The survey data of vegetation quadrat in the middle reaches of Heihe River consists of the field survey data in 2013 and 2014, including the vegetation and soil data of the survey quadrat. The data of each survey sample includes the following information: sample longitude and latitude, sample size, elevation, sample overview, plant name, plant height, crown width, coverage, total coverage, number of trees, plant spacing, row spacing, large row spacing, DBH. The soil is divided into 6 layers according to 0-100cm below the ground, which are 0-10cm, 10-20cm, 20-40cm, 40-60cm, 60-80cm and 80-100cm respectively.
0 2020-07-30
The data set include crop height observed at four sample regions, that is the soil moisture control experimental field at Daman county, and the EC plots, the super station, and Shiqiao sample plots at Wuxing village in Zhangye city. 1) Objective Crop height, a key biophysical parameter, was observed for evapotranspiration estimation in regional scale and the retrieval of other biophysical parameters as well as the application in eco-hydrological models. 2) Measurement instrument: Steel tape. 3) Measurement site a. the soil moisture control experimental field at Daman county, Twelve soil water treatments are set. The wheat height are measured on 17, 23 and 29 May, and 3, 9, 14 and 24 June, and 5 and 12 July. b. the EC site Maize height at 14 EC site (EC-2,EC-3,EC-5,EC-6,EC-7,EC-8,EC-9, EC-10, EC-11, EC-12, EC-13, EC-14, EC-15, EC-16) are measured on 14, 21, 25 and 31 May, 7, 13, 23 and 28 June, 3, 13, 18 and 23 July, 3, 12 and 28 August. c. the super station Maize height at the super station is measured on 22 and 28 May, 5, 11, 18, and 25 June, and 1, 8, 15, 22 and 31 July, 9, 15 and 22 August, and 3 and 11 September. d. the Shiqiao sample site Maize height at the Shiqiao village is measured on 17, 22 and 28 May, 4, 11, 17 and 25 June, 1, 8, 15, 22, and 30 July, 8, 16 and 27 August, and 9 September. 4) Data processing The observational data was recorded in the sheets and reorganized in the EXCEL sheets. The time used in this dataset is in UTC+8 Time.
0 2019-09-15
This dataset includes the observational data from 20 September, 2012, through 31 December, 2013, collected by the Cosmic-ray Soil Moisture Observation System (COSMOS), called crs, which waslocated at 100.372° E, 38.856° N and 1557 m above sea level,near the Daman Superstation in the Daman Irrigation District, Zhangye City, Gansu Province. The land cover in the footprint was a maize crop. The bottom of the probe was 0.5 m above the ground, and the sampling interval was 1 hour. The raw COSMOS data include the following: battery (Batt, V), temperature (T, ℃), relative humidity (RH, %), air pressure (P, hPa), fast neutron counts (N1C, counts per hour), thermal neutron counts (N2C, counts per hour), the sample time of fast neutrons (N1ET, s), and the sample time of thermal neutrons (N2ET, s). The distributed data include the following variables: Date, Time, P, N1C, N1C_cor (corrected fast neutron counts) and VWC (volume soil moisture, %), which were processed as follows: 1) Quality control Data were deleted and replaced by -6999 when (a) the battery voltage was less than 11.8 V, (b) the relative humidity exceeded 80% inside the probe box, (c) the samping durationwere less than 59 minutes or greater than 61 minutes and (d) the neutron count differed from the previous value by more than 20%. 2) Air pressure correction An air pressure correction was applied to the quality-controlled raw data according to the equation containedin the equipment manual. 3) Calibration After the quality control and corrections were applied, the soil moisture was calculated using the equation in Desilets et al. (2010), where N0 is the neutron counts above dry soil and the other variables are fitted constants that define the shape of the calibration function. Here, the parameter N0 was calibrated using the in situ observed soil moisture recordedby SoilNET within the footprint. 4) Soil moisture computation Based on the calibrated N0 and corrected N1C, the hourly soil moisture was computed using the equation specified in the equipment manual. For more information, please refer to Liu et al. (2018) (for hydrometeorological observation network or sites information), Zhu et al. (2015) (for data processing) in the Citation section.
