This dataset is the LAI observation in the artificial oasis experimental region of the middle stream of the Heihe River Basin. The observation period is from 24 May to 20 September 2012 (UTC+8). Measurement instruments: LAI-2000 (Beijing Normal University) Measurement positions: Core Experimental Area of Flux Observation Matrix 18 corn samples, 1 orchard sample, 1 artificial white poplar sample Measurement methods: To measure the incoming sky radiation on the canopy firstly. Then the transmission sky radiation are mearued under the canopy for serveral times. The canopy LAI is retrieved by using the gap probability model.
Li Yun, Wang Yan, MA Mingguo
Lysimeter is the most effective tool for measuring water consumption per plant, which can provide daily, monthly and seasonal changes of transpiration water consumption per plant. In this project, a lysimeter measurement system for Populus euphratica seedlings is established in the lower reaches of Heihe River, with the observation frequency of 0.5h, mainly including water content changes, infiltration, evapotranspiration, etc.
SI Jianhua
The dataset of ground truth measurement synchronizing with the airborne microwave radiometers (L&K bands) mission was obtained in L2, L4 and L5 of the A'rou foci experimental area on Mar. 19, 2008. The samples were collected every 100 m along the strip from south to north. In L2, the soil temperature, soil volumetric moisture, the loss tangent, soil conductivity, and the real part and the imaginary part of soil complex permittivity were acquired by the POGO soil sensor, the mean soil temperature from 0-5cm by the probe thermometer, and soil gravimetric moisture, volumetric moisture, and soil bulk density after drying by the cutting ring (100cm^3). In L4, the soil temperature, soil volumetric moisture, the loss tangent, soil conductivity, and the real part and the imaginary part of soil complex permittivity were acquired by the POGO soil sensor, the mean soil temperature from 0-5cm by the probe thermometer, the surface radiative temperature measured three times by the hand-held infrared thermometer, and soil gravimetric moisture, volumetric moisture, and soil bulk density after drying by the cutting ring (100cm^3). In L5, soil volumetric moisture was acquired by ML2X, the mean soil temperature from 0-5cm by the probe thermometer, and soil gravimetric moisture, volumetric moisture, and soil bulk density after drying by the cutting ring (100cm^3). Surface roughness was detailed in the "WATER: Surface roughness dataset in the A'rou foci experimental area". Besides, GPR (Ground Penetration Radar) observations were also carried out in L6 and the handheld thermal imager observations in L4. Those provide reliable ground data for retrieval and validation of soil moisture and freeze/thaw status from active remote sensing approaches.
CAO Yongpan, GU Juan, HAN Xujun, LI Zhe, WANG Jianhua, Wang Weizhen, WU Yueru, ZHOU Hongmin, LI Hua, CHANG Cun, YU Meiyan, ZHAO Jin, PATRICK Klenk, SUN Jicheng, YAN Yeqing
The dataset of groundwater level was obtained by the automatic water gauges at an interval of 1 hour from Dec. 25 2007 to Jul. 6, 2009. In order to monitor changes in the groundwater level and in the groundwater temperature in the cold region hydrology experiment area, six sets of instruments (the HOBO pressure type mario/thermograph: U20-001-01; U20-001-01-TI) were scattered by Cold and Arid Regions Environmental and Engineering Research Institute, CAS in the Yingke oasis, Xinmiao village in Daman township, Daman Water Management office, Wangqizha village in Xiaoman township, Yanhe village in Mingyong county, Xiaowan village in Wujiang township and Liuquan village in Xindun township respectively. The items were mainly the groundwater pressure and the groundwater temperature . Based on the air pressure obtained in the Yingke oasis station, the groundwater pressure by HOBO could be changed into the grounwater depth, and the groundwater level could be developed by differential GPS.
TAN Junlei, Qian Jinbo, MA Mingguo, WANG Xufeng
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.
SONG Yi, MA Mingguo
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.
LI Li, ZHONG Bo, WU Junjun, WU Shanlong, XIN Xiaozhou
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.
LIU Shaomin, LI Xin, XU Ziwei
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.
CAO Yongpan, CHAO Zhenhua, GE Chunmei, HU Xiaoli, HUANG Chunlin, LIU Chao, WU Yueru, SHEN Xinyi
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
HAN Chuntan, CHEN Rensheng
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
FAN Wenjie
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
ZHAO Shaojie, KOU Xiaokang, YE Qinyu, MA Mingguo
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.
LIU Shaomin, LI Xin, XU Ziwei, CHE Tao, REN Zhiguo, TAN Junlei
The data set is the physiological and ecological parameters of the dominant species of each ecosystem in Heihe River Basin. According to the requirements of tesim model, the data set divides Heihe River basin into seven ecosystems: deciduous broad-leaved forest ecosystem (BRD), evergreen coniferous forest ecosystem (CNF), agricultural field ecosystem (CRP), desert ecosystem (DST), meadow grassland ecosystem (MDS) Shrubbery ecosystem (SHB) and grassland ecosystem (STP). Some of the data in this data set are based on the measured data, some are obtained by reference documents, but after verification, they are applied to the Heihe River Basin. For the data in this data, each parameter of each ecosystem has three values, which are the value in the model, the minimum value and the maximum value of this parameter. The data can provide input parameters for the ecological process model, and the data set is still in further optimization.
PENG Hongchun
1. Data overview The soil temperature monitoring point of the typical soil profile in the small basin of cucurbitou was set in the middle and lower part of the red mud ditch, and its geographical coordinates were 99 ° 52 '25.3 "E, 38 ° 15' 37.97" N. Soil Temperature was observed using HOBO Pendant® Temperature/Light Data Logger 64k-ua-002-64 Temperature recorder. 2. data content Soil temperature monitoring in typical soil profile of hongnigou is divided into seven layers, with depth distribution of 20cm, 40cm, 60cm, 80cm, 120cm, 160cm and 200cm.The frequency of observation is 1 time /15 minutes.The time range of observation data is from September 7, 2012 to May 6, 2013.
