The data set contains the observation data of meteorological elements from the Bajitan Gobi Desert Station, which is located along the middle reaches of the Heihe Hydro-meteorological Observation Network, and the data set covers data from January 1, 2014 to December 31, 2014. The station is located in Bajitan, West Zhangye City, Gansu Province, the underlying surface is Gobi. The latitude and longitude of the observation point is 100.3042E, 38.9150N, and the altitude is 1562m. The air temperature and relative humidity sensors are erected 5 and 10 meters above the ground, facing North; the barometer is installed 2 meters above the ground; tipping bucket rain gauge is installed 10 meters above the ground; the wind speed sensors are set 5 and 10 meters above the ground, facing North; the four-component radiometer is installed 6 meters above the ground, facing South; two infrared thermometers are installed 6 meters above the ground, facing South, and the probe orientation is vertical downward; the soil temperature probes are buried respectively at 0cm on the ground surface, 2cm, 4cm, 10cm, 20cm, 40cm, 60cm and 100cm under the ground, they are located 2 meters from the meteorological tower in the North. The soil moisture sensors are buried 2cm, 4cm, 10cm, 20cm, 40cm, 60cm and 100cm under the ground, 2 meters from the meteorological tower in the South; the soil heat flow boards (3 pieces) are buried 6cm under the ground. Observed items include: air temperature and humidity (Ta_5m、RH_5m、Ta_10m、RH_10m) (unit: Celsius, percentage), pressure(Press) (unit:hectopascal), precipitation (Rain) (unit: mm), wind speed (WS_5m、WS_10m) (unit: meter / sec), wind direction (WD_10m) (unit: degree), four-component radiation (DR, UR, DLR_Cor, ULR_Cor, Rn) (unit: watt / square meter), surface radiation temperature (IRT_1, IRT_2) (unit: Celsius) , soil heat flux (Gs_1, Gs_2, Gs_3) (unit: watt / square meter), soil moisture (Ms_2cm、Ms_4cm、Ms_10cm、Ms_20cm、Ms_40cm、Ms_60cm、Ms_100cm) (unit: volumetric water content, percentage), soil temperature (Ts_0cm、Ts_2cm、Ts_4cm、Ts_10cm、Ts_20cm、Ts_40cm、Ts_60cm、Ts_100cm) (unit : Celsius). Processing and quality control of observation data: (1) Ensure 144 data per day (every 10 minutes), if there is missing data, it is marked as -6999. Due to sensor problem, Ms_40cm data between January 1 and March 2 had a large fluctuation, it can only be used as reference. (2) Eliminate moments with duplicate records; (3) Remove data that is significantly beyond physical meaning or beyond the measuring range of the instrument; (4) Data marked by red is debatable; (5) The formats of the date and time are uniform, and the date and time are in the same column. For example, the time is: 2014-6-10 10:30; (6) The naming rule is: AWS + site name. For hydro-meteorological network or site information, please refer to Liu et al. (2018). For observation data processing, please refer to Liu et al. (2011).
0 2020-04-10
The data is digitized from a drawing, the map of developmental degree of desertification in Daqinggou, Keerqin (HORQIN) Steppe (1981). The specific information of this map is as follows: * Chief Editor: Zhu Zhenda * Editor: Feng Yusun * Drawer: Feng Yusun, Yao Fafen, Wang Jianhua, Zhao Yanhua, Li Weimin * Mapping unit: Prepared by Desert Research Office, Chinese Academy of Sciences * Publisher: No * Scale: 1: 50000 * Publication time: No * Legend: Gully Dense Forest, Sparse Woods, Brush, Artificial Woodland, Nursery and Vegetable Garden, Grass Land, Dry Farmland (Dry Farmland), Rejected Farmland, Marsh Land, Shifting Snad-Dunes, Semi-Shifting Sand-Dunes, Semi-Fixed Sand-Dunes ), Fixed Sand-Dunes, Water Area, Rice, Residential, Highway 1. File format and naming The data is stored in ESRI Shapefile format, including the following layers: Desertification map of Daqinggou area in Horqin steppe, rivers, swamps, roads, lakes, residential areas 2. Data desertification attribute fields: Type of desertification (Shape), Grassland (Grassland), Woodland (Woodland), Woodland Density (W_density), Farmland (Farmland) 3. Projection information: Angular Unit: Degree (0.017453292519943295) Prime Meridian: Greenwich (0.000000000000000000) Datum: D_Beijing_1954 Spheroid: Krasovsky_1940 Semimajor Axis: 6378245.000000000000000000 Semiminor Axis: 6356863.018773047300000000 Inverse Flattening: 298.300000000000010000
0 2020-06-11
