m2), latent heat flux LE (W/m2), carbon dioxide flux Fc (mg/(m2s)), the quality of the sensible heat flux identifier QA_Hs, the quality of the latent heat flux identifier QA_LE,Carbon dioxide flux mass identification QA_Fc.The quality of the sensible heat and latent heat, carbon dioxide flux identification is divided into three (quality id 0: (Δ st < 30, the ITC < 30);1: (Δ st < 100, ITC < 100);The rest are 2).The meaning of data time, such as 0:30 represents the average between 0:00 and 0:30;The data is stored in *.xls format. Please refer to Li et al.(2013) for hydrometeorological network or site information, and Liu et al.(2011) for observation data processing.
0 2020-03-05
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