SUN Ziyong, CHANG Qixin
The 1 km / 5-day FVC data set of Heihe River basin provides the 5-day FVC synthesis results from 2011 to 2014. The data uses the data of Terra / MODIS, Aqua / MODIS, and domestic satellites fy3a / MERSI and fy3b / MERSI to build a multi-source remote sensing data set with a spatial resolution of 1 km and a time resolution of 5 days. The whole country is divided into different vegetation divisions and land types, and the conversion coefficient of NDVI and FVC is calculated respectively. The conversion coefficient look-up table and 1km / 5-day synthetic NDVI product production area 1km / 5-day synthetic FVC product are used. In the Heihe River Basin, 1 km / 5-day synthetic FVC products can directly obtain vegetation coverage ratio through high-resolution data to reduce the impact of low-resolution data heterogeneity; in addition, select the typical period of vegetation growth and change, obtain the corresponding growth curve parameters of each pixel by fitting the vegetation index of each pixel time series; and then cooperate with land use map and vegetation classification map, To find the representative uniform pixel of the region to train the conversion coefficient of vegetation index. Compared with the results of high-resolution aster reference FVC in Heihe River Basin, the first step is to aggregate the aster products in Heihe River basin to 1km scale by combining the measured ground data and using the scale up method, and to obtain the aster aggregate FVC data, which is based on spot vegetation remote sensing data released by geoland 2 project (geov1 for short) The results show that the results of geov1 are higher than those of ASTER image combined with ground measurement, and the results of 1 km / 5-day synthetic FVC products in Heihe River Basin are between the two, and the results of 1 km / 5-day synthetic FVC products in Heihe River Basin in the experimental area are better than those of geov1 products. In a word, the comprehensive utilization of multi-source remote sensing data to improve the estimation accuracy and time resolution of FVC parameter products can better serve the application of remote sensing data products.
MU Xihan, RUAN Gaiyan, ZHONG Bo, LIU Qinhuo
On 29 June 2012 (UTC+8), a CASI/SASI 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 relative flight altitude is 3500 meters（an elevation of 3500 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 are recorded in reflectance processed by geometric correction and atmospheric correction based on 6S model.
XIAO Qing, Wen Jianguang
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 Shenshawo sandy desert station between 1 September, 2012, and 31 December, 2013. The site (100.493° E, 38.789° N) was located on a desert surface in the Shenshawo, which is near Zhangye city, Gansu Province. The elevation is 1594 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (HMP45AC; 5 and 10 m, north), wind speed profile (010C; 5 and 10 m, north), wind direction profile (020C; 10 m, north), air pressure (PTB110; 2 m), rain gauge (52203; 10 m), four-component radiometer (CNR1; 6 m, south), two infrared temperature sensors (IRTC3; 6 m, south, vertically downward), soil heat flux (HFP01; 3 duplicates, -0.06 m), soil temperature profile (109; 0, -0.02, -0.04, -0.1, -0.2, -0.4, -0.6, and -1 m), and soil moisture profile (CS616; -0.02, -0.04, -0.1, -0.2, -0.4, -0.6 and -1 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), wind speed (Ws_5 m and 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/m^2), infrared temperature (IRT_1 and IRT_2) (℃), soil heat flux (Gs_1, Gs_2 and Gs_3) (W/m^2), soil temperature (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 (Ms_2 cm, Ms_4 cm, Ms_10 cm, Ms_20 cm, Ms_40 cm, Ms_60 cm and Ms_100 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 precipitation data were missing during 31 March, 2013 and 26 July, 2013 because of the malfunction of rain gauge. 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: 2013-6-10 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
The data includes the discharge data of the outlet river of No.2 catchment area of hulugou small watershed from July 24 to September 11, 2014 / 2015. Sampling location: the coordinates of river flow monitoring section are located at the outlet of No. 2 catchment area, near the red wall, with coordinates of 99 ° 52 ′ 58.40 ″ E and 38 ° 14 ′ 36.85 ″ n. The soil temperature monitoring depth in hulugou is 20cm, 50cm, 100cm, 200cm and 300cm. The monitoring depth of groundwater temperature is 10m. The observation frequency is 1 time / 1 hour. The time range of observation data is from May 13, 2015 to September 5, 2015. Sampling location: the soil temperature monitoring point in hulugou small watershed is located in the middle of the Delta, with the geographic coordinates of 99 ° 52 ′ 45.38 ″ E and 38 ° 15 ′ 21.27 ″ n.
MA Rui
The dataset of ground truth measurement synchronizing with the airborne LiDAR mission and Envisat ASAR was obtained in the Yingke oasis and Huazhaizi desert steppe foci experimental areas on Jun. 19, 2008. The Envisat ASAR data were in AP mode and VV/VH polarization combinations, and the overpass time was approximately at 11:17 (Beijing Time). The observation item was soil moisture by TDR ( the probe with a length of 5cm) in the maize plot of Yingke oasis station, the wheat plot and some temporary sample points (details in GPS.txt).
GE Yingchun, SHU Lele, XIA Chuanfu, ZHOU Mengwei
This dataset includes soil moisture, soil temperature and land surface temperature observations of 50 WATERNET wireless sensor network (WSN) nodes during the period from May to September 2012, which is one type of WSN nodes in the Heihe eco-hydrological wireless sensor network (WSN). The WATERNET located in the 4×4 MODIS grids in the observation matrix in the Zhangye oasis. Each WATERNET node observes the soil moisture, soil temperature, soil conductivity and complex dielectric constant at 4 cm and 10 cm depths by the Hydra Probe II sensor. There are 29 nodes among the WATERNET with the SI-111 sensor at 4 m height to measure the surface radiance temperature. The operational observation interval is 10 minutes, and the intensive observation mode with 1 minute is activated during 00:00-04:30, 08:00-18:00 and 21:00-24:00 (UTC+8), in order to synchronize with airborne or satellite-borne remote sensors. This dataset can be used in the estimation of surface hydrothermal variables and their validation, eco-hydrological research, irrigation management and so on. The detail description please refers to "WATERNET_Data_Document_HRBMiddle.docx”.
KANG Jian, Wang Zuocheng, Dong Cunhui, LI Xin, MA Mingguo
The dataset of chlorophyll content observations was obtained in the Yingke oasis and Linze grassland foci experimental areas. Observation items included: (1) Chlorophyll content synchronizing with TM in Yingke oasis No. 1, 4 and 5 maize plots on May 20, 2008. (2) Chlorophyll content synchronizing with ASTER and MODIS in Linze grassland foci experimental areas on May 24, 2008. (3) Chlorophyll content synchronizing with ASTER and MODIS in Yingke oasis maize field on May 28, 2008. (4) Chlorophyll content synchronizing with WiDAS (Wide-angle Infrared Dual-mode line/area Array Scanner) in Yingke oasis maize field on May 30, 2008. (5) Chlorophyll content synchronizing with OMIS-II in Yingke oasis maize field on Jun. 16, 2008. (6) Chlorophyll content synchronizing with WiDAS (Wide-angle Infrared Dual-mode line/area Array Scanner) in Yingke oasis maize field on Jun. 29, 2008. (7) Chlorophyll content synchronizing with WiDAS (Wide-angle Infrared Dual-mode line/area Array Scanner) and TM in Yingke oasis maize field on Jul. 7, 2008. (8) Chlorophyll content synchronizing with WiDAS (Wide-angle Infrared Dual-mode line/area Array Scanner) in Yingke oasis maize field on Jul. 11, 2008.
