On 29 June 2012, CASI sensor carried by the Harbin Y-12 aircraft was used in a visible near Infrared hyperspectral airborne remote sensing experiment, which is located in the observation experimental area (30×30 km). The land cover pattern product in the middle reaches of the Heihe River Basin were obtained at a spatial resolution of 1 m, using CASI aerial data with high spatial and spectral resolution．A hierarchical classification structure integrated by pixel-based classification and object-based classification is used to obtain production．According to surveyed reference data about land cover and visual interpretation from high resolution imagery，the accuracy of the classification result of land cover was evaluated，and the result showed that overall accuracy was 84.61 %，Kappa coefficient was 0.8262．
XIAO Qing, Liu Liangyun
The dataset includes the fractional vegetation cover data generated from the stations of crop land, wetland, Gebi desert and desert steppe in Yingke Oasis and biomass data generated from the stations of crop land (corn) and wetland. The observations lasted for a vegetation growth cycle from 19 May, 2012 to 15 September, 2012. 1. Fractional vegetation cover observation 1.1 Observation time 1.1.1 Station of the crop land: The observations lasted from 20 May, 2012 to 15 September, 2012, and in five-day periods for each observation before 31 July and in ten-day periods for each observation after 31 July. The observation time for the station of crop land (corn) are 2013-5-20, 2013-5-25, 2013-5-30, 2013-6-5, 2013-6-10, 2013-6-16, 2013-6-22, 2013-6-27, 2013-7-2, 2013-7-7, 2013-7-12, 2013-7-17, 2013-7-27, 2013-8-3, 2013-8-13, 2013-8-25, 2013-9-5 and 2013-9-15. 1.1.2 The other four stations: The observations lasted from 20 May, 2012 to 15 September, 2012 and in ten-day periods for each observation. The observation time for the crop land are 2013-5-20, 2013-6-5, 2013-6-16, 2013-6-27, 2013-7-7, 2013-7-17, 2013-7-27, 2013-8-3, 2013-8-13, 2013-8-25, 2013-9-5 and 2013-9-15. 1.2 method 1.2.1 Instruments and measurement method Digital photography measurement is implemented to measure the FVC. Plot positions, photographic method and data processing method are dedicatedly designed. In field measurements, a long stick with the camera mounted on one end is beneficial to conveniently measure various species of vegetation, enabling a larger area to be photographed with a smaller field of view. The stick can be used to change the camera height; a fixed-focus camera can be placed at the end of the instrument platform at the front end of the support bar, and the camera can be operated by remote control. 1.2.2 Design of the samples Three and two plots with the area of 10×10 m^2 were measured for the station of the crop land and wetland, respectively. One plot with the area of 10×10 m^2 was measured for the other three stations. Shoot 9 times along two perpendicularly crossed rectangular-belt transects. The picture generated of each time is used to calculate a FVC value. “True FVC” of the plot is then acquired as the average of these 9 FVC values. 1.2.3 Photographic method The photographic method used depends on the species of vegetation and planting pattern. A long stick with the camera mounted on one end is used for the stations of crop land and wetland. For the station of the crop land, rows of more than two cycles should be included in the field of view (<30), and the side length of the image should be parallel to the row. If there are no more than two complete cycles, then information regarding row spacing and plant spacing are required. The FVC of the entire cycle, that is, the FVC of the quadrat, can be obtained from the number of rows included in the field of view. For other three stations, the photos of FVC were obtained by directly photographing for the lower heights of the vegetation. 1.2.4 Method for calculating the FVC The FVC calculation was implemented by the Beijing Normal University. The detail method can be found in the reference below. Many methods are available to extract the FVC from digital images, and the degree of automation and the precision of identification are important factors that affect the efficiency of field measurements. This method, which is proposed by the authors, has the advantages of a simple algorithm, a high degree of automation and high precision, as well as ease of operation (see the reference). 2. Biomass observation 2.1. Observation time 2.1.1 Station of the crop land: The observations lasted from 20 May 2012 to 15 September 2012, and in five-day periods for each observation before 31 July and in ten-day periods for each observation after 31 July. The observation time for the crop land are 2013-5-25, 2013-5-30, 2013-6-5, 2013-6-10, 2013-6-16, 2013-6-22, 2013-6-27, 2013-7-2, 2013-7-7, 2013-7-12, 2013-7-17, 2013-7-27, 2013-8-3, 2013-8-13, 2013-8-25, 2013-9-5 and 2013-9-15. 2.1.2 The station of wetland: The observations lasted from 20 May 2012 to 15 September 2012, and in ten-day periods for each observation. The observation time for the crop land are 2013-6-5, 2013-6-16, 2013-6-27, 2013-7-7, 2013-7-17, 2013-7-27, 2013-8-3, 2013-8-13, 2013-8-25, 2013-9-5 and 2013-9-15. 2.2. Method Station of the crop land: Three plots were selected and three strains of corn for each observation were random selected for each plot to measure the fresh weight (the aboveground biomass and underground biomass) and dry weight. Per unit biomass can be obtained according to the planting structure. Station of the wetland: Two plots of reed with the area of 0.5 m × 0.5 m were random selected for each observation. The reed of the two plots was cut to measure the fresh weight (the aboveground biomass) and dry weight. 2.3. Instruments Balance (accuracy 0.01 g); drying oven 3. Data storage All observation data were stored in excel. Other data including plant spacing, row spacing, seeding time, irrigation time, the time of cutting male parent and the harvest time of the corn for the station of cropland were also stored in the excel.
