The dataset of ground truth measurements synchronizing with the airborne microwave radiometers (L&K bands) mission was obtained along the sample lines 1, 2, 3, 4, 5 and 6 of the Linze grassland foci experimental area on Jul. 8, 2008. 25 points at intervals of 100m were selected along each line. Simultaneous with the satellite overpass, numerous ground data were collected, soil gravimetric moisture, volumetric moisture, and soil bulk density by the cutting ring, the mean soil temperature from 0-5cm by the probe thermometer, the canopy and the land surface temperature by the hand-held infrared thermometer. See WATER: Dataset of setting of the sampling plots and stripes in the foci experimental area of Linze station for more information.
0 2019-05-23
1. Data overview: Eddy covariance system is a micrometeorological measurement method.It USES the principle of vorticity correlation to measure the material exchange and energy exchange of the atmosphere cushion surface with a fast response sensor.The core of open circuit eddy covariance system is composed of CR1000 data collector, CSAT3 3d ultrasonic wind speed and direction sensor, and li-7500 open circuit CO2/H2O gas analyzer (EC150).The eddy covariance system is a newly purchased instrument of this project, which takes a long time to order. It was installed in early October 2011, and the data is relatively short.This data set is the vorticity covariance data of qilian station from October 1, 2011 to December 31, 2011 at 30min. 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 (mg/m^3), water vapor concentration (g/m^3), pressure press (KPa).The data sampling rate is 10Hz per second. 3. Space and time range: Geographical coordinates: longitude: 99° 52’e;Latitude: 38°15 'N;Height: 3232.3 m
0 2020-03-11
This data is digitized from the `` Map of Desertification Types of Naiman Banner, Kulun Banner, and Horqin Left-wing Rear Banner '' on the drawing.The specific information of this map is as follows: * Chief Editor: Zhu Zhenda * Deputy editors: Liu Shu and Qiu Xingmin * Edit: Feng Yukun * Mapping: Feng Yudi, Zhao Yanhua, Wang Jianhua * Double photo: Li Weimin * Field trip: Zhu Zhenda, Qiu Xingmin, Liu Shu, Shen Jingqi, Feng Yudi, Wang Yimou, Yang Youlin, Yang Taiyun, Wen Zixiang, Liu Yangxuan * Mapping unit: Prepared by Desert Research Office, Chinese Academy of Sciences * Publisher: No * Scale: 1: 300000 * Publication time: No * Legend: undulating undulating sandy loess plain, non-desertified land, grassland, saline-alkali land, woods and shrubs, arable land, mountains, sand dunes File format and naming The data is stored in ESRI Shapefile format, including the following layers: Naiman Banner, Kubian Banner, Kezuohou Banner Desertification Type Map, River, Road, Lake, Railway, Well Spring, Residential Area Data attributes Desertification Grade Vegetation Background Desertified land under development Saline-alkali land Heavily desertified land Woods and shrubs Mountain Strongly developed desertified land Potentially desertified land Lake Non-desertified land Undulating sandy loess plain 2. 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
ET (ET) monitoring is crucial to agricultural water resource management, regional water resource utilization planning and socio-economic sustainable development.The limitations of traditional ET monitoring methods mainly lie in that they cannot observe a large area at the same time and can only be limited to observation points. Therefore, the cost of personnel and equipment is relatively high, and they can neither provide surface ET data, nor provide ET data of different land use types and crop types. Quantitative monitoring of ET can be achieved by using remote sensing. The characteristics of remote sensing information are that it can not only reflect the macroscopic structure characteristics of the earth surface, but also reflect the microscopic local differences. Version 2.0 (second edition) of the surface evapotranspiration data set of the heihe river basin from 2000 to 2013 is based on multi-source remote sensing data and the latest ETWatch model is adopted to estimate the raster image data. Its temporal resolution is monthly scale and the spatial resolution is 1km scale. The data covers the whole basin in millimeters.Data types include monthly, quarterly, and annual data. The projection information of the data is as follows: Albers equal-area cone projection, Central longitude: 110 degrees, First secant: 25 degrees, Second secant: 47 degrees, Coordinates by west: 4000000 meter. File naming rules are as follows: Monthly cumulative ET value file name: heihe-1km_2013m01_eta.tif Heihe represents the heihe river basin, 1km represents the resolution of 1km, 2013 represents the year of 2013, m01 represents the month of January, eta represents the actual evapotranspiration data, and tif represents the data in tif format. Name of quarterly cumulative ET value file: heihe-1km_2013s01_eta.tif Heihe refers to heihe river basin, 1km refers to the resolution of 1km, 2013 refers to 2013, s01 refers to january-march, is the first quarter, eta refers to the actual evapotranspiration data, and tif refers to the data in tif format. Annual cumulative value file name: heihe-1km_2013y_eta.tif Among them, heihe represents heihe river basin, 1km represents the resolution of 1km, 2013 represents the year of 2013, y represents the year, eta represents the actual evapotranspiration data, and tif represents the data in tif format.
