A land surface temperature observation system was set up in apple orchard near by the No.17 eddy covariance system of the MUlti-Scale Observation experiment on Evapotranspiration over heterogeneous land surfaces 2012 (MUSOEXE-12). This observation site can offer in situ calibration data of apple trees for TASI, WiDAS and L band sensor used in aerospace experiment. Observation Site: This point is located in a large and homogeneous apple orchard in Zhangye Experiment Field, Gansu Academy of Agricultural Sciences. It’s 4 meters away from southwest of No.17 eddy covariance system, and observation height is 4.55 m. Crown size of observed apple tree is 4 m × 4 m. Underlying surface of observation site is mainly apple trees. The coordinates of this site: 38°50′41.70" N，100°22′11.40" E. Observation Instrument: The observation system consists of one SI-111 infrared radiometers (Campbell, USA) installed vertically downward to apple tree. Observation Time: This site operates from 3 August, 2012 to 27 September, 2012. Observation data laagered by every 1 minute uninterrupted. Output data contained sample data of every 1 minute. Accessory data: Land surface (apple tree) infrared temperature (by SI-111) can be obtained. Dataset is stored in *.dat file, which can be read by Microsoft excel or other text processing software (UltraEdit, et. al). Table heads meaning: Target_C_Avg, apple tree temperature @ 4.55 m (℃); SBT_C_Avg, body temperature of SI-111 sensor (℃). Dataset is stored day by day, named as: data format + site name + interval time + date + time. The detailed information about data item showed in data header introduction in dataset.
2019-09-15
This dataset contains Doppler Weather Radar data from the Zhangye National Climate Observatory during the Watershed Allied Telemetry Experimental Research from 2008-03-08 to 2008-06-30. The latitude and longitude of the observation point are 100°16.8'E, 39°05.094'N; the altitude is 1378m. The main observation items are: rainfall, cloud physics, weather radar, etc.
2019-09-15
Trough the select tasking, we obtained the WorldView-2 stereo image data in Dayekou Basin production in mid-May 2012. In the same year from July to August, 27 GPS ground control points (GCP) and checkpoints were measured based on the watershed differential GPS control network. Based on the full-field GCPs, the rational polynomial coefficients (RPC) files of WorldView-2 images were corrected in the digital photogrammetry software system. In the stereo model, 60 high-precision tie points evenly distributed were got through image matching technology, and the 1-m and 2-m resolution digital elevation model (DEM) were rapid extracted. Moreover, the DEM was edited in some key areas, such as the shady forest coverage and Dayekou reservoir. The terrain feature points and line data were added to improve the accuracy of the results in large variation of terrain feature. Check points were composed of GPS points and model confidential points, which used for quantitative validation. And they root mean square errors RMSE were 1.9 meters and 1.2 meters respectively, which achieve the requirements of two degree accuracy of 2.0 m at a scale of 1:2000 in high mountains.
2019-09-15
The dataset of soil moisture observations was obtained by the cutting ring (50cm^3) and ML2X Soil Moisture Tachometer in the Linze station foci experimental area. Surface soil (0-5cm) was measured 2-3 times in 40 subplots of the west-east desert strip on May 24, 25, 28, Jun. 27 and Jul. 11, 2008, 2-4 times in 9 subplots of north-south strip on May 24, 25, 28, Jun. 27 and Jul. 11, 17 times from P1 to P6 strips on Jul. 4 and 8, nine times along LY06 strip on Jun. 6, 15, 29 and Jul. 11, LY07 strip on May 30, Jun. 6, 10, 15, 29 and Jul. 11 and LY08 strip on May 30, Jun. 6 and 10, and once by the cutting ring and three times by ML2X Soil Moisture Tachometer in Wulidun farmland quadrates on May 24, 25, 28, Jun. 29 and Jul. 11. Data were archived as Excel files. See the metadata record “WATER: Dataset of setting of the sampling plots and stripes in the Linze station foci experimental area” for more information of the quadrate locations.
2019-09-15
Zhanye Airport desert observation system can offer in situ calibration data for TASI, WiDAS and L band sensor used in aerospace experiment. Observation Site: This point is located in a large, homogeneous and flatten desert near by Zhangye Airport. The main vegetation type is Sparse and low shrub. The coordinates of this site: 38°4′41.30" N, 100°41′48.10" E. Observation Instrument: The observation system consists of two SI-111 infrared radiometers (Campbell, USA), one installed vertically downward to land surface, another face to south of zenith angle 35°. SI-111 sensor installed at 4.0 m height. Observation Time: This site operates from 10 June, 2012 to today. Observation data laagered by every 5 seconds uninterrupted. Output data contained sample data of every 5 seconds and mean data of 1 minute. Accessory data: Land surface infrared temperature (by SI-111), sky infrared temperature (by SI-111) can be obtained. Dataset is stored in *.dat file, which can be read by Microsoft excel or other text processing software (UltraEdit, et. al). Table heads meaning: TarT_Atm, Sky infrared temperature @ facing south of zenith angle 35° (℃); SBT_Atm, body temperature of SI-111 sensor (℃) measured sky; TarT_Sur, land surface infrared temperature @ 4.0 m height; SBT_Sur, body temperature of SI-111 sensor (℃) measured land surface. Dataset is stored day by day, named as: data format + site name + interval time + date + time. The detailed information about data item showed in data header introduction in dataset.