LI Li, XIN Xiaozhou, ZHANG Yang, ZHOU Mengwei
The dataset of automatic meteorological observations was obtained at the A'rou freeze/thaw observation station from Jul. 25, 2008 to Dec. 31, 2009, in Wawangtan pasture (E100°28′/N38°03′, 3032.8), Daban, A'rou. The experimental area, situated in the valley highland of south Babaohe river, an upper stream branch of Heihe river, with a flat and open terrain slightly sloping from southeast to southeast and hills and mountains stretching for 3km is ideal for a horizontal homogeneous underlying surface. Observation items included multilayer (2m and 10m) of the wind speed, the air temperature and air humidity, the air pressure, precipitation, four components of radiation, the multilayer soil temperature (10cm, 20cm, 40cm, 80cm, 120cm and 160cm), soil moisture (10cm, 20cm, 40cm, 80cm, 120cm and 160cm), and soil heat flux (5cm & 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. As for detailed information, please refer to Meteorological and Hydrological Flux Data Guide.
HU Zeyong, MA Mingguo, Wang Weizhen, HUANG Guanghui, Zhang Zhihui, TAN Junlei
The data set contains data from January 1, 2016 to December 31, 2016 from the meteorological element gradient observation system of alou superstation, upstream of the heihe hydrometeorological observation network.The station is located in caoban village, aru township, qilian county, qinghai province.The longitude and latitude of the observation point are 100.4643e, 38.0473n and 3033m above sea level.The air temperature, relative humidity and wind speed sensors are located at 1m, 2m, 5m, 10m, 15m and 25m respectively, with a total of six layers facing due north.The wind direction sensor is located at 10m, facing due north;The barometer is installed at 2m;The tilting bucket rain gauge is installed on the observation tower 40m of super aru station;The four-component radiometer is installed at 5m, facing due south;Two infrared thermometers are installed at 5m, facing due south, and the probe facing vertically downward.The photosynthetic effective radiometer is installed at 5m, facing due south, and the probe facing vertically upward.Part of the soil sensor is buried at 2m in the south direction of the tower body, and the soil heat flow plate (self-correcting formal) (3 pieces) are all buried at 6cm underground.The mean soil temperature sensor TCAV is buried 2cm and 4cm underground.The soil temperature probe is buried at the surface of 0cm and underground of 2cm, 4cm, 6cm, 10cm, 15cm, 20cm, 30cm, 40cm, 60cm, 80cm, 120cm, 160cm, 200cm, 240cm, 280cm and 320cm, among which the 4cm and 10cm layers have three repeats.The soil water sensor is buried underground 2cm, 4cm, 6cm, 10cm, 15cm, 20cm, 30cm, 40cm, 60cm, 80cm, 120cm, 160cm, 200cm, 240cm, 280cm and 320cm respectively, among which the 4cm and 10cm layers have three duplexes. The observations included the following: air temperature and humidity (Ta_1 m, Ta_2 m, Ta_5 m, Ta_10 m, Ta_15 m and Ta_25 m; RH_1 m, RH_2 m, RH_5 m, RH_10 m, RH_15 m and RH_25 m) (℃ and %, respectively), wind speed (Ws_1 m, Ws_2 m, Ws_5 m, Ws_10 m, Ws_15 m and Ws_25 m) (m/s), wind direction (WD_2 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) (℃), photosynthetically active radiation (PAR) (μmol/(s m-2)), average soil temperature (TCAV, ℃), soil heat flux (Gs_1, Gs_2 and Gs_3) (W/m2), soil temperature (Ts_0 cm, Ts_2 cm, Ts_4 cm_1, Ts_4 cm_2, Ts_4 cm_3, Ts_6 cm, Ts_10 cm_1, Ts_10 cm_2, Ts_10 cm_3, Ts_15 cm, Ts_20 cm, Ts_30 cm, Ts_40 cm, Ts_60 cm, Ts_80 cm, Ts_120 cm, Ts_160 cm, Ts_200 cm, Ts_240 cm, Ts_280 cm and Ts_320 cm) (℃), and soil moisture (Ms_2 cm, Ms_4 cm_1, Ms_4 cm_2, Ms_4 cm_3, Ms_6 cm, Ms_10 cm_1, Ms_10 cm_2, Ms_10 cm_3, Ms_15 cm, Ms_20 cm, Ms_30 cm, Ms_40 cm, Ms_60 cm, Ms_80 cm, Ms_120 cm, Ms_160 cm, Ms_200 cm, Ms_240 cm, Ms_280 cm and Ms_320 cm) (%, volumetric water content). Processing and quality control of observed data :(1) ensure 144 pieces of data every day (every 10min), and mark by -6999 in case of data missing;Sensor problem of soil heat flux G1 between December 8, 2016 and December 16, 2016, data missing;(2) excluding the time with duplicate records;(3) data that obviously exceeds the physical significance or the range of the instrument is deleted;(4) the part marked with red letter in the data is the data in question;(5) date and time have the same format, and date and time are in the same column.For example, the time is: 2016-6-10-10:30;(6) the naming rule is: AWS+ site name. For information of hydrometeorological network or station, please refer to Liu et al. (2018), and for observation data processing, please refer to Liu et al. (2011).
LIU Shaomin, LI Xin, CHE Tao, XU Ziwei, ZHANG Yang, TAN Junlei
The data set mainly includes observation data of each tree in the super site, and the observation time is from June 2, 2008 to June 10, 2008. The super site is set around the Dayekou Guantan Forest Station. Since the size of the super site is 100m×100m, in order to facilitate the forest structure parameter survey, the super site is divided into 16 sub-sample sites, and tally forest measurement is performed in units of sub-samples. The tally forest measurement factors include: diameter, tree height, height under branch, crown width in transversal slope direction, crown width in up and down slope direction, and tindividual tree growth status. The measuring instruments are mainly: tape, diameter scale, laser altimeter, ultrasonic altimeter, range pole and compass. The data set also records the center point latitude and longitude coordinates of 16 sub-samples (measured by Z-MAX DGPS). The data set can be used for verification of remote sensing forest structure parameter extraction algorithm. The data set, together with other observation data of the super site, can be used for reconstruction of forest 3D scenes, establishment of active and passive remote sensing mechanism models, and simulation of remote sensing images,etc.
