The 1:1 million wetland data of Guangdong Province (2000) is cut from the "1:1 million wetland data of China". "China 1:100,000 wetland data" mainly reflects the information of marshes and wetlands throughout the country in the 2000s, and is represented by geographical coordinates in decimal scale. The main contents include: types of marshes and wetlands, types of water supply, types of soil, types of main vegetation, and geographical regions.The information classification and coding standard of China sustainable development information sharing system was implemented.Data source of this database: 1:20 swamp map (internal version), 1:500 000 swamp map (internal version) of qinghai-tibet plateau, 1:100 000 swamp survey data and 1:400 000 swamp map of China;The processing steps are as follows: data source selection, preprocessing, marshland element digitization and coding, data editing and processing, establishment of topological relationship, edge-to-edge processing, projection transformation, connection with attribute database such as geographical name and acquisition of attribute data.
0 2020-06-09
The datasets of “Land Cover Map of Heihe River Basin” provide monthly land cover classification data in 2012-2013. The HJ-1/CCD data with both high spatial resolution (30 m) and high temporal (2 days) frequency was used to construct the time series data. The NDVI curves from the time series HJ-1/CCD data can depict the variation of typical land surface. Different land use type has different NDVI curve. Rules were set to extract every land use type information. The datasets of “Land Cover Map of Heihe River Basin” hold the traditional land use types including water bodies, urban and built-up, croplands, evergreen coniferous forests, deciduous broadleaf forests and so on. Crop type classification (including maize, spring wheat, highland barely, rape and so on), snow and ice and glaciers information updates, make the datasets more detailed. Compared with previous land cover map and other products, the classification result of the datasets is visually bette. Especially in middle stream, the accuracy of crop classification is quite high compared with the data from the ground campaign. The accuracy of land cover map of the datasets in 2012 was evaluated using very high spatial resolution remote sensing data within Google Earth and data from campaign, and the overall accuracy can be as high as 92.19%. In a word, the datasets of “Land Cover Map of Heihe River Basin” is not only high in overall accuracy, but also more detailed in crop fine classification. Furthermore, it updated some new classes like glaciers and snow. The datasets of “Land Cover Map of Heihe River Basin” are consequently the classification datasets with the highest accuracy and most detailed information up to now.
0 2019-09-15
The data set contains data from the meteorological gradient observation system of sidaqiao super station downstream of heihe hydrometeorological observation network from January 1, 2017 to December 31, 2017.The station is located in the four Bridges of dalaihubu town, ejin banner, Inner Mongolia.The latitude and longitude of the observation point are 101.1374e, 42.0012n, and 873m above sea level.Air temperature, relative humidity and wind speed sensors are installed at 5m, 7m, 10m, 15m, 20m and 28m, with a total of 6 layers, facing due north.The wind sensor is installed at 15m, facing due north;The barometer is installed in the waterproof box;Dump-type rain gauge installed at 28m;The four-component radiometer is installed at 10m, facing due south;The two infrared thermometers are installed at 10m, facing due south, and the probe is facing vertically down.The two photosynthetic effective radiometers are installed at a location of 10m, facing due south, with the probes pointing vertically up and down, respectively.Part of the soil sensor is installed at 2m to the south of the tower body, in which the soil heat flow plate (self-calibration formal) (3 pieces) is successively buried at 6cm underground;The average soil temperature sensor TCAV is buried 2cm and 4cm underground.The soil temperature probe is buried at 0cm on the surface and 2cm, 4cm, 10cm, 20cm, 40cm, 80cm, 120cm, 160cm and 200cm underground.The soil moisture sensors were embedded in the ground at 2cm, 4cm, 10cm, 20cm, 40cm, 80cm, 120cm, 160cm and 200cm. The observation items are: wind speed (WS_5m, WS_7m, WS_10m, WS_15m, WS_20m, WS_28m) (unit: m/s), wind direction (WD_15m) (unit: degree), air temperature and humidity (Ta_5m, Ta_7m, Ta_10m, Ta_15m, Ta_20m, Ta_28m and RH_5m, RH_7m, RH_10m, RH_15m, RH_20m, RH_28m) (unit: Celsius, percentage), air pressure (Press) (unit:Hundred mpa), precipitation (Rain) (unit: mm), 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), up and down the photosynthetic active radiation (PAR_U_up, PAR_U_down) (unit: second micromoles/m2), the average soil temperature (TCAV) (unit: c), soil heat flux (Gs_1, Gs_2, Gs_3) (unit:W/m2), soil moisture (Ms_2cm, Ms_4cm, Ms_10cm, Ms_20cm, Ms_40cm, Ms_80cm, Ms_120cm, Ms_160cm, Ms_200cm) (unit: volume water content, percentage), soil temperature (Ts_0cm, Ts_2cm, Ts_4cm, Ts_10cm, Ts_20cm, Ts_40cm, Ts_80cm, Ts_120cm, Ts_160cm, Ts_200cm) (unit: Celsius). Processing and quality control of observation data :(1) ensure 144 data per day (every 10min). If data is missing, it will be marked by -6999;(2) eliminate the moments with duplicate records;(3) data that is obviously beyond the physical meaning or the range of the instrument is deleted;(4) the part marked by red letter in the data is the data in question;(5) the format of date and time is uniform, and the date and time are in the same column.For example, the time is: 2017-9-10-10:30;(6) the naming rule is: AWS+ site name. Please refer to Li et al. (2013) for hydrometeorological network or site information, and Liu et al. (2011) for observation data processing.
