The dataset of ground truth measurements synchronizing with airborne Polarimetric L-band Multibeam Radiometer (PLMR) mission was obtained in upper reaches of the Heihe River Basin on 1 August, 2012. PLMR is a dual-polarization (H/V) airborne microwave radiometer with a frequency of 1.413 GHz, which can provide multi-angular observations with 6 beams at ±7º, ±21.5º and ±38.5º. The PLMR spatial resolution (beam spot size) is approximately 0.3 times the altitude, and the swath width is about twice the altitude. The measurements were conducted along two transects respectively located at the west and east branches of the Babaohe River and two sampling plots in the A’rou foci experimental area. Along the transects, soil moisture was sampled at every 50 m in the west-east direction. In order to keep the ground measurements following the airborne mission as synchronous as possible in temporal, measurements were made discontinuously. In the A’rou foci experimental area, two sampling plots were identified with areas of 1.5 km × 0.6 km and 0.85 km × 0.6 km. In each plot, soil moisture was sampled at every 50 m in the west-east direction and 100 m in the north-south direction. Steven Hydro probes were used to collect soil moisture and other measurements. Concurrently with soil moisture sampling, vegetation properties were measured at some typical sampling plots. Observation items included: Soil parameters: volumetric soil moisture (inherently converted from measured soil dielectric constant), soil temperature, soil dielectric constant, soil electric conductivity. Vegetation parameters: biomass, vegetation water content, canopy height. Data and data format: This dataset includes two parts of measurements, i.e. soil and vegetation parameters. The former is as shapefile, with measured items stored in its attribute table. The measured vegetation parameters are recorded in an Excel file.
0 2019-09-14
This dataset includes data recorded by the Hydrometeorological observation network obtained from an observation system of Meteorological elements gradient of A’rou Superstation between 14 October, 2012, and 31 December, 2013. The site (100.464° E, 38.047° N) was located on a cold grassland surface in the Caodaban village, A’rou Town, Qilian County, Qinghai Province. The elevation is 3033 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (HMP45C; 1, 2, 5, 10, 15 and 25 m, towards north), wind speed profile (010C; 1, 2, 5, 10, 15 and 25 m, towards north), wind direction profile (020C; 2 m, towards north), air pressure (CS100; 2 m), rain gauge (TE525M; 5 m, towards south), four-component radiometer (CNR4; 5 m, towards south), two infrared temperature sensors (SI-111; 5 m, towards south, vertically downward), photosynthetically active radiation (PAR-LITE; 5 m, towards south, vertically upward), soil heat flux (HFP01SC; 3 duplicates, -0.06 m, 2 m in the south of tower), a TCAV averaging soil thermocouple probe (TCAV; -0.02, -0.04 m, 2 m in the south of tower), soil temperature profile (109; 0, -0.02, -0.04, -0.06, -0.1, -0.15, -0.2, -0.3, -0.4, -0.6, -0.8, -1.2, -1.6, -2, -2.4, -2.8 and -3.2 m, 3 duplicates in -0.04 m and -0.1 m), and soil moisture profile (CS616; -0.02, -0.04, -0.06, -0.1, -0.15, -0.2, -0.3, -0.4, -0.6, -0.8, -1.2, -1.6, -2, -2.4, -2.8 and -3.2 m, 3 duplicates in -0.04 m and -0.1 m). 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). 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 AWS data were averaged over intervals of 30 min before 4 December, 2012 for a total of 48 records per day). The average soil temperature, soil heat flux, soil temperature and soil moisture were missing during 30 November, 2012 and 8 December, 2012, 21 April, 2013 and 31 May, 2013 because of insufficient power supply; Wind speed in 2 m and 5 m were missing during 28 December, 2012 and 28 March, 2012 because of datalogger repairing. 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) 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).
0 2020-04-10
On 26 July 2012, a Wide-angle Infrared Dual-mode line/area Array Scanner (WIDAS) carried by the Y-12 aircraft was used in a visible near Infrared thermal Dual-mode airborne remote sensing experiment, which is located in the artificial oasis eco-hydrology experimental area (5×5 km). WIDAS includes an CCD cameras with spatial resolution 0.2 m, a visible near Infrared multispectral camera with five bands scanner (an maximum observation angle 48° and spatial resolution 1 m), and a thermal image camera with spatial resolution 4.8 m. The CCD camera data are recorded in DN values processed by mosaic and orthorectification. The multispectral camera data are recorded in reflectance processed by atmospheric and geometric correction. Thermal image camera data are recorded in radiation brightness temperature processed by atmospheric and geometric correction.