CHEN Erxue, BAI Lina, WANG Bengyu, TIAN Xin, LIU Qingwang, CAO Bin, Yang Yongtian, Zhihai Gao, Bingxiang Tan, GUO Zhifeng, WANG Xinyun, FU Anmin, ZHANG Zhiyu, NI Wenjian, WANG Qiang, BAO Yunfei, WANG Dianzhong, ZHANG Yang, ZHAO Liqiong, LIANG Dashuang, WANG Shunli, ZHAO Ming, LEI Jun, NIU Yun, LUO Longfa
Based on the meteorological data of 105 meteorological stations in and around the Qinghai Tibet Plateau from 1980 to 2019, the National Meteorological Science Data Center of China Meteorological Administration (CMA) was established. By calculating the oxygen content, it is found that there is a significant linear correlation between oxygen content and altitude, y = - 0.0263x + 283.8, R2 = 0.9819. Therefore, the oxygen content distribution map can be calculated based on DEM data grid. Due to the limitation of the natural environment in the Qinghai Tibet Plateau, there are few related fixed-point observation institutions. This data can reflect the distribution of oxygen content in the Qinghai Tibet Plateau to a certain extent, and has certain reference significance for the research of human living environment in the Qinghai Tibet Plateau.
HE Xiaobo, ZHANG Jian, NING Tianxiang, HUANG Xiaoming, JIANG Heng, LIU Shaomin, LI Xin
Canopy conductance (mm s-1) is a sensitive index of forest transpiration response to environmental factors, and is a key parameter in water and carbon exchange model. The data is obtained by expanding the water consumption scale measured by stem sap flow technology to the stand scale to obtain the water consumption of the stand, and then using penman equation to calculate. This data mainly provides basic data for some eco hydrological models.
CHANG Xuexiang
1. Data overview: This data set is the scale meteorological gradient data of qilian station from January 1, 2012 to December 31, 2012 (installed at the end of September 2011).VG1000 gradient observation system carries out long-term monitoring of wind speed, wind direction, air temperature, humidity, radiation and other conventional meteorological elements, and carries out data storage and processing analysis in combination with the data collector with high precision and high scanning frequency. 2. Data content: The main observation factors include four layers of air temperature, humidity and two-dimensional ultrasonic wind, rain and snow volume meter, eight layers of ground temperature, soil moisture content, etc. 3. Space and time range: Geographical coordinates: longitude: longitude: 99° 52’e;Latitude: 38°15 'N;Height: 3232.3 m
CHEN Rensheng, HAN Chuntan
The dataset of soil moisture observations (VWC%) was obtained at the super site (100m×100m) around the Dayekou Guantan forest station on Jun. 5, 2008. The super site was divided into 16 subplots (25m×25m). 10 points were measured by TDR 300 (with the probe 20cm long) at random location in each subplot. The serial number and the cover type of the subplot, the number of the sample points and soil moisture (%) were recorded. Those provide reliable data for the construction of the 3D structure of the forest scene, and for the modeling of active and passive remote sensing mechanisms and the simulation of remote sensing images.
CAO Bin, Yang Yongtian
It is of great significance to carry out the quantitative study on the evapotranspiration of forest vegetation in Qilian Mountain, to correctly understand the hydrological function of the forest ecosystem in Qilian Mountain, to understand the water cycle process and to develop the hydrological model of the watershed, and to make a reasonable forest management plan. Forest evapotranspiration is mainly composed of soil surface evaporation, vegetation transpiration and canopy interception water evaporation. Traditional evapotranspiration research methods can be divided into two categories: actual measurement and estimation. The actual measurement methods include hydrology method, micro meteorology method and plant physiology method; the estimation method is to calculate Evapotranspiration by model, mainly including analysis model and empirical model. However, none of these methods can effectively distinguish forest transpiration from evaporation. The trunk liquid flow method can effectively calculate the transpiration of forest land by measuring the transpiration water consumption of trees. The trunk liquid flow method can effectively calculate the transpiration of forest land by measuring the transpiration water consumption of trees. The transpiration water consumption of Picea crassifolia forest was measured by thermal pulse technique, and the scale was extended to the stand scale to indicate the transpiration water consumption of Picea crassifolia forest.
CHANG Xuexiang
The dataset of snow depth measured by the elevation-graduated snow sticks was obtained in the Binggou watershed foci experimental area from Nov. 11 to 16, 2007, during the pre-observation period. 51 snow-stakes (2m long) were arranged according to different topographic landscapes, such as the flat, ubac, tailo and partial shade, and the length above the ground was recorded. From Mar. 2 to Apr. 6, 2008, the intensive observation period, ten measurements (Mar. 2, Mar. 4, Mar. 9, Mar. 16, Mar. 19, Mar. 21, Mar. 23, Mar. 29, Apr. 1 and Apr. 6) were carried out both manually and additionally by the telescope for the snow depth around the snow-stakes. Two files including raw data and preprocessed snow depth data were archived. Those provide reliable data for snow spatial heterogeneity study and snow accumulation and melt monitoring in the Binggou watershed.
BAI Yunjie, HAO Xiaohua, LI Hongyi
This data set includes the eddy correlation data of Shenshawo Desert Station in the middle reaches of Heihe Hydrometeorological Observation Network from January 1, 2015 to April 12, 2015. The site is located in Zhangye City, Gansu Province, and the underlying surface is desert. The latitude and longitude of the observation point is 100.49330E, 38.78917N, and the altitude is 1594.00m. The height of eddy correlator is 4.6 m, the sampling frequency is 10 Hz, the ultrasonic orientation is positive north, and the distance between the ultrasonic wind speed thermometer (CSAT3) and the CO2/H2O analyzer (Li7500) is 15 cm. The original observation data of the eddy correlation meter is 10 Hz, and the released data is 30-minute data processed by Eddypro software. The main steps of the processing include: outlier removal, time-lag correction, coordinate rotation (double rotation), frequency response correction, ultrasonic virtual temperature correction and density (WPL) correction, etc. At the same time, the quality evaluation of each flux value is conducted, it mainly contains atmosphere state stability test(Δst) and integrated turbulence characteristic test(ITC). The 30-min flux value output by Eddypro software was also screened: (1) data from the instrument error was eliminated; (2) data 1 h before and after precipitation was removed; (3) data from the deletion rate greater than 10% within every 30 min of the 10 Hz raw data. (4) eliminating observation data of weak turbulence at night (u* less than 0.1 m/s). The average time period of observation data is 30 minutes, 48 data per day, and the missing data is labeled -6999. Abnormal data caused by instrument drift and other reasons are marked in red. Published observations include: date/time Date/Time, wind direction Wdir(°), horizontal wind speed Wnd(m/s), lateral wind speed standard deviation Std_Uy(m/s), ultrasonic virtual temperature Tv(°C), water vapor density H2O (g/m3), carbon dioxide concentration CO2 (mg/m3), friction velocity Ustar (m/s), Obukhov length L (m), sensible heat flux Hs (W/m2), latent heat flux LE (W/m2), carbon dioxide flux Fc (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 of 0:00-0:30; the data is stored in *.xls format. 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 includes one scene acquired on (yy-mm-dd) 2012-05-12, covering the Pailugou catchment. This datum is of panchromatic bands, with spatial resolution of 0.5 m. The data product level of this image is L2. WorldView dataset was acquired through purchase.