The data set contains data of three stations in the middle reaches: (1) the eddy related flux observation data of point 4 in the flux observation matrix from May 31 to September 17, 2012. The station is located in the Yingke irrigation area of Zhangye City, Gansu Province, and the underlying surface is the village. The longitude and latitude of the observation point are 100.35753e, 38.87752n and 1561.87m above sea level. The height of the eddy correlator is 4.2m (after August 19, the height of the eddy correlator is adjusted to 6.2m), the sampling frequency is 10Hz, the ultrasonic direction is due north, and the distance between the ultrasonic anemometer and the CO2 / H2O analyzer is 17cm. (2) Eddy related flux data of point 12 in the flux observation matrix from May 28 to September 21, 2012. The site is located in the farmland of Daman irrigation area, Zhangye City, Gansu Province, with corn as the underlying surface. The longitude and latitude of the observation point are 100.36631e, 38.86515n and 1559.25m above sea level. The height of the eddy correlator is 3.5m, the sampling frequency is 10Hz, the ultrasonic direction is north, and the distance between the ultrasonic anemometer and the CO2 / H2O analyzer is 15cm. (3) Eddy related flux data of point 14 in the flux observation matrix from May 30 to September 21, 2012. The site is located in the farmland of Yingke Irrigation District, Zhangye City, Gansu Province, with corn as the underlying surface. The longitude and latitude of the observation point are 100.35310e, 38.85867n and 1570.23m above sea level. The height of the eddy correlator is 4.6m, the sampling frequency is 10Hz, the ultrasonic direction is north, and the distance between the ultrasonic anemometer and the CO2 / H2O analyzer is 15cm. The original observation data of the eddy correlator is 10Hz. The published data is the 30 minute data processed by the edire software. The main processing steps include: outliers elimination, delay time correction, coordinate rotation (secondary coordinate 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 mainly the test of atmospheric stability (Δ st) and turbulence similarity (ITC). The 30min flux value output by edire software was also screened: (1) data in case of instrument error; (2) data in 1H before and after precipitation; (3) data with loss rate greater than 3% in every 30min of 10Hz original data; (4) observation data with weak turbulence at night (U * less than 0.1M / s). The average period of observation data is 30 minutes, 48 data in a day, and the missing data is marked as - 6999. Suspicious data caused by instrument drift and other reasons shall be identified with red font. The published observation data include: date / time, wind direction WDIR (?), horizontal wind speed wnd (M / s), standard deviation of lateral wind speed STD uuy (M / s), ultrasonic virtual temperature TV (℃), 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), two Carbon dioxide flux FC (mg / (M2S)), quality mark of sensible heat flux QA ﹤ HS, quality mark of latent heat flux QA ﹐ Le, quality mark of carbon dioxide flux QA ﹐ FC. The quality identification of sensible heat, latent heat and carbon dioxide flux is divided into three levels (quality identification 0: (Δ st < 30, ITC < 30); 1: (Δ st < 100, ITC < 100); the rest is 2). The meaning of data time, for example, 0:30 represents the average of 0:00-0:30; data is stored in *. XLS format. For station information, please refer to Liu et al. (2015), and for observation data processing, please refer to Liu et al. (2011) and Xu et al. (2013).
0 2020-03-28
The GIPL2.0 frozen soil model was used to simulate the average ground temperature distribution map of the Qinghai-Tibet Engineering Corridor. The model required to synthesize temperature data set of time series. In addition, the temperature data were divided into two phases according to the time spans, which were 1980-2009 and 2010-2015. The data of the first phase were from the Chinese meteorological driving data set (http://dam. Itpcas.ac.cn/rs/?q=data#CMFD_0.1), the data of the second phase were the application of MODIS surface temperature products (MOD11A1/A2 and MYD11A1/A2) with a spatial resolution of 1 km. In addition, the soil type data required by the model came from the China Soil Database (V1.1) and have a resolution of 1 km. At the same time, the topography was also considered. The research area was classified into 88 types based on the measured soil thermophysical parameters and land cover types, and then the simulation was performed. The annual average ground temperature simulation results were compared with the field measured data, and the results showed that they were highly consistent. The simulation results show that the annual average ground temperature is lower than -2.0 °C in high mountain areas such as Kunlun Mountain and Tanggula Mountain, while that in the higher river valleys such as Tuotuohe is above 0 °C. In the high plain areas (such as Beiluhe Basin and Wudaoliang Basin), the annual average ground temperatures are between -2.0 °C and 0 °C. If taking an annual average ground temperature lower than 0 °C as the threshold for the presence or absence of permafrost, the permafrost of the Qinghai-Tibet Engineering Corridor accounts for 78.9% of the entire area. In the meantime, according to the different ground temperatures, the frozen soils of the Qinghai-Tibet Engineering Corridor are divided into four types: low-temperature stable permafrost, low-temperature basically stable permafrost, high-temperature unstable permafrost and high-temperature extremely unstable permafrost.