0 2019-09-15
This dataset uses daily temperature data from SMMR (1978-1987), SSM/I (1987-2009) and SSMIS (2009-2015). It is generated by the dual-index (TB, 37v, SG) freeze-thaw discrimination algorithm. The classification results include the frozen surface, the thawed surface, the deserts and water bodies. The data coverage is the main part of China’s mainland, with a spatial resolution of 25.067525 km via the EASE-Grid projection method, and it is stored in ASCIIGRID format. All the ASCII files in this data set can be opened directly with a text program such as Notepad. Except for the head file, the body content is numerically characterized by the freeze/thaw status of the surface soil: 1 for frozen, 2 for thawed, 3 for desert, and 4 for precipitation. If you want to use the icon for display, we recommend using the ArcView + 3D or Spatial Analyst extension module for reading; in the process of reading, a grid format file will be generated, and the displayed grid file is the graphical expression of the ASCII file. The read method comprises the following. [1] Add the 3D or Spatial Analyst extension module to the ArcView software and then create a new View. [2] Activate View, click File menu, and select the Import Data Source option. When the Import Data Source selection box pops up, select ASCII Raster in the Select import file type box. When the dialog box for selecting the source ASCII file automatically pops up, click to find any ASCII file in the data set, and then press OK. [3] Type the name of the Grid file in the Output Grid dialog box (it is recommended that a meaningful file name is used for later viewing) and click the path to store the Grid file, press OK again, and then press Yes (to select integer data) and Yes (to put the generated grid file into the current view). The generated files can be edited according to the Grid file standard. This completes the process of displaying an ASCII file into a Grid file. [4] In the batch processing, the ASCIGRID command of ARCINFO can be used to write AML files, and then use the Run command to complete the process in the Grid module: Usage: ASCIIGRID <in_ascii_file> <out_grid> {INT | FLOAT}. The production of this data is supported by the following Natural Science Foundation Projects: Environmental and Ecological Science Data Center of West China (90502010), Land Data Assimilation System of West China (90202014) and Active and Passive Microwave Radiation Transmission Simulation and Radiation Scattering Characteristics of the Frozen Soil (41071226).
0 2020-01-09
The data set includes the observation data of river water level and velocity at NO.5 point in the dense runoff observation of the middle reaches of Heihe River from January 1 to April 30, 2014 and from July 18 to July 26, 2014,. The observation point is located in Heihe bridge, Banqiao Township, Linze County, Zhangye City, Gansu Province. The riverbed is sandy gravel with unstable section. The longitude and latitude of the observation point are n39 ° 15'32.41 ", E100 ° 16'33.95", with an altitude of 1398 meters and a channel width of 270 meters. In 2014, the water level was observed by sr50 ultrasonic distance meter with acquisition frequency of 30 minutes. During the observation period, the instrument failure was returned to the factory for maintenance, and the failure was not eliminated after later installation.
0 2020-03-03
The dataset focuses on the distribution of sampling plots and stripes in the Yingke oasis and Huazhaizi desert steppe foci experimental areas. (1) YKLZYMD-the maize field plot (180m×180m) at Yingke Weather Station It matches No. 10 flight route. Five subplots were selected, including three maize subplots and 2 wheat subplots. The maize subplots, labeled as YKLZYMD01, YKLZYMD02 and YKLZYMD03, were planted in different directions with a ridge sturctrue, which was composed of single row of maizes and bare soils. The distance of adjacent maize rows, as well as the width of bare soil was 0.5m . YKLZYMD05 (2.46m×1m, along the ridge) was located in the northwest of the plot and interplanted with wheat and soy bean. YKLZYMDD06 was exclusively wheat, and 10 rows (1.5m) vertical to the ridge and 1m along the ridge were measured. This is a key experimental area for canopy spectrum, component reflectance spectra, BRDF, albedo, the photosynthetic rate, FPAR, structural parameters, vegetation coverage, the radiative temperature, surface emissivity, atmospheric parameters and soil moisture. (2) YKXMD-Yingke wheat plot (180m×170m) It matches No. 11 flight route. Wheat and maize were interplanted. Three subplots with the same size (3.4m * 3.4m) were selected for the measurement of vegetaion structural parameters, BRDF, the radiative temperature, vegetation coverage and soil moisture. (3) HZZHMZYMD-Huazhaizi maize plot (240m×240m) It is located between No. 9 and No. 10 flight routes. The maize seed dominates, and wheat, alfalfa and tomatoes were planted. 4 maize subplots and one wheat subplot were chosen to collect the canopy temperature, spectrum, structural parameters and vegetation coverage. (4) HZZHMYD1-Huazhaizi desert No. 1 plot (240m×240m) It is located within No. 4 flight route. 3 subplots (30m×30m) were chosen for reflectance spectra, BRDF, vegetation coverage, emissivity, the radiative temperature, soil moisture, atmospheric parameters by sunphotometer CE318 and surface roughness. In cooperation with experiments in Huazhaizi desert plots and Yingke weather station, simultaneous airborne multiangular thermal infrared camera&CCD-ground observations, simultaneous airborne hyperspectral imager (OMIS)-ground observations, simultaneous OMIS/TM/ASTER/Hyperion/CHRIS/ASAR-ground observations were all accomplished. (5) HZZHMYD2-Huazhaizi desert No. 2 plot It matches No. 5 flight route. Three subplots (10m×10m) for coverage and the radiative temperature and one (30m×30m) for simultaneous temperature and spectrum were chosen. (6) HZZHMYD3-Huazhaizi desert No. 3 plot (30m×30m) It is an intensive plot without simultaneous airporne or spaceborne measurement. (7) DJCYMYD-the maize field at the resort It is an intensive plot (30m×30m) with the maize seeds, mainly for the measurement of radiative temperature and soil moisture. (8) DJCDMD-the barley field at the resort It is mainly for radiative temperature data. (9) DJCDBC-the calibration field at the resort It is located at the ICBC resort. The reflectance spectra of the basketball court, the pool and the vegetation were collected used for radiative calibration of CCD camera in visible and near infrared spectra range. The dataset also includes geographic infomation of each sample point.
