This data was derived from "1: 100,000 Land Use Data of China". Based on Landsat MSS, TM and ETM remote sensing data, 1: 100,000 Land Use Data of China was compiled within three years by a remote sensing scientific and technological team of 19 research institutes affiliated to the Chinese Academy of Sciences, which was organized by the “Remote Sensing Macroinvestigation and Dynamic Research on the National Resources and Environment", one of the major application programs in Chinese Academy of Sciences during the "Eighth Five-year Plan". This data adopts a hierarchical land cover classification system, which divides the country into 6 first-class categories (cultivated land, forest land, grassland, water area, urban and rural areas, industrial and mining areas, residential land and unused land) and 31 second-class categories. This is the most accurate land use data product in our country at present. It has already played an important role in national land resources survey, hydrology and ecological research.
0 2020-06-11
The 30 m / month vegetation index (NDVI / EVI) data set of Heihe River basin provides the monthly NDVI / EVI composite products from 2011 to 2014. This data uses the characteristics of HJ / CCD data of China's domestic satellite, which has both high time resolution (2 days after Networking) and spatial resolution (30 m), to construct multi angle observation data set. The average composite MC method is used as the main algorithm for synthesis, and the backup algorithm uses VI method. At the same time, the main observation angles of the multi-source data set are used as part of the quality descriptor to help analyze the angle effect of the composite vegetation index residue. The remote sensing data acquired every month can provide more angles and more observations than the single day sensor data, but the quality of multi-phase and multi angle observation data is uneven due to the difference of on orbit operation time and performance of the sensor. Therefore, in order to effectively use the multi-temporal and multi angle observation data, before using the multi-source data set to synthesize the vegetation index, the algorithm designs the data quality inspection of the multi-source data set, removing the observation with large error and inconsistent observation. The verification results in the middle reaches of Heihe River show that the NDVI / EVI composite results of the combined multi temporal and multi angle observation data are in good agreement with the ground measured data (R2 = 0.89, RMSE = 0.092). In a word, the 30 m / month NDVI / EVI data set of Heihe River Basin comprehensively uses multi temporal and multi angle observation data to improve the estimation accuracy and time resolution of parameter products, so as to realize the stable standardized products from scratch and better serve the application of remote sensing data products.
0 2020-03-13
This data set contains the eddy correlation-meter observation data from January 1, 2014 to December 31, 2014 at the lower level of the daman superstation in the middle reaches of the heihe hydrometeorological observation network.The station is located in the daman irrigation district of zhangye city, gansu province.The latitude and longitude of the observation point is 100.37223E, 38.85551N, and the altitude is 1556.06m.The rack height of the vortex correlativity meter is 4.5m, 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 17cm. 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, 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), stability Z/L (dimensionless), 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 measurement synchronizing with the airborne microwave radiometers (L&K bands) mission was obtained in the Biandukou foci experimental area on Jul. 4, 2008. Observation items included: (1) the soil temperature by the handheld infrared thermometer from L1 to L8 (1km from one another) in Biandukou and soil moisture by ML2X; nine samples were collected every 200 m along each line (1.6km). (2) 5 quadrates (50cm×50cm) investigations including GPS, the vegetation cover types and the height, the actual numbering, the valve bag numbering, wet weight+the refuse bag (g), dry weight+the envelope (g), the envelope (g) and the photo numbering. The data were archived as Excel files.
0 2019-05-23
The dataset of runoff measuring weir observations at the hydrological section was obtained in the Pailugou watershed foci experiment area during two full years from Oct. 2006 to Oct. 2008. The ice flow measurement and the container aet were used manually. The measurement was carried out every five days from Oct. 2006 to Apr. 2007, three times a day from May to Sep. 2007, every five days from Oct. 2007 to Apr. 2008, once a day from May to Sep. 2008, and every five days during Oct. 2008. Data were archived in Excel format.
0 2019-05-23
Ⅰ. Overview This data set is based on Landsat MSS, TM and ETM Remote sensing data by means of satellite remote sensing. Using a hierarchical land cover classification system, the data divides the whole region into six first-class classifications (cultivated land, forest land, grassland, water area, urban and rural areas, industrial and mining land, residential land and unused land), and 31 second-class classifications. Ⅱ. Data processing description The data set is based on Landsat MSS, TM and ETM Remote sensing data as the base map, the data set projection is set as Alberts equal product projection, the scale is set at 1:24,000 for human-computer interactive visual interpretation, and the data set storage form is ESRI coverage format. Ⅲ. Data content description The data set adopts a hierarchical land cover classification system, which is divided into 6 first-class classifications (cultivated land, forest land, grassland, water area, urban and rural areas, industrial and mining land, residential land and unused land), and 31 second-class classifications. Ⅳ. Data use description The data can be mainly used in national land resources survey, climate change, hydrology and ecological research.