0 2020-04-10
The data are soil moisture data of tianlaochi watershed in Qilian Mountain. The TDR probes of soil moisture in the whole watershed were buried on July, 19-august 23, 2013. The positions of these probes can represent the whole tianlaochi watershed. The four altitudes of Picea forest slope, shrub slope, Sabina forest slope and steppe were mainly sampled. The first observation will be carried out on July 19, with an interval of one week. If there is rainfall time, the observation will be carried out on the next day. At the last time of observation, soil samples were taken from all sampling points, and soil mass moisture content was measured in the laboratory, aiming to correct the data observed by TDR probe.
0 2020-03-11
"Heihe River Basin Ecological hydrological comprehensive atlas" is supported by the key project of Heihe River Basin Ecological hydrological process integration research. It aims at data arrangement and service of Heihe River Basin Ecological hydrological process integration research. The atlas will provide researchers with a comprehensive and detailed background introduction and basic data set of Heihe River Basin. The scale of Zhangye irrigation canal system map in Heihe River Basin is 1:2500000, the normal axis is equal to the conic projection, and the standard latitude is 2547 n. Data sources: Zhangye irrigation canal system data of Heihe River Basin, administrative boundary data of one million Heihe River Basin in 2008, and Heihe River Basin in 2009. The channels of Heihe River Basin are mainly distributed in Zhangye, which are divided into five levels: dry, branch, Dou, Nong and Mao.
0 2020-03-05
This data set contains the eddy correlativity observation data from January 1, 2017 to December 31, 2017 at the super station at the upper reaches of 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 rack height of the vortex correlativity meter is 3.5m, the sampling frequency is 10Hz, the ultrasonic orientation is due north, and the distance between the ultrasonic wind speed and temperature meter (CSAT3) and CO2/H2O analyzer (Li7500A) is 15cm. The original observation data of the vortex correlativity instrument is 10Hz, and the published data is the 30-minute data processed by Eddypro software. The main processing steps include: outliers, delay time correction, coordinate rotation (quadratic 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 :(1) data when instrument error was eliminated;(2) data of 1h before and after precipitation are excluded;(3) remove the data with a missing rate of more than 10% in the original 10Hz data within every 30 minutes;(4) the observation data of weak turbulence at night (u* less than 0.1m/s) were excluded.The average observation period was 30 minutes, 48 data per day, and the missing data was marked as -6999.Suspicious data caused by instrument drift and other reasons are marked with red font, in which the calibration data of the vortex system Li7500A from April 13 to April 14 is missing;When 10Hz data is missing due to a problem with the storage card (2.17-2.23, 3.3-4.12), the data will be replaced by the 30-min flux data output by the collector. The published observational data 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,Quality indicator for co2 flux 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 is 2).The meaning of data time, such as 0:30 represents the average of 0:00-0:30;The data is stored in *.xls format. 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).
0 2020-04-10
The dataset of ground truth measurements synchronizing with PROBA CHRIS was obtained in 21 quadrates of the Biandukou foci experimental area on Jul. 18, 2008. Observation items included: (1) GPS by GARMIN GPS 76; (2) species by manual cognition; (3) the plant number by manual work, (4) the height by the measuring tape repeated 4-5 times, (5) the chlorophyll content by SPAD 502; (6) the coverage by manual work; (7) photo taking by Nikon D80 with a lens of Sigma 8mm F3.5 EX DG CIRCULAR FISHEYE, shooting straight downwards at the height of 1.5m; original photos were in JPG format and the processed data in Excel format. (8) the biomass (samples over 0.5m×0.5m) by wet weight and dry weight; as Excel files.
