This dataset contains the flux measurements from site No.5 eddy covariance system (EC) in the flux observation matrix from 3 June to 18 September, 2012. The site (100.35068° E, 38.87574° N) was located in a cropland (maize surface) in Yingke irrigation district, which is near Zhangye, Gansu Province. The elevation is 1567.65 m. The EC was installed at a height of 3 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 0.17 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 includes observational data of sap flow from 14 June to 21 September, 2012. The study area was located in the irrigation area within the middle reaches of the Heihe River Basin, China. Sample trees were selected for installing TDP (thermal dissipation sap flow velocity probe) instruments according to their height and diameter at breast height (DBH); only Popolusgansuensis trees were selected in this study. The TDP instrument is made in China; the model type was TDP30. There were 3 TDP observation sites, i.e., TDP-1, TDP-2 and TDP-3, which were located near the LAS4_S, EC6 and EC8 sites, respectively. The order of tree heights was TDP-2 > TDP-1 > TDP-3, and the order of DBH was TDP-2 > TDP-3 > TDP-1. At each site, 3 representative trees were selected to measure the sap flow. Three TDPs were mounted on the stem of each tree, one each for the southeast, southwest and north directions; the mounting height is 1.3 meters. Each TDP had two probes. The raw TDP data included the temperature difference between the two probes at a frequency of 30 s. The released data include the 10 minute-averaged sap flow rate (cm/h), sap flow flux (cm^3/h), and daily transpiration (mm/d). The sap flow rate and the sap flow flux were calculated according to the temperature difference between the two probes; the shelter-forest transpiration per unit area (Q) was calculated based on the area of shelterbelts and density of Popolusgansuensis trees at each site. The data preprocessing steps included the following. (1) Unphysical data were excluded. (2) Missing data were filled with -6999. (3) Suspicious data, which were most likely caused by probe failure, were marked in red; confirmed bad data were excluded. For more information, please refer to Liu et al. (2016) (for multi-scale observation experiment or sites information), Qiao et al. (2015) (for data processing) in the Citation section.
2019-09-15
This dataset contains the automatic weather station (AWS) measurements from site No.11 in the flux observation matrix from 2 June to 18 September, 2012. The site (100.34197° E, 38.86991° N) was located in a cropland (maize surface) in Yingke irrigation district, which is near Zhangye, Gansu Province. The elevation is 1575.65 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity (HMP45AC; 5 m, towards north), air pressure (CS100; 2 m), rain gauge (TE525M; 10 m), wind speed and direction (03001; 10 m, towards north), a four-component radiometer (CNR1; 6 m, towards south), two infrared temperature sensors (SI-111; 6 m, vertically downward), soil temperature profile (109; 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 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.
2019-09-15
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.
2019-09-15
Our project entrust the L band radiosonde sounding encrypt observations to Zhangye National Climate Observatory, and collect regular observation twice a day. The dataset contains three times one day at 8:00, 14:00, 20:00, which can support the remote sensing image atmospheric correction and atmospheric science research. Observation Site: Zhangye National Climate Observatory located in Shajing Town, west of ZhangYe. The coordinates of this site: 39°5′15.68" N, 100°16′39.11" E。 Observation Instrument: China Meteorological Administration Operational L Band radiosonde system. Observation Time: The observation date last from 1 May, 2012 to 31 September, 2012, among which: Three times observations at 7:00-8:00, 13:00-14:00 and 19:00-20:00 during 1 June, 2012 to 31 August, 2012; twice at 7:00-8:00 and 19:00-20:00 during 2012-5-1 to 5-31 and 2012-9-1 to 9-31. Accessory data： Pressure, temperature, relative humidity, wind speed and wind direction profiles data.
2019-09-15
On 28 August 2012, Leica ALS70 airborne laser scanner carried by the Harbin Y-12 aircraft was used in a LiDAR airborne optical remote sensing experiment. Leica ALS70 airborne laser scanner has unlimited numbers of returns intensities measurements including the first, second ,third return intensities. The wavelength of laser light is 1064 nm. The absolute flight altitude is 4800 m with the point cloud density 1.6 point per square meter. Airborne LiDAR-DEM and DSM data production were obtained through parameter calibration, automatic classification of point cloud density and manual editing.