0 2020-03-05
This dataset contains data on river water level and flow velocity at No.8 in the intensive runoff observation in the middle reaches of Heihe River runoff from January 1, 2014 to December 31, 2014. The observation point is located at Heihe Bridge, Gaotai County, Zhangye City, Gansu Province. The riverbed is sediment and the section is stable. The latitude and longitude of the observation point is N39°23'22.93", N 99°49'37.29", the altitude is 1347 meters, and the river channel width is 210 meters. The water level observation is measured by SR50 ultrasonic range finder with a frequency of 30 minutes. The data declaration includes the following two parts: Water level observation, observation frequency 30 minutes, unit (cm); data covering time period from January 1, 2014 to December 31, 2014; Flow observation, unit (m3); monitoring flow and obtaining water level flow curve according to different water levels. The process of the runoff changing is obtained by observing the water level process. The No. 8 point-Gaotaiqiao section only monitored the water level because the water body of the wetland park basically stopped flowing. The missing data is uniformly represented by the string -6999. For hydrometeorological network or site information, please refer to Li et al. (2013). For observation data processing, please refer to He et al. (2016).
0 2019-09-11
1. Data overview: This data set is the scale artificial evaporation dish and precipitation data of qilian station from January 1, 2013 to December 31, 2013. The artificial evaporator is a 20cm standard evaporator, and the precipitation is a 20cm standard rain gauge. 2. Data content: (1) the evaporation capacity is measured at 20:00 every day with 20 special measuring cups;It is before a day commonly 20 when measure clear water 20 millimeter with special measure cup (original quantity) pour into implement inside, 24 hours hind namely in the same day 20 hour, again measure the water inside implement (allowance), its reduce quantity is evaporation quantity.Namely: evaporation = original quantity - residual quantity.If there is precipitation between 20:00 of the previous day and 20:00 of the same day, the calculation formula is: evaporation = original quantity + precipitation - residual quantity. (2) precipitation is generally observed in two stages, namely once at 8 o 'clock and once at 20 o 'clock each day. In the rainy season, observation periods are increased, and additional measurements are needed when the rainfall is large.The daily rainfall is divided into 8 a.m. of each day, and the precipitation from 8 a.m. to 8 a.m. of the next day is the precipitation of the current day.If it is rain, measure it with 20 special measuring cups. When it snows, only use the outer tube as snow bearing equipment, and then weigh it with an electronic balance (shenyang longteng es30k-12 type electronic balance, the minimum sensible amount is 0.2g). 3. Space and time range: Geographical coordinates: longitude: 99° 53’e; Latitude: 38°16 'N; Height: 2981.0 m
0 2020-03-11
The dataset of survey at the poplar sampling plot was obtained in the Linze station foci experimental area. Observation items included: (1) soil profile moisture and temperature (0-5cm, 0-5cm, 10-20cm, 20-40cm and 40-60cm) with photos measured twice by the cutting ring method (50cm^3, each layer), once by ML2X Soil Moisture Tachometer and the probe thermometer (15cm, twice each layer) on Jun. 3, 2008. Data were archived as Excel files. (2) shallow layer soil moisture (0-5cm) measured once by the cutting ring method (50cm^3, once each point) and twice by ML2X Soil Moisture Tachometer on Jun. 4, 2008. 13 points were selected and data were archived as Excel files. (3) LAI by TRAC on Jul. 20, 2008. Data were archived as Excel files. (4) roughness measured by the roughness plate together with the digital camera. 18 points were selected and data were archived in JPG format format. (5) forest investigation of Populus gansuensis from Jun. 5-13, 2008: coordinates, the diameter at breast height and the crown size by the measuring tape, full height by TruPulse200. 408 trees were selected and data were archived as Excel files. See the metadata record “WATER: Dataset of setting of the sampling plots and stripes in the Linze station foci experimental area” for more information of the quadrate locations.