2019-09-15
This dataset contains the flux measurements from site No.9 eddy covariance system (EC) in the flux observation matrix from 4 June to 17 September, 2012. The site (100.38546° E, 38.87239° N) was located in a cropland (maize surface) in Yingke irrigation district, which is near Zhangye, Gansu Province. The elevation is 1543.34 m. The EC was installed at a height of 3.9 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 (Gill&Li7500A) was 0.2 m. Raw data acquired at 10 Hz were processed using the Eddypro post-processing software (Li-Cor Company, http://www.licor.com/env/products/ eddy_covariance/software.html), including spike detection, lag correction of H2O/CO2 relative to the vertical wind component, sonic virtual temperature correction, angle of attack 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.
2019-09-15
This dataset includes data recorded by the Hydrometeorological observation network obtained from the automatic weather station (AWS) at the observation system of Meteorological elements gradient of Huangzangsi station between 10 June, 2013, and 31 December, 2013. The site (100.192° E, 38.225° N) was located on a cropland (wheat) surface in the Huangzangsi village, Babao town, Qilian County, Qinghai Province. The elevation is 2612 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (HMP45AD; 5 m, north), wind speed and direction profile (03001; 10 m, north), air pressure (278; in the tamper box on the ground), rain gauge (TE525M; 10 m), four-component radiometer (CNR4; 6 m, south), two infrared temperature sensors (IRTC3; 6 m, south, vertically downward), soil heat flux (HFT3; 3 duplicates with G1 below the vegetation; G2 and G3 between plants, -0.06 m), soil temperature profile (AV-10T; 0, -0.04, -0.1, -0.2, -0.4, -0.8, -1.2, and -1.6 m), and soil moisture profile (CS616; -0.04, -0.1, -0.2, -0.4, -0.8, -1.2, and -1.6 m). The observations included the following: air temperature and humidity (Ta_5 m; RH_5 m) (℃ and %, respectively), wind speed (Ws_10 m) (m/s), wind direction (WD_10 m) (°), air pressure (press) (hpa), precipitation (rain) (mm), 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/m2), infrared temperature (IRT_1 and IRT_2) (℃), soil heat flux (Gs_1, Gs_2 and Gs_3) (W/m2), soil temperature (Ts_0 cm, Ts_4 cm, Ts_10 cm, Ts_20 cm, Ts_40 cm, Ts_80 cm, Ts_120 cm, and Ts_160 cm) (℃), and soil moisture (Ms_4 cm, Ms_10 cm, Ms_20 cm, Ms_40 cm, Ms_80 cm, Ms_120 cm, and Ms_160 cm) (%, volumetric water content). The data processing and quality control steps were as follows: (1) The AWS data were averaged over intervals of 10 min for a total of 144 records per day. The missing data were denoted by -6999. (2) Data in duplicate records were rejected. (3) Unphysical data were rejected. (4) The data marked in red are problematic data. (5) The format of the date and time was unified, and the date and time were collected in the same column, for example, date and time: 2013-9-10 10:30. (6) Finally, the naming convention was AWS+ site no. Moreover, suspicious data were marked in red. For more information, please refer to Li et al. (2013) (for hydrometeorological observation network or sites information), Liu et al. (2011) (for data processing) in the Citation section.
2019-09-15
On 7 July 2012 (UTC+8), a CASI/SASI sensor boarded on the Y-12 aircraft was used to obtain the visible/near Infrared hyperspectral image, which is located in the observation experimental area. The relative flight altitude is 2000 meters, The wavelength of CASI and SASI is 380-1050 nm and 950-2450 nm, respectively. The spatial resolution of CASI and SASI is 1 m and 2.4 m, respectively. Through the ground sample points and atmospheric data, the data product are recorded in reflectance processed by geometric correction and atmospheric correction based on 6S model.
2019-09-15
This dataset contains the flux measurements from the Huazhaizi desert steppe station eddy covariance system (EC) in the flux observation matrix from 6 June to 15 September, 2012. The site (100.31860° E, 38.76519° N) was located in a desert surface, which is near Zhangye, Gansu Province. The elevation is 1731.00 m. The EC was installed at a height of 2.85 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.
2019-09-15
This dataset contains the automatic weather station (AWS) measurements from Zhangye wetland station in the flux observation matrix from 25 June to 21 September, 2012. The site (100.44640° E, 38.97514° N) was located in a wetland surface, which is near Zhangye city, Gansu Province. The elevation is 1460 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 (03002; 5 m and 10 m, towards north), wind direction (03002; 10 m, towards north), a four-component radiometer (NR01; 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, and -0.4 m), and soil heat flux (HFP01; 3 duplicates, 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, Gs_2 and Gs_3, W/m^2), and soil temperature profile (Ts_0 cm, Ts_2 cm, Ts_4 cm, Ts_10 cm, Ts_20 cm, Ts_40 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.
2019-09-15
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