0 2019-09-13
This data set was acquired by the L & K band airborne microwave radiometer on the morning of April 1, 2008, in the A'rou flight zone. The frequency of L-band is 1.4GHz, and the backsight is 35 degrees to obtain dual polarization (H and V) information; the frequency of K-band is 18.7ghz, and there is no polarization information. The plane took off from Zhangye airport at 8:06 (Beijing time, the same below) and landed at 11:17. 8: 50-10:13 fly from north to south, observe and reserve 10 routes, flight height is about 4100m, flight speed is about 260km / hr. 10: At 20-10:35, Jiafei 6-8 and 6-9 lines completed the observation. The original data is divided into two parts: microwave radiometer data and GPS data. The L and K bands of microwave radiometer are non imaging observations. The digital values obtained from the instantaneous observation are recorded in the text file, and the longitude and latitude as well as the aircraft attitude parameters are recorded in the GPS data. 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, we can connect the microwave observation with GPS record and match the geographic coordinate information for the microwave observation. 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 L band and K band is consistent with that of observation footprint. The reference resolution is: L band, x = 0.3H; K band, x = 0.24h. After the above steps, we can get the products that users can use directly.
0 2020-03-09
This data set contains the eddy correlativity observation data of the downstream desert station of heihe hydrometeorological observation network from January 1, 2016 to December 31, 2016.The station is located in ejin banner, Inner Mongolia.The longitude and latitude of the observation point are 100.9872e, 42.1135n and 1054m above sea level.The frame height of the vortex correlativity instrument is 4.7m, 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 (Li7500) 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.The vortex correlator's Li7500 was calibrated on April 21-22 with missing data.Suspicious data caused by instrument drift, etc., shall be marked in red font. 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 Li et al. (2013), and for observation data processing, please refer to Liu et al. (2011).
0 2020-03-04
This dataset contains the flux measurements from site No.16 eddy covariance system (EC) in the flux observation matrix from 6 June to 17 September, 2012. The site (100.36411° E, 38.84931° N) was located in a cropland (maize surface) in Daman irrigation district, which is near Zhangye, Gansu Province. The elevation is 1564.31 m. The EC was installed at a height of 4.9 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 (Gill&Li7500) was 0.2 m. Raw data acquired at 10 Hz were processed using the Eddypro post-processing software (Li-Cor Company, http://www.licor.com/env/products/ eddy_covariance/software.html), including spike detection, lag correction of H2O/CO2 relative to the vertical wind component, sonic virtual temperature correction, angle of attack 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.
0 2020-06-29
1. The data is digitized in the map of the development degree of desertification in daqintara (1958) from the drawing. The specific information of the map is as follows: * chief editor: zhu zhenda, qiu xingmin * editor: wang yimou * drawing: feng yu-sun, yao fa-fen, wu wei, wang jianhua, wang zhou-long * cartographic unit: desert laboratory, Chinese academy of sciences * publishing house: xi 'an map publishing house, unified isbn: 12461.26 二. The data is stored in ESRI Shapefile format, including the following layers: 1, * desertification development degree map (1958) : desertification1958.shp 2, * double river: river_double-shp 3, * single river: river_single-shp 4, Road: SHP 5, Lake: lake.shp 6, street: Stree. SHP 7, Railway: Railway. SHP 8, forest belt: Tree_networks 9. Residential land: residential. SHP 10. Map: map_margin.shp 三, desertification development degree figure property fields and encoding attribute: (1) desertification degree (Type) : a flow of sand (Semi - shifting Sandy Land), sand form class (Shapes), grass (Grassland), forest Land, Woodland and forest density (W_density), the cultivated Land (Farmland) (2) sand Shapes: Barchan Dunes, Flat Sandy Land, undulated Sandy Land, Vegetated Dunes (3) the grass (Grassland) (4) Woodland: Woodland. (5) woodland density (W_density): Sparse Woodlot (6) Farmland: Dryfarming and Abandoned Farmland, Irrigated Fields
0 2020-03-10
Trough the select tasking, we obtained the WorldView-2 stereo image data in Dayekou Basin production in mid-May 2012. In the same year from July to August, 27 GPS ground control points (GCP) and checkpoints were measured based on the watershed differential GPS control network. Based on the full-field GCPs, the rational polynomial coefficients (RPC) files of WorldView-2 images were corrected in the digital photogrammetry software system. In the stereo model, 60 high-precision tie points evenly distributed were got through image matching technology, and the 1-m and 2-m resolution digital elevation model (DEM) were rapid extracted. Moreover, the DEM was edited in some key areas, such as the shady forest coverage and Dayekou reservoir. The terrain feature points and line data were added to improve the accuracy of the results in large variation of terrain feature. Check points were composed of GPS points and model confidential points, which used for quantitative validation. And they root mean square errors RMSE were 1.9 meters and 1.2 meters respectively, which achieve the requirements of two degree accuracy of 2.0 m at a scale of 1:2000 in high mountains.
0 2019-09-15
Soil moisture, also known as soil humidity. It is the moisture that remains in the pore space of the soil. The main source of soil moisture in Qinghai spruce forest is atmospheric precipitation, which is the only source of water absorption of Qinghai spruce to survive. The data is the soil moisture of Qinghai spruce forest in Pailugou of Heihe River Basin measured by the EM50 soil moisture meter produced in the United States.
0 2019-09-12
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