China Centre for Resources Satellite Data and Application
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 Land Surface Temperature (LST) observations was obtained in the Yingke oasis and Huazhaizi desert steppe foci experimental areas. (1) The time-continuous surface radiative temperature by the automatic thermometer (FOV: 10°; six from BNU with emissivity 0.95; two from Institute of Remote Sensing Applications with emissivity 1.00, observing at nadir at an intervals of one second. The maize canopy, the bare land and the wheat canopy in Yingke oasis maize field, the wheat canopy in Yingke oasis wheat field, the maize canopy in Huazhaizi desert maize field, vegetation and the bare land in Huazhaizi desert No. 1 and 2 plots and three intensive plots (Huazhaizi desert No. 3 plot, the barley field and the maize field near the resort) were measured on May 20, 24, 28, 30 and 31, Jun. 1, 3, 4, 16, 29 and 30, Jul. 1, 7, 9 and 11, 2008. The dataset of ground truth measurement was synchronizing with WiDAS (Wide-angle Infrared Dual-mode line/area Array Scanner), OMIS-II, TM, ASTER, MODIS, Hyperion and CHRIS. Diurnal variation in the radiative temperature was recorded as well. Raw data, blackbody calibrated data and processed data were archived in Excel format. (2) the surface radiative temperature by the handheld infrared thermometer (FOV:1°; accuracy: 0.1°C) in Yingke oasis maize field and wheat field, Huazhaizi desert maize field, No. 1 and 2 plots, and the maize field at the resort on May 20, 28, 30 and 31, Jun. 1, 4, 16 and 29, Jul. 4, 7 and 11, 2008. Besides, the four component temperature was also measured in Yingke oasis maize field and wheat field, Huazhaizi desert maize field. Raw data and processed data on the surface radiative temperature were archived.
CHAI Yuan, CHEN Ling, KANG Guoting, QIAN Yonggang, REN Huazhong, REN Zhixing, WANG Haoxing, WANG Tianxing, YAN Guangkuo, SHU Lele, Liu Qiang, XIA Chuanfu, XIN Xiaozhou, ZHOU Chunyan, SHEN Xinyi, LI Xinhui, YANG Guijun, LI Xiaoyu, HUANG Bo
This data set contains the vortex correlativity data of zhangye wetland station in the middle reaches of heihe hydrometeorological observation network from January 1, 2015 to September 25, 2015.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.The suspicious data caused by instrument drift and other reasons are marked in red. The vortex system Li7500A was calibrated on April 12, 2015, solstice, May 1, 2015, and the data is missing.After September 26, there were many errors in the data due to problems in the power supply and Li7500A. 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), Mr. Hoff length L (m), 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.
LIU Shaomin, LI Xin, CHE Tao, XU Ziwei, REN Zhiguo, TAN Junlei
On August 2, 2012, airborne ground synchronous observation was carried out in plmr quadrats of Yingke oasis and huazhaizi desert. Plmr (polarimetric L-band multibeam radiometer) is a dual polarized (H / V) L-band microwave radiometer, with a center frequency of 1.413 GHz, a bandwidth of 24 MHz, a resolution of 1 km (relative altitude of 3 km), six beam simultaneous observations, an incidence angle of ± 7 °, ± 21.5 °, ± 38.5 °, and a sensitivity of < 1K. The flight mainly covers the middle reaches of the artificial oasis eco hydrological experimental area. The local synchronous data set can provide the basic ground data set for the development and verification of passive microwave remote sensing soil moisture inversion algorithm. Quadrat and sampling strategy: The observation area is located in the transition zone between the southern edge of Zhangye Oasis and anyangtan desert, on the west side of Zhangye Daman highway, and across the trunk canal of Longqu in the north and the south, which is divided into two parts. In the southwest, there is a 1 km × 1 km desert quadrat. Because the desert is relatively homogeneous, here 1 The soil moisture of 5 points (1 point and center point around each side, and several more points can be measured during walking along the road in the actual measurement process) is collected in KM quadrat. The four corner points are 600 m apart from each other except the diagonal direction. The southwest corner point is huazhaizi desert station, which is convenient to compare with the data of meteorological station. On the northeast side, a large sample with an area of 1.6km × 1.6km was selected to carry out synchronous observation on the underlying surface of oasis. The selection of quadrat is mainly based on the consideration of the representativeness of surface coverage, avoiding residential buildings and greenhouses as much as possible, crossing oasis farmland and some deserts in the south, accessibility, and observation (road consumption) time, so as to obtain the comparison of brightness and temperature with plmr observation. Considering the resolution of plmr observation, 11 splines (east-west distribution) were collected at the interval of 160 m in the east-west direction. Each line has 21 points (north-south direction) at the interval of 80 M. four hydraprobe data acquisition systems (HDAS, reference 2) were used for simultaneous measurement. Measurement content: About 230 points on the quadrat were obtained, each point was observed twice, that is to say, two times were observed at each sampling point, one time was inside the film (marked as a in the data record) and one time was outside the film (marked as B in the data record). As the HDAS system uses pogo portable soil sensor, the soil temperature, soil moisture (volume moisture content), loss tangent, soil conductivity, real part and virtual part of soil complex dielectric are observed. No synchronous vegetation sampling was carried out on that day. Data: This data set consists of two parts: soil moisture observation and vegetation observation. The former saves data in vector file format, and the spatial location is the location of each sampling point (WGS84 + UTM 47N). Soil moisture and other measurement information are recorded in attribute file.