GENG Liying, Jia Shuzhen, Li Yimeng, MA Mingguo
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 4800 m with the point cloud density 1 points per square meter. Aerial LiDAR- DSM was obtained through parameter calibration, automatic classification of point cloud density and manual editing.
XIAO Qing, Wen Jianguang
This dataset contains the data of the meteorological element gradient observation system of the Sidaoqiao superstation downstream of the Heihe Hydrometeorological Observation Network from January 1, 2014 to December 31, 2014. The site is located in Sidaoqiao, Dalaihu Town, Ejin Banner, Inner Mongolia. The underlying surface is Tamarix. The latitude and longitude of the observation point is 101.1374E, 42.0012N, and the altitude is 873m. The air temperature, relative humidity and wind speed sensors are respectively set at 5m, 7m, 10m, 15m, 20m and 28m, with 6 layers facing the north; the wind direction sensor is set at 15m, facing the north; the barometer is installed in the waterproof box. The tipping bucket rain gauge is installed at 28m; the four-component radiometer is installed at 10m, facing south; two infrared thermometers are installed at 10m, facing south, the probe orientation is vertically downward; two photosynthetically active radiometers are installed At 10m, facing south, and the probe is vertically upward and downward respectively; the soil moisture sensor is installed 2m on the south side of the tower body, and the soil heat flow plates (self-correcting type) (3 pieces) are buried in turn in the ground 6cm deep; The average soil temperature sensor TCAV is buried in the ground 2cm, 4cm; the soil temperature probe is buried in the ground surface 0cm and underground 2cm, 4cm, 10cm, 20cm, 40cm, 80cm, 120cm and 160cm; soil moisture sensors are buried in the underground 2cm, 4cm, 10cm, 20cm, 40cm, 80cm, 120cm and 160cm. Observed items include: wind speed (WS_5m, WS_7m, WS_10m, WS_15m, WS_20m, WS_28m) (unit: m/s), wind direction (WD_15m) (unit: degree), air temperature and humidity (Ta_5m, Ta_7m, Ta_10m, Ta_15m, Ta_20m, Ta_28m and RH_5m, RH_7m, RH_10m, RH_15m, RH_20m, RH_28m) (unit: centigrade, percentage), pressure (unit: hectopascal), precipitation (Rain) (unit: mm), four-component radiation (DR, UR, DLR_Cor, ULR_Cor, Rn) (unit: watts/square meter), surface radiation temperature (IRT_1, IRT_2) (unit: centigrade), up and down photosynthetically active radiation (PAR_U_up, PAR_U_down) (unit: micromol/square Msec), average soil temperature (TCAV) (unit: centigrade), soil heat flux (Gs_1, Gs_2, Gs_3) (unit: watts/square meter), soil moisture (Ms_2cm, Ms_4cm, Ms_10cm, Ms_20cm, Ms_40cm, Ms_80cm) , Ms_120cm, Ms_160cm) (unit: volumetric water content, percentage), soil temperature (Ts_0cm, Ts_2cm, Ts_4cm, Ts_10cm, Ts_20cm, Ts_40cm, Ts_80cm, Ts_120cm, Ts_160cm) (unit: centigrade). Processing and quality control of the observation data: (1) ensure 144 data per day (every 10 minutes), when there is missing data, it is marked by -6999; From September 8, 2014 to November 8, due to the sensor problems, the data is missing; on May 9, 2014, the soil moisture probe was re-buried, and the data before and after is inconsistent; (2) eliminate the moment with duplicate records; (3) delete the data that is obviously beyond the physical meaning or the range of the instrument; (5) the format of date and time is uniform, and the date and time are in the same column. For example, the time is: 2014-9-10 10:30; (6) the naming rules are: AWS+ site name. For hydrometeorological network or site information, please refer to Li et al. (2013). For observation data processing, please refer to Liu et al. (2011).
