The dataset of ground truth measurement synchronizing with the airborne WiDAS mission and Landsat TM was obtained in the Yingke oasis and Huazhaizi desert steppe foci experimental areas on Jul. 7, 2008. Observation items included: (1) the radiative temperature by the thermal camera (Institute of Remote Sensing Applications) of maize, wheat and the bare land of Yingke oasis maize field at a height of 1.2m above the ground. Optical photos of the scene were also taken. Raw data (read by ThermaCAM Researcher 2001) was archived in IMG format, and blackbody calibrated data and processed data were all archived as Excel files. (2) 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. (3) Reflectance spectra in Yingke oasis maize field by ASD FieldSpec (350-1603nm) from Institute of Remote Sensing Applications (CAS). The grey board and the black and white cloth were also used for calibration on the CCD camera. Raw data were binary files direct from ASD (by ViewSpecPro), and pre-processed data on reflectance were in Excel format. (4) the component temperature by the handheld radiometer in Yingke oasis maize field and Huazhaizi desert maize field. For maize, the component temperature included the vertical canopy temperature, the bare land temperature and the plastic film temperature; for the wheat, it included the vertical canopy temperature, the half height temperature, the lower part temperature and the bare land temperature. The data included raw data (in Word format), recorded data and the blackbody calibrated data (in Excel format). (5) the radiative temperature by the handheld radiometer (emissivity = 1.0) in Yingke oasis maize field (for the canopy mean temperature), Huazhaizi desert maize field (for the transect temperature), Zhangye airport (the black and white cloth for calibration) and Huazhaizi desert No. 2 plot (the diagonal radiative temperature and the radiative temperature of 30m*30m subplot). The component temperature was also measured. The data included raw data (in Word format), recorded data and the blackbody calibrated data (as Excel files). (6) The air temperature (°C) , the soy bean leaf temperature (°C) and the maize leaf temperature (°C) by SPAD (from Institute of Remote Sensing Applications (CAS)) in Yingke oasis maize field. Besides, spectrum, photosynthesis, fluorescence and chlorophyll were measured as well. (7) The leaf reflectance spectra ASD (serial number: 64831) and 50% grey board from Institute of Remote Sensing Applications (CAS). The spectral DN was changed into radiance based on the 50% grey board calibration data and calibration lamp data, which could further be transformed into Excel format. Moreover, the solar radiance=the reference board radiance/the reference reflectance. (8) The leaf fluorescence by ImagingPam from Beijing Academy of Agriculture and Forestry Sciences. YII = (Fm'-F)/Fm' was applied for caculation, F indicating fluorescence before saturating flash light, Fm' the maximum fluorescence before saturating flash light, and YII the quantum yield of photosystem II. Data were archived in pim and could be read by ImagingPam, which can be downloaded from http://www.zealquest.com. (9) The leaf photosynthesis by LI-6400. (10) The radiative temperature by the automatic thermometer (FOV: 10°; emissivity: 0.95), observing straight downwards at intervals of 1s in Yingke oasis maize field and Huazhaizi desert maize field. Raw data, blackbody calibrated data and processed data were all archived in Excel format. (11) FPAR (Fraction of Photosynthetically Active Radiation) 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 the table format of Word. (12) Atmospheric parameters near Daman Water Management office 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 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.
0 2019-09-12
This data set was acquired by K & Ka band airborne microwave radiometer on March 29, 2008, in the Binggou watershed flight zone. Among them, K-band frequency is 18.7ghz, zenith angle observation, no polarization information; Ka band frequency is 36.0ghz, scanning imaging, scanning range ± 12 °, vertical polarization observation. The plane took off from Zhangye airport at 8:49 (Beijing time, the same below) and landed at 12:54. 9: At 25-12:08, 18 routes were flown according to the scheduled design, with a flight altitude of about 5000m and a flight speed of about 220-250km / hr. The original data is divided into two parts: microwave radiometer data and GPS data. The K-band of microwave radiometer belongs to non imaging observation, and the digital value obtained from instantaneous observation is recorded in the text file. Ka band belongs to imaging observation, which is different from L band and K band data. The original record of Ka band is hexadecimal text file. In data processing, the hexadecimal file needs to be converted to decimal system first, and then 112 data (the angle difference of each two data points is 24 / 112 = 0.214 degrees) are collected uniformly within the scanning range of 24 degrees. GPS data record the latitude and longitude of the flight and the aircraft attitude parameters. When using microwave radiometer to observe data, it is necessary to convert the digital value recorded into the bright temperature value according to the calibration coefficient (the calibration coefficient file is filed with the original observation data). At the same time, through the clock records of microwave radiometer and GPS, microwave observation and GPS record can be linked to match the geographical coordinate information for microwave observation. When processing Ka band data, the angle scanning effect should also be considered, and 112 data in the scanning period should be given geographical coordinate information respectively. Due to the coarse observation resolution of microwave radiometer, the effects of aircraft yaw, roll and pitch are generally ignored in data processing. According to the target and flight relative altitude (H), after calibration and coordinate matching, the observation information can also be gridded. The resolution (x) of K-band is consistent with that of observation footprint. The reference resolution is: x = 0.24h; the resolution of Ka band is 39m. After the above steps, we can get the products that users can use directly.