WANG Shuguo, MA Mingguo, LI Xin
The dataset of surface roughness was obtained at the super site (100m×100m, pure Qinghai spruce) around the Dayekou Guantan forest station. 25 corner points and 16 center points were collected and each point was measured twice and photos were taken. With the roughness plate 110cm long and the measuring points distance 1cm, the samples were collected along the strip from south to north and from east to west, respectively. The photos were processed using ArcView software; and after geometric correction, surface height standard deviation (cm) and correlation length (cm) could be acquired based on the formula listed on pages 234-236, Microwave Remote Sensing, Vol. II. The roughness data were initialized by the sample name, which was followed by the serial number, the name of the file, standard deviation and correlation length. Each .txt file is matched with one sample photo and standard deviation and correlation length represent the roughness. In addition, the length of 101 radius is also included for further checking. Those provide reliable ground data for improving and verifying the remote sensing algorithms.
BAI Yunjie, CAO Yongpan, CHE Tao, CHEN Ling, Qu Yonghua, ZHOU Hongmin
Correlation data of vegetation functional traits with topographic factors and pastoral animal husbandry activity factors, including: 1) observation data of main functional traits of 2-3 kinds of grassland plants in elevation, slope and slope upward; 2) correlation analysis data of vegetation functional traits and topographic factors; 3) correlation analysis data between vegetation functional traits and livestock activity intensity factors.
ZHAO Chengzhang
The dataset of regimen change statistics was obtained at the hydrological section of the Dayekou watershed reservoir from Jan. 1, 2007 to May 23, 2008. Ten days observations were carried out from Oct. 21, 2007 to Apr. 11, 2008, and diurnal observations from Apr. 15 to Oct. 21, 2007, and from Apr. 16 to May 23, 2008. Data record fields included: inflow (m^3/s), water level (m), impoundment (ten thousand m^3/s), outflow (m^3/s), ten days mean inflow (m^3/s), ten days mean outflow (m^3/s), monthly mean inflow (m^3/s), and monthly mean outflow (m^3/s).
MA Mingguo
In the middle of July and August 2012, mass photosynthesis was determined and the plant species was caragana korshinskii. The mass photosynthesis measurement system is composed of li-8100 closed-circuit automatic soil carbon flux measurement system (li-cor, USA) and an assimilation box designed and manufactured by Beijing liaotai technology co., LTD. Li-8100 is an instrument for soil carbon flux measurement produced by li-cor, USA, which USES an infrared gas analyzer to measure CO2 and H2O concentrations.The length, width and height of the assimilation box are all 50cm.The assimilation box is controlled by li-8100, and the instrument can operate automatically after the measurement parameters are set. The photosynthetic rate of population was calculated according to the following formula: CAP (Canopy growth Rate) is the Photosynthetic Rate of the population (mol CO2•m -- 2•s -- 1).A is the total leaf area (m2) of the plant canopy;VA is the total volume (m3) of the population photosynthesis measurement system, which is the product of the height of the assimilation box from the ground (the distance between the upper edge and the inner ground after the special base is placed), the soil area (0.25 m2) and the sum of the volume of the assimilation box (0.125 m3).Is the change rate of CO2 measured by assimilation chamber (mol CO2•mol -- 1•s -- 1) in the process of population photosynthesis measurement;Is the CO2 change rate (mol CO2•mol -- 1•s -- 1) measured in a 20 cm measuring chamber during the soil respiration measurement process;P is atmospheric pressure (Pa), T is the air temperature in the assimilation chamber (℃), and R is the gas constant (8.314 Pa•m3•mol-1• k-1).N is the conversion coefficient, which means the change rate of CO2 caused by soil respiration in the soil area (SA) covered by the assimilation box and in the total volume (VA) of the population photosynthesis measurement system is converted from the measurement in the 20cm measurement chamber, and calculated according to the following formula: SA is assimilation box cover soil area, 0.25 m2, SC is 20 cm soil area of the measuring chamber cover (0.03 m2), VC is plant roots and soil respiration measurement system of the total volume (m3), to 20 cm measurement chamber high from the ground (after ring on measuring the soil in place along with the internal distance) on the ground and soil area is the product of the (SC) and 20 cm measurement chamber volume (4.82 x 10-3 m3) combined.
SU Peixi
The dataset of ground truth measurements synchronizing with PROBA CHRIS was obtained in the Biandukou foci experimental area on Jun. 22, 2008. Observation items included: (1) quadrates investigation including GPS by GARMIN GPS 76, species by manual cognition, the plant number by manual work, the height by the measuring tape repeated 4-5 times, the chlorophyll content by SPAD 502, the coverage by manual work and the biomass (samples from 0.5m×0.5m) by wet weight and dry weight. Data were archived as Excel files. (2) LAI of maize, desert scrub and the poplar by the fisheye camera (CANON EOS40D with a lens of EF15/28), shooting straight downwards, with exceptions of higher plants, which were shot upwards. Data included original photos (.JPG) and those processed by can_eye5.0 (as Excel files). For more details, see Readme file. (3) ground object spectrum of grassland, barley and the rape by ASD FieldSpec (350～2 500 nm) from BNU, with 20% reference board. Raw data were binary files direct from ASD (by ViewSpecPro), which were recorded daily in detail, and pre-processed data on reflectance were in .txt. (4) BRDF of grassland, barley and the rape by ASD FieldSpec (350～2 500 nm), with 20% reference board. Raw data were binary files direct from ASD (by ViewSpecPro), which were recorded daily in detail. The processed reflectance and transmittivity were archived in .txt files. The dataset includes processed spectrum data, soil moisture, BRDF, quadrates investigation, integrating spheres data on the rape, LAI, CHRIS data and the fisheye camera data.
DING Songchuang, HAO Xiaohua, YU Yingjie
This data is soil evapotranspiration data of subalpine grassland in tianlaochi small watershed of Qilian Mountain. Lysimeter was used to observe soil evapotranspiration and provide basic data for the development of watershed evapotranspiration model. Six repeated experiments were conducted to observe the soil evapotranspiration of subalpine grassland during the whole growing season. At 8:00 and 20:00 every day, use an electronic scale with an accuracy of 1G to weigh the inner barrel. In case of rainfall, observe whether there is leakage in the leakage barrel. If there is leakage, measure the leakage water in the leakage barrel at the same time. Observation instrument: 1) standard 20 cm diameter rain gauge. 2) Lysimeter was made by ourselves (diameter 30.5cm, barrel height 28.5). 3) Electronic balance (accuracy 1g) is used to observe the weight change of lysimeter.