LIU Shaomin, LI Xin, CHE Tao, XU Ziwei, REN Zhiguo, TAN Junlei
This dataset contains the flux measurements from site No.4 eddy covariance system (EC) in the flux observation matrix from 31 May to 17 September, 2012. The site (100.35753° E, 38.87752° N) was located in a residential area in Yingke irrigation district, which is near Zhangye, Gansu Province. The elevation is 1561.87 m. The EC was installed at a height of 4.2 m (6.2 m after 19 August); 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&Li7500A) 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.
LIU Shaomin, LI Xin, XU Ziwei
The data set contains the observation data of the eddy covariance system of the desert station, which is located along the lower reaches of the Heihe Hydro-meteorological observation network, and the data set covers data from April 28, 2015 to December 31, 2015. The station is located in Ejina Banner, Inner Mongolia, and the underlying surface is desert. The latitude and longitude of the observation station is 100.9872E, 42.1135N, and the altitude 1054m. The height of the eddy covariance system is 4.7 meters, the sampling frequency is 10Hz, the ultrasonic orientation is positive north, and the distance between the ultrasonic wind speed and temperature monitor (CSAT3) and the CO2/H2O analyzer (Li7500) is 15cm. The original observation data of the eddy covariance system is 10 Hz, and the released data is a 30-minute data processed by Eddypro software. The main steps of the processing include: outlier eliminating, delay time correction, coordinates rotation (secondary coordinates rotation), frequency response correction, ultrasonic virtual temperature correction and density (WPL) correction, etc. Meanwhile, the quality evaluation of each flux value was performed,mainly includes atmospheric stability (Δst) test and turbulence similarity (ITC) test. The 30-min flux value output of Eddypro software was also screened: (1) Data from the instrument error was eliminated; (2) Data obtained with one hour before and after precipitation was removed; (3) Data with a deletion rate greater than 10% of the 10 Hz raw data every 30 minutes was eliminated; (4) Observation data of weak turbulence at night (u* less than 0.1 m/s) was excluded. The average period of observation data is 30 minutes, 48 data per day, and the missing data is marked as -6999. The suspicious data caused by instrument drift and other reasons was marked by red fonts. Published observation data include: Date/Time, wind direction(°), horizontal wind speed(m/s), lateral wind speed standard deviation(m/s), ultrasonic virtual temperature (°C), water vapor density (g/m3), carbon dioxide concentration(mg/m3), friction velocity (m/s), length (m), sensible heat flux(W/m2), latent heat flux (W/m2), carbon dioxide flux (mg/(m2s)), sensible heat flux quality identification QA_Hs, latent heat flux quality identification QA_LE, carbon dioxide flux quality identification QA_Fc. The quality identification of sensible heat, latent heat, and carbon dioxide flux is divided into three levels (quality mark 0: (Δst <30, ITC<30); 1: (Δst <100, ITC<100); the rest is 2). The meaning of the data time, such as 0:30 represents an average data of 0:00-0:30; the data is stored in *.xls format. For hydro-meteorological network or station information, please refer to Li et al. (2013). For observation data processing, please refer to Liu et al. (2011).
LIU Shaomin, LI Xin, CHE Tao, XU Ziwei, REN Zhiguo, TAN Junlei
This dataset contains the automatic weather station (AWS) measurements from site No.7 in the flux observation matrix from 28 May to 18 September, 2012. The site (100.36521° E, 38.87676° N) was located in a cropland (maize surface) in Yingke irrigation district, which is near Zhangye, Gansu Province. The elevation is 1556.39 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 (010C/020X; 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 (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). 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.