0 2020-03-28
The dataset of ground-based RPG-8CH-DP microwave radiometer and ground truth observations for soil freeze/thaw cycle was obtained in the A'rou foci experimental area from Mar. 10 to 11, 2008. The radiometer was set 4.5m height above a smooth land, which was covered with snow less than 10cm deep. The field of view was roughly determined and not as ideal. Frozen soil was observed clockwise 240° and snow clockwise 270° with the truck head as the 0 degree azimuth; the elevation angle was set at -40° for the former, and from -20° to -70° for the latter. Observation items included surface soil moisture (microwave drying to get the gravimetric moisture), the soil temperature by the thermal resistor and vegetation. The shallow layer of the site was covered with withered grass with exuberant roots underground due to rich organic. The soil temperature changes were reflected by the thermal resistor and recorded by the DataTaker. The brightness temperature was archived as .BRT and .txt files (the ASCII format). Data in two formats were the same. Each row in .txt format was listed by year, month, date, hour, minute, second, 6.925GHz (h), 6.925GHz (v), 10.65GHz (h), 10.65GHz (v) , 18.7GHz (h), 18.7GHz (v), 36.5GHz (h), 36.5GHz (v), the elevation angle, and the azimuth angle. Values for 6.925GHz and 10.65GHz were zero due to disfunction.
0 2019-05-23
This data set contains meteorological element observation data from January 1, 2015 to December 31, 2015 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 and 100cm underground, 2m to the south of the meteorological tower.The soil water probe is buried 2cm, 4cm, 10cm, 20cm, 40cm, 60cm and 100cm 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:(unit: Ts_0cm, Ts_2cm, Ts_4cm, Ts_10cm, Ts_20cm, Ts_40cm, Ts_60cm, Ts_100cm) (unit: Celsius), soil moisture (Ms_2cm, Ms_4cm, Ms_10cm, Ms_20cm, Ms_40cm, Ms_60cm, Ms_100cm) (unit:Volumetric water content, percentage), upward and downward photosynthetically active radiation (PAR_up, PAR_down) (in micromol/m2 seconds). 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 was partly missing between September 28 and November 8, 2015;Infrared temperature 1 data missing between 4.28 and 5.23 due to sensor problem;(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: September 10, 2015, 10:30;(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
This dataset includes seven scenes; two scenes cover the Dayekou catchment on (yy-mm-dd) 2012-08-19 and 2012-08-28, one scene covers the airport desert experimental site on 2012-06-29, three scenes cover the Daman foci experimental area on 2012-06-21, 2012-07-10 and 2012-08-27, and one scene covers the natural oasis eco-hydrology experimental area in the lower reaches of the Heihe River Basin. The data were all acquired around 9:00 (BJT) of full swath mode with data product of Level 1A. PROBA CHRIS dataset was acquired through the European Space Agency (ESA)-Ministry of Science and Technology of China (MOST) Cooperative Dragon 2 (project ID: 5322) and Dragon 3 (project ID: 10649) Programme.
0 2019-09-15
The coverage time of microwave radiometer ice sheet freeze-thaw data set is updated to 2016-2019, with a spatial resolution of 25 km; the remote sensing inversion method based on microwave radiometer adopts the improved wavelet based ice sheet freeze-thaw detection algorithm, which takes into account the change of ice sheet freeze-thaw brightness temperature characteristics in time. First, the long-time brightness temperature data of all ice sheet areas in Greenland is small by using wavelet transform. The multi-scale decomposition of wave is used to analyze the edge information at different scales. Thirdly, the edge information of ice sheet melting and refreezing is separated from the noise by ANOVA. Based on the extracted edge information of long-term brightness and temperature change of ice sheet, the optimal edge threshold of dry snow and wet snow classification is determined by using the generalized Gaussian model, so as to detect the melting area of Greenland ice sheet. Finally, based on the principle of space automatic error correction, the error results caused by noise are detected by using the space neighborhood error correction operator, and the error is corrected manually. The brightness and temperature data of passive microwave in long time series come from SMMR, SSM / I and SSMI / s sensors. To ensure simultaneous interpreting of the brightness temperature of different sensors, simultaneous interpreting of different sensor brightness temperatures is made before freezing and thawing. Through the verification of the actual measurement site, it shows that the detection accuracy of Greenland ice sheet freeze-thaw is more than 70%.
0 2020-01-19
Contact Support
Northwest Institute of Eco-Environment and Resources, CAS
0931-4967287
poles@itpcas.ac.cn
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