2019-09-15
The dataset of photosynthesis was observed by LI-6400XT Portable Photosynthesis System in the natural oasis eco-hydrology experimental area of the Heihe River Basin. Observation items included the main vegetation type in the lower reaches of Heihe river: Populus forest, which located in the Populus forest station and the mixed forest station of Ejinaqi. Observation periods lasted from 2014-07-24 to 2014-07-31. This dataset included the raw observation data of the Populus forest observed by LI-6400 during the observation periods. 1） Objectives of observation The photosynthetic datasets can be used in the study of plant physiological ecology characteristic and the simulation and validation for the eco-hydrological models. 2） Instrument and theory of the observation Measuring instrument: LI-6400XT Portable Photosynthesis System. Measuring theory: Using the infrared gas analyzer to measure the change of CO2 concentration, and then measuring the differences of CO2 concentration between the sample chamber and the referenced chamber so as to acquire the net productivity of the leaf. 3） Time and site of observation Observation site in the Populus forest station. Observation time: 2014-07-24 Observation site in the mixed forest station. Observation time: From 2014-07-25 to 2014-07-31. 4） Data processing The raw data of LI-6400 were archived in text format and can be opened by text editor or excel, the preprocessed data were in Excel format. Every time period of observation was archived in a single document, named as “date + type”.
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 Sidaoqiao cropland station between 9 July, 2013, and 31 December, 2013. The site (101.134° E, 42.005° N) was located on a cropland (melon) surface in the Sidaoqiao, Dalaihubu Town, Ejin Banner, Inner Mongolia Autonomous Region. The elevation is 875 m. The installation heights and orientations of different sensors and measured quantities were as follows: four-component radiometer (CM21; 6 m, south), two infrared temperature sensors (SI-111; 6 m, south, vertically downward), two photosynthetically active radiation (PQS-1; 6 m, south, one vertically upward and one vertically downward), soil heat flux (HFP01; 3 duplicates with G1 below the vegetation; G2 and G3 between plants, -0.06 m), and soil temperature profile (AV-10T; 0, -0.02 and -0.04 m). The observations included the following: 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 IRT_2) (℃), photosynthetically active radiation of upward and downward (PAR_up and PAR_down) (μmol/ (s m^-2)), soil heat flux (Gs_1, Gs_2 and Gs_3) (W/m^2), the soil temperature (Ts_0 cm, Ts_2 cm and Ts_4 cm) (℃). 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 25 July 2012, a Leica ALS70 airborne laser scanner boarded on the Y-12 aircraft was used to obtain the point cloud data. Leica ALS70 airborne laser scanner has unlimited numbers of returns intensities measurements including the first, second, third return intensities. The wavelength of laser light is 1064 nm. The absolute flight altitude is 5500 m with the point cloud density 1 points per square meter. Aerial LiDAR-DEM was obtained through parameter calibration, automatic classification of point cloud density and manual editing.
2019-09-15
The aim of the simultaneous observation of land surface temperature is obtaining the land surface temperature for different kinds of underlying surface, including the lager areas of homogeneous vegetation with high coverage, water, and concrete floor, while the thermal imager go into the experimental areas of the low reaches. All the land surface temperature data will be used for validation of the retrieved land surface temperature from thermal imager and the analysis of the scale effect of the land surface temperature, and finally serve for the validation of the plausibility checks of the surface temperature product from remote sensing. 1. Observation time On 1 August, 2014 2. Observation samples Three field samples were chosen in the fly zone, which were large areas of homogeneous vegetation (with high coverage), water, and concrete floor. 3. Observation method Surface temperature values were observed continuously for each sample using handheld infrared thermometers during the imager went into the flying area. 4. Instrument parameters and calibration The field of view of the handheld infrared thermometer is one degree and the emissivity was assumed to be 0.95. All instruments were calibrated on 31 July, 2014 using a black body. 5. Data storage All the observation data were stored in an excel.
2019-09-15
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