MA Wenying, ZHAO Chuanyan
1. Data overview: This data set is eddy covariance Flux data of qilian station from January 1, 2012 to December 31, 2012. 2. Data content: The observation items are: horizontal wind speed Ux (m/s), horizontal wind speed Uy (m/s), vertical wind speed Uz (m/s), ultrasonic temperature Ts (Celsius), co2 concentration co2 (mg/m^3), water vapor concentration h2o (g/m^3), pressure press (KPa), etc.The data is 30min Flux data. 3. Space and time range: Geographical coordinates: longitude: 99° 52’e;Latitude: 38°15 'N;Height: 3232.3 m
CHEN Rensheng, HAN Chuntan
This dataset contains the flux measurements from the Zhangye wetland station eddy covariance system (EC) in the midstream reaches of the Heihe integrated observatory network from January 1 to December 31 in 2018. The site (100.44640° E, 38.97514° N) was located in the Zhangye City in Gansu Province. The elevation is 1460 m. The EC was installed at a height of 5.2 m, 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 0.25 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. There were 48 records per day, and the missing data were replaced with -6999. Suspicious data were marked in red. Flux data during March 25 to May 10, 2018 were wrong to the sensor malfunction. 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. For more information, please refer to Liu et al. (2018) (for 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
This mesurement aims to obtain the wind direction, wind speed, and disturbance characteristics of the lower atmosphere. The observation period is from 25 June to 17 Septemper, 2012 (UTC+8). Measurement instruments: Germany Scintec MFAS Flat Array Sodar Measurement position: 60 meters northwest of Daman Super Station Measurement period: 25 June to 17 Septemper, 2012. 24 hours of uninterrupted obeservation. Automatically Recorded Data every half hour. Data contents: We obtain one data file every day. The data contents include observation height, wind speed, wind direction, wind speed in east – west direction, wind speed in south – north direction, vertical wind speed, standard deviation of vertical wind speed, backscatter intensity. Remarks: The prectical obsevation height changes with the air water vapor content. Our obsevation point is located in the arid region. The air water vapor content is very low. Therefore the maximum obsevation height is about 300 meters. When it rains or very windy and dusty, the backscatter intensity is very high. Then the data would be miss or only has the vertical wind speed and backscatter intensity.
Wan Bingcheng
The dataset of TIR spectral emissivity was obtained in the arid region hydrology experiment area and A'rou foci experiment area. Observations were by: (1) Spectral emissivity obtained from 102F at 2-25um in cooperation with the handheld infrared thermometer (BNU) for the surface radiative temperature and one au-plating board for downward atmospheric radiation. The radiative transfer equation and TES methods were applied to retrieve emissivity. The grassland and the concrete floor were measured on May, 27, 2008, the wheat field and the maize field at ICBC resort on May, 29, 2008, the concrete floor (multiangle measurements) at ICBC resort on Jun. 3, 2008, the bare soil and the maize leaf in Yingke oasis maize field on Jun. 22, 2008, the maize and wheat canopy in Yingke oasis maize field on Jun. 23, 2008, the rape field in Biandukou experimental area on Jun. 24, 2008, the alfalfa, the saline land, the grassland and the barley land on Jun. 26, 2008, the wheat field and the maize field in Yingke oasis maize field on Jun. 29, 2008, the desert bare land and vegetation (Reaumuria soongorica) in No. 2 Huazhaiai desert plot on Jun. 30, 2008, the rape field and the grassland in Biandukou experimental area on Jul. 6, 2008, and the grassland and the bare land (multiangle) in A'rou experimental area on Jul. 14, 2008. The cold blackbody calibration (*.CBX/*.CBB), the warm blackbody calibration (*.WBX/*.WBB), the ground objects measurements (*.SAX), au-plating board measurements, and the downward atmospheric radiation (*.DWX) were all needed during observation. Moreover, the spectral radiance and emissivity were also archived. The response function of various bands could be acquired by 102F. And then emissivity of 2-25um could be retrieved. Two results of emissivity were developed: one was direct from 102F and the other was retrieved by ISSTES (Iterative spectrally smooth temperature-emissivity separation). Spectral resolution for raw data and proprecessed data was 4cm-1. (2) Spectral emissivity obtained from BOMAN at 2 -13μm in cooperation with the blackbody barrel and the blackbody from Institute of Remote Sensing Applications and the blackbody (BNU). The desert was measured on Jun. 30 and Jul. 1, 2008, A'rou foci experimental area on Jul. 14, 2008, indoor observations on the deep and shallow layer soil, vegetation, small stones, two maize plants from Yingke No.2 (YKYZYMD02) field and one maize plant and bare land from No. 3 (YKYZYMD03)field on on Jul. 16, 2008, Linze experimental area on Jul. 17, 2008, and gobi on Jul. 18, 2008. The sample site, coordinates, time and photos were all archived. During each observation, BOMAN was preheated and the blackbody was set at the predicted target temperature, which would be changed after the infrared radiation of the blackbody was measured by BOMAN. And then the target infrared radiation, the downward atmospheric radiation (reflected by the au-plating board) and the infrared radiation of the blackbody would be measured one by one. Raw data were archived in Igm, and after processed by FTSW500, the result was Rad (radiation). Finally, Rad would be changed into txt files by Matlab programs.
REN Huazhong, CHEN Ling, YAN Guangkuo, DU Yongming, LI Hua, LIU Yani, WANG Heshun, XIAO Qing, ZHOU Chunyan
The dataset of ground truth measurements synchronizing with the airborne WiDAS mission was obtained in 5 quadrates (30 m×30 m) the Biandukou foci experimental area on May 31, 2008. WiDAS, composed of four CCD cameras, one mid-infrared thermal imager (AGEMA 550), and one infrared thermal imager (S60), can acquire CCD, MIR and TIR band data. The simultaneous ground data were the surface radiative temperature and soil moisture. The quadrates were covered with wheat, rape and bare land. The radiative temperature of 25 corner points (located in No. 2, 3, 4 and 5 quadrates) were acquired. (1) the surface radiative temperature by the handheld infrared thermometer; the quadrate of 30 m×30 m was divided into 21 corner points and each point was measured three times; two for the bare land and one for the vegetation if the two coexist. The data included raw data, recorded data and the blackbody calibrated data. (2) soil moisture (0-5cm) by TDR; 16 center points of the subplot (7.5m×7.5m) were measured three times and the data were archived as Excel files. (3) the time-continuous surface radiative temperature by the fixed automatic thermometer (FOV: 10°; emissivity: 0.95), observing straight downwards at intervals of 1s. Raw data, blackbody calibrated data and processed data were archived as Excel files. Four data files were included, the fixed point temperature in No. 2, 3, 4 and 5 quadrates, the radiative temperature by the handheld infrared thermometer, calibration data and the time-continuous data.