0 2019-05-23
This glacial lake inventory is supported by the International Centre for Integrated Mountain Development (ICIMOD) and the United Nations Environment Programme/Regional Resource Centre, Asia and The Pacific (UNEP/RRC-AP). 1. The glacial lake inventory incorporates topographic map data and reflects the status of glacial lakes in the region in 2000. 2. The spatial coverage of the glacial lake inventory is as follows: Pa Chu Sub-basin, Mo Chu Sub-basin, Thim Chu Sub-basin, Pho Chu Sub-basin, Mangde Chu Sub-basin, Chamkhar Chu Sub-basin, Kuri Chu Sub-basin, Dangme Chu Sub-basin, Northern Basin, etc. 3. The glacial lake inventory includes the following data fields: glacial lake code, glacial lake types, glacial lake orientation, glacial lake width, glacial lake area, glacial lake depth, glacial lake length, etc. 4. Data projection: Projection: Polyconic Ellipsoid: Everest (India 1956) Datum: Indian (India, Nepal) False easting: 2,743,196.4 False northing: 914,398.80 Central meridian: 90°0'00'' E Central parallel: 26°0'00'' N Scale factor: 0.998786 For a detailed description of the data, please refer to the data file and report.
0 2020-06-09
The evapotranspiration and soil evapotranspiration of lycium rubra and red sand of small shrubs in typical desert weather were observed by using infrared gas analyzer to measure water vapor flux. The measurement system consists of li-8100 closed-circuit automatic measurement of soil carbon flux (li-cor, USA) and an assimilation box designed and manufactured by Beijing ligotai technology co., LTD. Li-8100 is an instrument produced by li-cor for soil carbon flux measurement. It USES an infrared gas analyzer to measure the concentration of CO2 and H2O.The length, width and height of the assimilation box are all 50cm.The assimilation box is controlled by li-8100. After setting up the measurement parameters, the instrument can run automatically.
0 2020-03-10
Wildfires can strongly affect the frozen soil environment by burning surface vegetation and soil organic matter. Vegetation affected by fire can take many years to return to mature pre-fire levels. In this data set, the effects of fires on vegetation regrowth in a frozen-ground tundra environment in the Anaktuvuk River Basin on the North Slope of Alaska were studied by quantifying changes in C-band and L-band SAR backscatter data over 15 years (2002-2017). After the fire, the C- and L-band backscattering coefficients increased by 5.5 and 4.4 dB, respectively, in the severe fire area compared to the unburned area. Five years after the fire, the difference in C-band backscattering between the fire zone and the unburned zone decreased, indicating that the post-fire vegetation level had recovered to the level of the unburned zone. This long recovery time is longer than the 3-year recovery estimated from visible wavelength-based NDVI observations. In addition, after 10 years of vegetation recovery, the backscattering of the L-band in the severe fire zone remains approximately 2 dB higher than that of the unburned zone. This continued difference may be caused by an increase in surface roughness. Our analysis shows that long-term SAR backscattering data sets can quantify vegetation recovery after fire in an Arctic tundra environment and can also be used to supplement visible-wavelength observations. The temporal coverage of the backscattering data is from 2002 to 2017, with a time resolution of one month, and the data cover the Anaktuvuk River area on the North Slope of Alaska. The spatial resolution is 30~100 m, the C- and L-band data are separated, and a GeoTIFF file is stored every month. For details on the data, see SAR Backscattering Data of the Anaktuvuk River Basin on the North Slope of Alaska - Data Description.
0 2020-07-28
The dataset of ground truth measurement synchronizing with the airborne microwave radiometers (L&K bands) mission was obtained in the Biandukou foci experimental area on May 25, 2008. Observation items included: (1) the soil temperature in L1, L2, L3, L4, L5, L6 and L7; (2) roughness measured by the roughness grid board and collected by the digital camera. Files with "result" field were processed data, in which the first row was RMS height (cm; one value), the second row was distance (cm), and the third row was correlation function (cm; changed into correlation length when it is 1/e). (3) GPR and TDR data. Five files were included, roughness photos and preprocessed data, the soil temperature, coordinates of quadrates and sampling lines, GPR and microwave radiometer data. All were archived as Excel and .txt files. Those provide reliable ground data for development and validation of soil moisture and freeze/thaw algorithms from active remote sensing approaches.
0 2019-05-23
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