LI Xin, XU Ziwei
On 26 July 2012, Wide-angle Infrared Dual-mode line/area Array Scanner (WIDAS) carried by the Harbin Y-12 aircraft was used in a visible near Infrared thermal Dual-mode airborne remote sensing experiment, which is located in the artificial oasis eco-hydrology experimental area (5×5 km). WIDAS includes a CCD camera with a spatial resolution of 0.2 m, a visible near Infrared multispectral camera with five bands scanner (an maximum observation angle 48° and spatial resolution 1 m), and a thermal image camera with a spatial resolution of 4.8 m. The CCD camera data are recorded in DN values processed by mosaic and orthorectification.
XIAO Qing, Wen Jianguang
The dateset of sun photometer observations was obtained in the Biandukou foci experimental area from Mar. 7 to 17, 2008, simultaneous with MODIS and TM. Those provide reliable data for atmosphere correction of the same period in this area. Atmospheric parameters were measured by CE318. The optical depth in 1020nm, 936nm, 870nm, 670nm and 440nm were all acquired. Column water vapor can also be retrieved according to data in 936 nm. The dataset archived in txt files includes processed data on Mar. 7, 14 and 17 respectively.
SU Gaoli
The dataset of sun photometer observations was obtained in Linze grassland station, the reed plot A, the saline plot B, the barley plot E, the observation stationof the Linze grassland foci experimental areaand Jingdu hotel of Zhangye city. The optical depth in 1020nm, 936nm, 870nm, 670nm and 440nm were all acquired by CE318 from May 30 to Jun. 11, 2008. And from Jun. 15 to Jul.11, the data of 1640nm, 1020nm, 936nm, 870nm, 670nm, 550nm, 440nm, 380nm and 340nm were acquired. Both measurements were carried out at intervals of 1 minute. Optical depth, rayleigh scattering, aerosol optical depth, the horizontal visibility, air temperature and pressure near land surface, the solar azimuth and zenith could all be further retrieved. Readme file was attached for detail.
LIANG Ji, WANG Xufeng
This dataset contains the flux measurements from site No.17 eddy covariance system (EC) in the flux observation matrix from 31 May to 17 September, 2012. The site (100.36972° E, 38.84510° N) was located in an orchard (apple tree) in Daman irrigation district, which is near Zhangye, Gansu Province. The elevation is 1559.63 m. The EC was installed at a height of 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&EC150) was 0 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.
LIU Shaomin, LI Xin, XU Ziwei
The dataset of automatic meteorological observations was obtained at the Binggou cold region hydrometerological station (N38°04′/E100°13′), south of Qilian county, Qinghai province, from Sep. 25, 2007 to Dec. 31, 2009. The experimental area with paramo and riverbed gravel, situated in the upper stream valley of Heihe river, is ideal for the flat and open terrain and hills and mountains stretching outwards. The items were multilayer (2m and 10m) of the air temperature and air humidity, the wind speed, the air pressure, precipitation, four components of radiation, the multilayer soil temperature (5cm, 10cm, 20cm, 40cm, 80cm and 120cm), soil moisture (5cm, 10cm, 20cm, 40cm, 80cm and 120cm), and soil heat flux (5cm and 15cm). The raw data were level0 and the data after basic processes were level1, in which ambiguous ones were marked; the data after strict quality control were defined as Level2. The data files were named as follows: station+datalevel+AMS+datadate. Level2 or above were strongly recommended to domestic users. The period from Sep. 25, 2007 to Mar. 12, 2008 was the pre-observing duration, during which hourly precipitation data (fragmented) and the soil temperature and soil moisture data were to be obtained. Stylized observations began from Mar. 12, 2008. As for detailed information, please refer to Meteorological and Hydrological Flux Data Guide.
WANG Jian, CHE Tao, MA Mingguo, Wang Weizhen, LI Hongyi, HAO Xiaohua, HUANG Guanghui, Zhang Zhihui, TAN Junlei
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.
LIU Shaomin, LI Xin, XU Ziwei
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.
LIU Shaomin, LI Xin
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.
LIU Shaomin, LI Xin, XU Ziwei
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.
LIU Shaomin, LI Xin, XU Ziwei
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.
MA Mingguo
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.
XIAO Qing, Wen Jianguang
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”.
WANG Haibo
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.
LIU Shaomin, LI Xin, CHE Tao, XU Ziwei, REN Zhiguo, TAN Junlei
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