CHAI Yuan, KANG Guoting, QIAN Yonggang, REN Huazhong, WANG Haoxing, LIU Xiaocheng, LIANG Wenguang, LI Xiaoyu, HUANG Bo, LUO Zhen
The dataset contains phenological camera observation data collected at the Arou Superstation in the midstream of the Heihe integrated observatory network from June 13 to November 16, 2018. The instrument was developed with data processed by Beijing Normal University. The phenomenon camera integrates data acquisition and data transmission functions. The camera captures high-quality data with a resolution of 1280×720 by looking-downward. The calculation of the greenness index and phenology are following 3 steps: (1) calculate the relative greenness index (GCC, Green Chromatic Coordinate, calculated by GCC=G/(R+G+B)) according to the region of interest, (2) perform gap-filling for the invalid values, filtering and smoothing, and (3) determine the key phenological parameters according to the growth curve fitting (such as the growth season start date, Peak, growth season end, etc.) There are also 3 steps for coverage data processing: (1) select images with less intense illumination, (2) divide the image into vegetation and soil, and (3) calculate the proportion of vegetation pixels in each image in the calculation area. After the time series data is extracted, the original coverage data is smoothed and filtered according to the time window specified by the user, and the filtered result is the final time series coverage. This data set includes relative greenness index (Gcc). Please refer to Liu et al. (2018) for sites information in the Citation section.
Qu Yonghua, XU Ziwei, LI Xin
The dataset of ground truth measurement synchronizing with the airborne WiDAS mission was obtained in the Yingke oasis and Huazhaizi desert steppe foci experimental areas on Jun. 1, 2008. WiDAS, composed of four CCD cameras, one mid-infrared thermal imager (AGEMA 550), and one infrared thermal imager (S60), can acquire CCD, MIR and TIR band data. The simultaneous ground data included: (1) The radiative temperature of maize, wheat and the bare land in Yingke oasis maize field and Huazhaizi desert No. 1 plot by ThermaCAM SC2000 (1.2m above the ground, FOV = 24°×18°). The data included raw data (read by ThermaCAM Researcher 2001), recorded data and the blackbody calibrated data (archived in Excel format). (2) The radiative temperature by the automatic thermometer (FOV: 10°; emissivity: 1.0; from Institute of Remote Sensing Applications), observing straight downwards at intervals of 1s in Yingke oasis maize field. Raw data, blackbody calibrated data and processed data were all archived in Excel format. (3) FPAR (Fraction of Photosynthetically Active Radiation) of maize and wheat by SUNSACN and the digital camera in Yingke oasis maize field. FPAR= (canopyPAR－surface transmissionPAR－canopy reflection PAR+surface reflectionPAR) /canopy PAR; APAR=FPAR* canopy PAR. Data were archived in Excel format. (4) The reflectance spectra by ASD in Yingke oasis maize field (350-2500nm , from BNU, the vertical canopy observation and the transect observation), and Huazhaizi desert No. 1 plot (350-2500nm , from Cold and Arid Regions Environmental and Engineering Research Institute, CAS, the NE-SW diagonal observation at intervals of 30m). The data included raw data (in .doc format), recorded data and the blackbody calibrated data (in Excel format). (5) Maize albedo by the shortwave radiometer in Yingke oasis maize field. R =10H (R for FOV radius; H for the probe height). Data were archived in Excel format. (6) The radiative temperature by the handheld radiometer in Yingke oasis maize field (from BNU, the vertical canopy observation, the transect observation and the diagonal observation), Yingke oasis wheat field (only for the transect temperature), and Huazhaizi desert No. 1 plot (the NE-SW diagonal observation). Besides, the maize radiative temperature and the physical temperature were also measured both by the handheld radiometer and the probe thermometer in the maize plot of 30m near the resort. The data included raw data (in .doc format), recorded data and the blackbody calibrated data (in Excel format). (7) Atmospheric parameters on the playroom roof at the resort by CE318 (produced by CIMEL in France). The underlying surface was mainly composed of crops and the forest (1526m high). The total optical depth, aerosol optical depth, Rayleigh scattering coefficient, column water vapor in 936 nm, particle size spectrum and phase function were then retrieved from these observations. The optical depth in 1020nm, 936nm, 870nm, 670nm and 440nm were all acquired by CE318. Those data include the raw data in .k7 format and can be opened by ASTPWin. ReadMe.txt is attached for detail. Processed data (after retrieval of the raw data) in Excel format are on optical depth, rayleigh scattering, aerosol optical depth, the horizontal visibility, the near surface air temperature, the solar azimuth, zenith, solar distance correlation factors, and air column mass number. (8) Narrow channel emissivity of the bare land and vegetation by the W-shaped determinator in Huazhaizi desert No. 1 plot. Four circumstances should be considered for emissivity, with the lid plus the au-plating board, the au-plating board only, the lid only and without both. Data were archived in Word.
CHEN Ling, HE Tao, REN Huazhong, REN Zhixing, YAN Guangkuo, ZHANG Wuming, XU Zhen, LI Xin, GE Yingchun, SHU Lele, JIANG Xi, HUANG Chunlin, GUANG Jie, LI Li, LIU Sihan, WANG Ying, XIN Xiaozhou, ZHANG Yang, ZHOU Chunyan, LIU Xiaocheng, TAO Xin, CHEN Shaohui, LIANG Wenguang, LI Xiaoyu, CHENG Zhanhui, Liu Liangyun, YANG Tianfu
The dataset of PR2 soil moisture profile observations (10cm, 20cm, 30cm, 40cm, 60cm and 100cm) was obtained in the Linze grassland foci experimental area. The sample points, with various underlying surface and depth were measured by PR2 probe in PR2 quadrate (3Grid×3Grid, 90m×90m) and PR2 line. Observations were carried out from May 31 to Jul. 13, 2008 with exceptions on Jun. 6, 8, 10, 13, 21, 27, 28, 29, Jul. 3 and 12. Data were archived in Excel and Word file. See WATER: Dataset of setting of the sampling plots and stripes in the foci experimental area of Linze station for more information.
CAO Yongpan, CHAO Zhenhua, GE Chunmei, HAN Xujun, HU Xiaoli, HUANG Chunlin, JIANG Xi, LI Hongxing, LIANG Ji, LIU Chao, NIAN Yanyun, WANG Shuguo, WANG Xufeng, WU Yueru, ZHU Shijie, FENG Lei, YU Fan, WANG Jing, LI Xiaoyu
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