0 2020-03-09
This dataset includes five scenes, covering the artificial oasis eco-hydrology experimental area of the Heihe River Basin, which were acquired on (yy-mm-dd) 2012-04-05, 2012-04-21, 2012-05-07, 2012-06-24, 2012-07-10. The data were all acquired around 11:50 (BJT) with data product of Level 2. Landsat ETM+ dataset was downloaded from http://glovis.usgs.gov/.
0 2020-05-28
The dataset consists of three parts: part 1, survey data of plant plots from 7 tributaries of the upper Shiyan River Basin and the Qingtu Lake in the Qilian Mountains from August 16,2018 to August 30 ,2018; part 2, survey data of plant plots in the main tributaries of Heihe River and Shule River Basins from 2018.9.25 to 2018.10.3 ; part 3, survey data of plant plots in Qinghai Lake and Heihe River Basin from August 18, 2013 to August 8, 2018. The first part involves the growth characteristics and quantity information of herbs, shrubs and trees; the second part mainly investigates trees and only gives a rough estimate of herbs; the third part mainly investigates meadow vegetation. The three-part survey sets up plots based on vegetation types, and at least 3 plots (sub-trees, shrubs, and herbs) are selected for each plot. Among them, the herbaceous aspect product is 1m×1m or 0.5m×0.5m; the desert shrub-like product is 10m×10m; the forest shrub area is 2m×2m; the shrub shrub area is 4m×4m; the arbor-like aspect product is 20m. ×20m. Plant community survey in each sample: the arbor sample survey mainly investigated the number of species, species abundance, 20 arbor trees per wooden ruler (including plant height, DBH, crown width, live branch height), within the sample The diameter of all arbor; the shrub-like method mainly investigated the species number, abundance, shrub crown and shrub plant height of all shrubs; the herb sample mainly investigated the number, degree or coverage of the herbaceous species, average plant height, total coverage, Aboveground biomass.
0 2019-09-14
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 Huazhaizi desert steppe station between 22 September, 2012, and 31 December, 2013. The site (100.319° E, 38.765° N) was located on a desert steppe surface in the Huazhaizi, which is near Zhangye city, Gansu Province. The elevation is 1731 m. There are two equipment in the site, and installed by Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences (CAREERI) and Beijing Normal University (BNU), respectively. The installation heights and orientations of BNU were as follows: two infrared temperature sensors (SI-111; 2.65 m, south, vertically downward), soil heat flux (HFP01; 3 duplicates, -0.06 m), soil temperature profile (AV-10T; 0, -0.02, -0.04, -0.2, -0.6, and -1 m), and soil moisture profile (ML2X; -0.04, -0.2 and -1 m). For the CAREERI installation: air temperature and humidity profile (HMP45C; 1, 1.99 and 2.99 m, north), wind speed profile (03102; 0.48, 0.98, 1.99 and 2.99 m, north), wind direction (03302; 4 m, north), air pressure (PTB210; in waterproof box), rain gauge (CTK-15PC; 0.7 m), four-component radiometer (CNR1; 2.5 m, south), soil temperature profile (107; -0.04, -0.1, -0.18, -0.26, -0.34, -0.42 and -0.5 m), and soil moisture profile (ML2X; -0.02, -0.1, -0.18, -0.26, -0.34, -0.42, -0.5, and -0.58 m, 3 duplicates in -0.02 m). The observations included the following: (1) 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_20 cm, Ts_60 cm and Ts_100 cm) (℃), and soil moisture (Ms_4 cm, Ms_20 cm and Ms_100 cm) (%). (2) air temperature and humidity (Ta_1 m, Ta_1.99 m and Ta_2.99 m; RH_1 m, RH_1.99 m and RH_2.99 m) (℃ and %, respectively), wind speed (Ws_0.48 m, Ws_0.98 m, Ws_1.99 m and Ws_2.99 m) (m/s), wind direction (WD_4 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), soil temperature (Ts_4 cm, Ts_10 cm, Ts_18 cm, Ts_26 cm, Ts_34 cm, Ts_42 cm and Ts_50 cm) (℃), and soil moisture (Ms_2 cm_1, Ms_2 cm_2, Ms_2 cm_3, Ms_10 cm, Ms_18 cm, Ms_26 cm, Ms_34 cm, Ms_42 cm, Ms_50 cm and Ms_58 cm) (%, volumetric water content). The data processing and quality control steps were as follows: (1) The BNU data were averaged over intervals of 10 min, The CAREERI data were averaged over intervals of 30 min. A total of 144 runs per day were recorded in BNU data and 48 records per day in CAREERI data. The BNU data during 30 June, 2013 and 26 July, 2013 were missing during the malfunction of datalogger. 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.