0 2019-09-12
The data set contains the observation data of meteorological elements from the Dashalong Station,,which is located along the upper reaches of the Heihe Hydro-meteorological Observation Network, and the data set covers data from January 1, 2017 to December 31, 2017. The station is located in Shalong Beach area on the west side of Qilian County, Qinghai Province. The underlying surface is swamp meadow. The latitude and longitude of the observation point is 98.9406E, 38.8399N, and the altitude is 3739m. The air temperature and relative humidity sensors are erected 5 meters above the ground, facing North; the barometer is installed in the pick-proof box on the ground; the tipping bucket rain gauge is erected 10 meters above the ground; the wind speed and direction sensor is set 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, 4cm、10cm、20cm、40cm、80cm、120cm and 160cm under the ground, they are located 2 meters from the meteorological tower in the South; the soil moisture sensors are buried 4cm、10cm、20cm、40cm、80cm、120cm and 160cm 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, 2 meters from the meteorological tower in the South. Observed items include: air temperature and humidity (Ta_5m, RH_5m) (unit: Celsius, percentage), air pressure (Press) (unit: hectopascal), precipitation (Rain) (unit: mm), wind speed (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 temperature (Ts_0cm, Ts_4cm, Ts_10cm, Ts_20cm, Ts_40cm, Ts_80cm, Ts_120cm, Ts_160cm) (unit: Celsius), soil moisture (Ms_4cm , Ms_10cm, Ms_20cm, Ms_40cm, Ms_80cm, Ms_120cm, Ms_160cm) (unit: volumetric water content, percentage). 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. (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: 2017-9-10 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
"Heihe River Basin Ecological hydrological comprehensive atlas" is supported by the key project of Heihe River Basin Ecological hydrological process integration research. It aims at data arrangement and service of Heihe River Basin Ecological hydrological process integration research. The atlas will provide researchers with a comprehensive and detailed background introduction and basic data set of Heihe River Basin. The industrial and mineral resources map of Heihe River Basin is one of the chapters of social economy, with a scale of 1:2500000, positive axis and equal volume conic projection, and standard latitude of 2547 n. Data sources: social and economic data of Heihe River Basin, administrative boundary data of one million Heihe River Basin in 2008, residential area data of Heihe River Basin in 2009.
0 2020-03-05
This dataset contains the flux measurements from the Populus forest station eddy covariance system (EC) in the lower reaches of the Heihe hydrometeorological observation network from 12 July to 31 December, 2013. The site (101.124° E, 41.993° N) was located in the Populus surface, Ejin Banner in Inner Mongolia. The elevation is 876 m. The EC was installed at a height of 22 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 0.17 m. The raw data acquired at 10 Hz were processed using the Edire post-processing software (University of Edinburgh, http://www.geos.ed.ac.uk/abs/research/micromet/EdiRe/), 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), as 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), which represent high-, medium-, and low-quality data, respectively. In addition to the above processing steps, the half-hourly flux data were screened using 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 3% of the 30 min raw record; and (4) data were rejected at night when the friction velocity (u*) was less than 0.2 m/s. There were 48 records per day, and the missing data were replaced with -6999. Suspicious data were marked in red. Due to the CF card storage problem, data during 17 September to 9 December were replaced with the 30 min output flux data in the data logger. 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 *.xls format. 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 2019-09-14
Vegetation index (NDVI) can be used to detect vegetation growth state, vegetation coverage and eliminate some radiation errors. The data set is the NDVI product data synthesized by MODIS in 500 meters and 16 days in the black river basin from 2000 to 2010 after graphic processing, and the no-value zone is -32768.The coordinate system is the longitude and latitude projection, and the spatial range is 96.5E -- 102.5E, 37.5N -- 43N.The data format is GEOTIFF.
0 2020-06-03
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