0 2020-08-26
The data set of bacterial diversity in Tibetan soil provides the microbial distribution characteristics of the soil surface (0-2 cm) of the Tibetan Plateau. The samples were collected from July 1st to July 15th, 2015, from three types of ecosystems: meadows, grasslands and desert. The soil samples were stored in ice packs and transported to the Ecological Laboratory of the Institute of Tibetan Plateau Research in Beijing. The DNA from the soil was extracted using an MO BIO Power Soil DNA kit. The soil surface samples were stored in liquid nitrogen after collection, shipped to the Sydney laboratory, and then extracted using a Fast Prep DNA kit. The extracted DNA samples adopted 515F (5'-GTGCCAGCMGCCGCGGTAA-3') and 909r (5'-GGACTACHVGGGTWTCTAAT-3') to amplify the 16S rRNA gene fragments. The amplified fragments were sequenced by the Illumina Miseq PE250 method, and the raw data were analyzed using Mothur software. The sequences with poor sequencing quality were first removed; the sequences were sorted, and the chimeric sequences were removed. The similarities between the sequences were then calculated, the sequences with similarities above 97% were clustered into one OTU, and the OTU representative sequence was defined. The OTU representative sequence was compared with the Silva database and identified as level one when the reliability exceeded 80%. The microbial diversities in these data on the Tibetan Plateau were systematically compared, which made them significant to the study of the microbial distribution on the Tibetan Plateau.
0 2020-04-29
In April 1999, Landsat 7 was launched. As a supplement and enhancement to the Landsat series, the sensor it carried was ETM+. The parameters of each band were close to those of Landsat 5, but the resolution of panchromatic band with a resolution of 15m was added, and the resolution of thermal infrared band was improved to 60m. At present, there are 85 ETM + data scenes in heihe river basin.Data acquisition time is 1999-07-07, 1999-09-23 (2 scenes), 1999-10-18, 1999-11-26, 2000-01-20, 2000-04-20, 2000-05-06 (2 scenes), 2000-05-20, 2000-06-14 (2 scenes), 2000-07-07 (2 scenes), 2000-07-08, 2000-08-10, 2000-10-02, 2000-10-11,2000-10-13, 2001-05-25, 2001-07-03, 2001-08-20 (2 king), 2001-10-23, 2002-05-03, 2002-05-28, 2002-06-13, 2002-06-29, 2002-07-24, 2004-12-11, 2005-07-23, 2005-09-09, 2005-10-09, 2006-05-07,2006-05-21, 2006-06-24, 2006-07-26, 2006-08-25, 2006-12-01, 2007-08-12, 2008-01-05, 2008-02-06, 2008-03-25, 2008-05-10, 2008-05-19, 2008-05-28, 2008-06-04, 2008-07-15 (2 scenes), 2008-07-22, 2008-08-16 (4 scenes),2008-08-30, 2008-09-08, 2008-09-15, 2008-09-17, 2008-10-01, 2008-10-10 (2 scenes), 2008-10-19 (3 scenes), 2008-10-26 (3 scenes), 2008-11-02, 2008-11-04 (4 scenes), 2008-11-18, 2008-11-20 (4 scenes), 2008-11-27 (3 scenes), 2008-12-04, 2008-12-062008-12-13 (3 scenes).
0 2020-06-05
This data comes from the Tianlaochi watershed sample plot. The vegetation types of the sample plot are grassland, shrub, Sabina przewalskii and Picea crassifolia. The self-made Lysimeter is mainly used to observe the soil evapotranspiration characteristics in Picea crassifolia forestry. To provide basic data for the development of watershed evapotranspiration model. At about 19:00 every day, an electronic scale with an accuracy of 1g is used to weigh the inner barrel. In case of rain, observe whether there is leakage in the leakage barrel. If there is leakage, measure the leakage amount in the leakage barrel as well. The observation period in 2011 is from May 30 to September 10. The observation period in 2012 is from June 11 to September 10. Observation instrument: 1) standard 20cm diameter rain tube rain gauge. 2) self-made lysimeter (diameter 30.5cm, barrel height 28.5). 3) Electronic balance (accuracy: 0.1g) used to observe the weight change of self-made lysimeter.