0 2019-09-12
The global Cryosat-2 GDR dataset is generated by the European Space Agency (ESA); it has a temporal coverage from 2010 to 2016 and covers the globe. On April 8, 2010, the ESA launched the Cryosat-2 high-tilt polar orbit satellite. The satellite is equipped with an SAR Interferometer Radar Altimeter (SIRAL), which is mainly used to monitor polar ice thickness and sea ice thickness changes, and, furthermore, to study the effects of melting polar ice on global sea level rise and that of global climate change on Antarctic ice thickness. The altimeter operates in the Ku-band and at a frequency of 13.575 GHz, it includes three measurement modes. One is a low-resolution altimeter measurement mode (LRM) that points to the subsatellite point to obtain all surface observations for land, sea, and ice sheets; its processing is similar to ENVISAT/RA-2, with an orbital resolution of 5 to 7 km. The second is the Synthetic Aperture Radar (SAR) measurement mode, which is mainly used to improve the accuracy and resolution of sea ice observations; it can make the resolution along the orbit reach approximately 250 m. The third is the Interferometric Synthetic Aperture Radar (InSAR), which is mainly used to improve the accuracy of areas with complex terrain such as the edges of ice sheets or ice shelves. The CryoSat -2/SIRAL data products mainly include 0-level data, 1b-level data, 2-level data and high-level data. The Cryosat-2/SIRAL products consist of two files: an XML head file (.HDR) and a data product file (.DBL). The HDR file is an auxiliary ASCII file for fast identification and retrieval of the data files. 1b-level products are stored separately according to the measurement modes, and the data recording formats of different modes are also different. Each waveform in LRM mode and SAR mode has 128 sampling points, while that in SARIn mode has 512 sampling points. 2-level GDR products are available for most scientific applications, including measurement time, geographic location, altitude, and more. In addition, the altitude information in GDR products has been obtained through instrumental calibration, transmission delay corrections, geometric corrections, and geophysical corrections (such as atmospheric corrections and tidal corrections). The GDR products are single global full-track data, that is, the measurement results of the three modes. After different processing, they are combined in chronological order; thereby, the data recording formats are unified. The data in the three modes use different waveform retracking algorithms to obtain altitude values. In the latest updated Baseline C data, the LRM mode data use three algorithms: Refined CFI, UCL and Refined OCOG.
0 2020-12-17
The dataset is a lake distribution map of Tarim River Basin, with a scale of 250000, projection: latitude and longitude, data including spatial data and attribute data, and lake attribute fields: NAME (name of lake) and CODE (lake code)
0 2020-03-31
The EC150 open circuit eddy covariance observation system was set up in the typical Populus euphratica community near ulantuge of Ejina oasis in the lower reaches of Heihe River. The water and heat fluxes of Populus euphratica community from July 2013 to September 2014 were systematically observed.
0 2020-06-01
The dataset investigated the growth status of plants and leaf morphological indexes of single and conjoined red sand and pearl in the middle and lower reaches of heihe river basin in 2013. The growth indexes were crown width, plant height, and biomass of fine roots and thick roots.Leaf shape indicators are: length, width, thickness, and leaf area, volume, etc.The experimental observation indexes are: leaf nitrogen content, water potential, gas exchange data, chlorophyll fluorescence data. Data include: field observation data and explanatory documents.
0 2020-03-05
The application of general circulation models (GCMs) can improve our understanding of climate forcing. In addition, longer climate records and a wider range of climate states can help assess the ability of the models to simulate climate differences from the present. First, we try to find a substitute index that combines the effects of temperature in different seasons and then combine it with the Beijing stalagmite layer sequence and the Qilian tree-ring sequence to carry out a large-scale temperature reconstruction of China over the past millennium. We then compare the results with the simulated temperature record based on a GCM and ECH-G for the past millennium. Based on the 31-year average, the correlation coefficient between the simulated and reconstructed temperature records was 0.61 (with P < 0.01). The asymmetric V-type low-frequency variation revealed by the combination of the substitute index and the simulation series is the main long-term model of China's millennium-scale temperature. Therefore, solar irradiance and greenhouse gases can account for most of the low-frequency variation. To preserve low-frequency information, conservative detrended methods were used to eliminate age-related growth trends in the experiment. Each tree-ring series has a negative exponential curve installed while retaining all changes. The four fields of the combined 1000-yr (1000 AD-2000 AD) reconstructed temperature records derived from stalagmite and tree-ring archives (excel table) are as follows: 1) Year 2) Annual average temperature reconstruction 3) Reconstructed temperature deviation 4) Simulated temperature deviation
0 2020-06-09
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