0 2019-09-11
The dataset of diurnal FPAR change observations was obtained in the Yingke oasis foci experimental areas. Observation items included: (1) Maize canopy reflectance spectra by ASD and 50% grey board, leaf SPAD by the chlorophyll meter and leaf photosynthesis by LI-6400 in Yingke oasis maize field on Jul. 5, 2008 (fixed point observations from 10:00-20:00 at intervals of one hour, and half an hour from 16:00) Besides, Photo: photosynthetic rate (µmol CO2 m-2 s-1), Cond: stomatal conductance (mol H2O m-2 s-1), Ci: intercellular CO2 viscosity (µmol CO2 mol-1), Trmmol: transpiration rate (mmol H2O m-2 s-1), VpdL: vapor pressure deficiency of leaves (kPa), Tleaf: leaf temperature (°C), ParIn_µm: active radiation of interior photosynthesis (µmol m-2 s-1), and ParOutµm: active radiation of outdoor photosynthesis (µmol m-2 s-1) were all archived. (2) Maize canopy reflectance spectra, leaf photosynthesis and diurnal FPAR change by ASD (Institute of Remote Sensing Applications), 50% grey board (Institute of Remote Sensing Applications), LI-6400 (Institute of Remote Sensing Applications) and SUNSCAN (Beijing academy of Agriculture and Forestry Sciences). Based on calibration lamp data (serial number: 64831), radiance spectrum on Jul. 9 by 1050 spectrometer (Beijing academy of Agriculture and Forestry Sciences) and 50% grey board and 99% white board calibration data, the spectrum data were preprocessed. Calibration was undertaken in accordance with the following precedures: a) The original DN was converted into radiance and further into readable EXCEL format by the spectrometer-matched calibration lamp data and ASD. b) Solar radiance was got by 99% white board radiance. solar radiance=the reference board radiance/the reference board reflectance. c) Spectrum from Agriculture and Forestry Sciences was sampled at an interval of 1.438nm, which was made into data at 1nm intervals by segmentation interpolation. d) Based on b=16.087a (where a is radiance before fitting and b after fitting), radiance data got by 68731 spectrograph were processed. The original maize leaf photosynthesis data (by LI-6400) were introduced into EXCEL format, diurnal changes of each leaf were archived as one single unit according to leaf classification. Maize FPAR (the fraction of photosynthetically active radiation) was got by FPAR= (canopyPAR-surface transmissionPAR-canopy reflection PAR+surface reflectionPAR) /canopy PAR; APAR= FPAR×canopy PAR. The unit for PAR was µmol m-2 s-1. The data included number (the whole leaf), observation time (hh:mm:ss), upper light (µmol m-2 s-1), upper reflectivity (µmol m-2 s-1), lower light (µmol m-2 s-1), lower reflectivity (µmol m-2 s-1) and Spread: variation coefficients of the probe optical intensity.
0 2019-05-23
The dataset of ground truth measurement synchronizing with PROBA CHRIS was obtained in No. 2 and 3 quadrates of the A'rou foci experimental area on Jun. 23, 2008. Observation items included: (1) quadrates investigation including GPS by GARMIN GPS 76, plant species by manual cognition, the plant number by manual work, the height by the measuring tape repeated 4-5 times, phenology by manual work, the coverage by manual work (compartmentalizing 0.5m×0.5m into 100 to see the percentage the stellera takes) and the chlorophyll content by SPAD 502. Data were archived in Excel format. (2) roughness by the self-made roughness board and the camera. The processed data were archived as .txt files. (3) BRDF by ASD FieldSpec (350~2 500 nm), with 20% reference board and the observation platform made by Beijing Normal University. The processed reflectance and transmittivity were archived as .txt files. (4) LAI of stellera and pasture 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 (in Excel). For more details, see Readme file. Five files were included, spectrum in No.2 quadrate, multiangle observations in No.2 and 3 quadrates, roughness photos in No.2 and 3 quadrates, the fisheye camera observations, and the No.2 and 3 quadrates investigation.
0 2019-09-12
The dataset of ground truth measurement synchronizing with Envisat ASAR was obtained in the arid region hydrological experimental area on Sep. 19, 2007 during the pre-observation period. One scene of Envisat ASAR image was captured on Sep. 19. The data were in AP mode and VV/VH polarization combinations, and the overpass time was approximately at 11:29 BJT. Those provide reliable ground data for remote sensing retrieval and validation of soil moisture from Envisat ASAR image. Observation items included: (1) soil moisture measured by the cutting ring method in Linze reed land, Zhangye farmland, Zhangye gobi, Linze maize land, Linze alfalfa land, Zhangye weather station, and Linze wetland. (2) GPS measured by GARMIN GPS 76 (3) vegetation measurements including the vegetation height, the green weight, the dry weight, the sampling method, and descriptions on the land type, uniformity and dry and wet conditions (4) atmospheric parameters at Daman Water Management office measured by CE318 (produced by CIMEL in France). 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 and can be opened by ASTPWin. ReadMetext files (.txt) is attached for detail. Processed data (after retrieval of the raw data) archived as Excel files 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. (5) roughness measured by the roughness plate together with the digital camera. The coordinates of the sample would be got with the help of ArcView; 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 text files (.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.
0 2019-09-13
Contact Support
Links
National Tibetan Plateau Data CenterFollow Us
A Big Earth Data Platform for Three Poles © 2018-2020 No.05000491 | All Rights Reserved
| No.11010502040845
Tech Support: westdc.cn