0 2020-03-12
The data set contains meteorological element observation data from January 1, 2017 to December 31, 2017 at the downstream mixed forest station of heihe hydrometeorological observation network.The station is located at sidao bridge, dalaihubu town, ejin banner, Inner Mongolia.The longitude and latitude of the observation point are 101.1335e, 41.9903n and 874m above sea level.The air temperature and relative humidity sensors are located at 28m, facing due north.The barometer is installed in the anti-skid box on the ground;Tilting bucket rain gauge installed at 28m;The wind speed and direction sensor is located at 28m, facing due north.The four-component radiometer is installed at 24m, facing due south;Two infrared thermometers are installed at 24m, facing due south and the probe facing vertically downward.Two photosynthetically active radiators were installed at a position of 24m, facing due south, with one probe vertically upward and one probe vertically downward.The soil temperature probe is buried at 0cm of the surface and 2cm, 4cm, 10cm, 20cm, 40cm, 60cm, 100cm, 160cm, 200cm and 240cm underground, 2m to the south of the meteorological tower.The soil water probe is buried 2cm, 4cm, 10cm, 20cm, 40cm, 60cm, 100cm, 160cm, 200cm and 240cm underground, 2m to the south of the meteorological tower.The soil heat flow plates (3 pieces) are buried in the ground 6cm underground, 2m to the south of the meteorological tower. Observation items are: air temperature and humidity (Ta_28m, RH_28m) (unit: c, percentage), pressure (Press) (unit: hundred mpa), precipitation (Rain) (unit: mm), wind speed (WS_28m) (unit: m/s), wind (WD_28m) (unit: degrees), the radiation of four component (DR, UR, DLR_Cor, ULR_Cor, Rn) (unit: watts per square meter), the surface radiation temperature (IRT_1, IRT_2) (unit:C), soil heat flux (Gs_1, Gs_2, Gs_3) (in watts/m2), soil temperature (Ts_0cm, Ts_2cm, Ts_4cm, Ts_10cm, Ts_20cm, Ts_40cm, Ts_60cm, Ts_100cm, Ts_160cm, Ts_200cm, Ts_240cm) (in:C), soil moisture (Ms_2cm, Ms_4cm, Ms_10cm, Ms_20cm, Ms_40cm, Ms_60cm, Ms_100cm, Ms_160cm, Ms_200cm, Ms_240cm) (unit: volumetric water content, percentage), upward and downward photosynthetically active radiation (PAR_up, PAR_down) (unit: micromole/sq.s). 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;Due to the sensor problem, the data of wind speed and infrared temperature between May 26 and July 9, 2017 were 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: 2017-9-1010:30;(6) the naming rule is: AWS+ site name. 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
1. Data overview: This data set is the daily scale groundwater level data of Qilian station from November 1, 2011 to December 31, 2011. In October 2011, two groundwater monitoring wells were arranged in hulugou small watershed. Well 1 is located beside the general control hydrological section of hulugou watershed, with a depth of 12.8m and an aperture of 12cm. Well 2 is located in the east of the Delta, about 100m away from the river, with a depth of 14.7m and an aperture of 12cm. 2. Data content: U20hobo water level sensor is arranged in the groundwater well, which is mainly used to monitor the change of groundwater level and temperature in hulugou small watershed. The data content is the temperature and atmospheric pressure inside the hole, and the data is the daily scale data. 3. Space time scope: Geographic coordinates of well 1: longitude: longitude: 99 ° 53 ′ E; latitude: 38 ° 16 ′ n; altitude: 2974m (near the hydrological section at the outlet of the basin). Geographic coordinates of well 2: longitude: 99 ° 52 ′ E; latitude: 38 ° 15 ′ n; altitude: 3204.1m (east side of the East Branch of the delta).
0 2020-12-23
This dataset contains the flux measurements from the desert station eddy covariance system (EC) in the downstream reaches of the Heihe integrated observatory network from January 1 to December 31 in 2018. The site (100.9872° E, 42.1135° N) was located in the Ejina Banner in Inner Mongolia Autonomous Region. The elevation is 1054 m. The EC was installed at a height of 4.7 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 (CSAT3&Li7500) was 0.15 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 10% 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. Data during May 14 to June 26, 2018 were missing due to the data logger 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 (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.
0 2020-07-25
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