This dataset: Editor-in-Chief: Hou Xueyu Drawing: Hou Xueyu, Sun Shizhou, Zhang Jingwei, He Miaoguang. Wang Yifeng, Kong Dezhen, Wang Shaoqing Publishing: Map Press Issue: Xinhua Bookstore Year: 1979 Scale: 1: 4,000,000 It took five years to complete from May 1972 to July 1976. In the process of drawing legends and mapping, referring to the vast majority of vegetation survey data (including maps and texts) after 1949 in China, we held more than a dozen mapping seminars involving researchers from inside and outside the institute. During the layout after the mapping work was completed, many new survey data were added, especially vegetation data in western Tibet. The nature of this map basically belongs to the current vegetation map, including two parts of natural vegetation and agricultural vegetation. The legend of natural vegetation is arranged according to the seven vegetation groups. They are mainly divided according to the appearance of plant communities and certain ecological characteristics. The concept of agricultural vegetation community, like the natural vegetation community, also has a certain life form (appearance, structure, layer), species composition and a certain ecological location. In 1990, the State Key Laboratory of Resources and Environmental Information Systems of the Institute of Geographical Sciences and Resources, Chinese Academy of Sciences completed the digitization of this map, and wrote relevant data description documents. The digitized data also adopt equal product cone projection and can be converted into other projections by GIS software. This data includes a vector file in e00 format, a Chinese vegetation coding design description, a dataset description, a vegetation data layer attribute data table, and a scanned "People's Republic of China Vegetation Map-Brief Description" and other files. Data projection: Projection: Albers false_easting: 0.000000 false_northing: 0.000000 central_meridian: 110.000000 standard_parallel_1: 25.000000 standard_parallel_2: 47.000000 latitude_of_origin: 0.000000 Linear Unit: Meter (1.000000) Geographic Coordinate System: Unknown Angular Unit: Degree (0.017453292519943299) Prime Meridian: Greenwich (0.000000000000000000) Datum: D_Unknown Spheroid: Clarke_1866 Semimajor Axis: 6378206.400000000400000000 Semiminor Axis: 6356583.799999999800000000 Inverse Flattening: 294.978698213901000000
0 2020-06-09
The dataset of ground truth measurements synchronizing with Landsat TM was obtained in the Linze grassland and Linze station foci experimental area on Sep. 23, 2007 during the pre-observation periods, and one scene was captured well. These data can provide reliable ground data for retrieval and validation of land surface temperatures with EO-1 Hyperion remote sensing approaches. Observation items included: (1) the land surface radiative temperature by the hand-held infrared thermometer, which was calibrated; (2) GPS by GARMIN GPS 76; (3) atmospheric parameters at Daman Water Management office measured by CE318 (produced by CIMEL in France). The total optical depth, aerosol optical depth, Rayleigh scattering coefficient, column water vapor in 936 nm, particle size spectrum and phase function were then retrieved from these observations. The optical depth in 1020nm, 936nm, 870nm, 670nm and 440nm were all acquired by CE318. These data include the raw data in .k7 format and can be opened by ASTPWin software. ReadMe.txt is attached for detail. Processed data (after retrieval of the raw data) in Excel contain optical depth, rayleigh scattering, aerosol optical depth, the horizontal visibility, the near surface air temperature, the solar azimuth, zenith, solar distance correlation factors, and air column mass number. (4) ground-based land surface temperature measurements by the thermal imager in the Heihe gobi, west of Zhangye city.
0 2019-09-12
This data set includes the continuous observation data set of soil texture, roughness and surface temperature measured by vehicle borne microwave radiometer from November 19 to 20, 2013 in Wuxing village farmland, Ganzhou District, Zhangye City, Gansu Province. The surface temperature and humidity include four layers of temperature sensor at the soil depth of 1cm, 5cm, 10cm, 20cm, and the observation of soil temperature and soil moisture data at the soil depth of 0-5cm. The time frequency of routine observation of soil temperature and humidity is 5 minutes. Data details: 1. Time: November 19-20, 2013 2. data: Brightness temperature: observed by vehicle mounted multi frequency passive microwave radiometer, including 6.925, 18.7 and 36.5ghz V polarization and H polarization data (10.65ghz band damage) Soil temperature: use sensor installed on dt80 to measure 1cm, 5cm, 10cm, 20cm soil temperature Soil moisture: use h-probe sensor to measure 0-5cm soil moisture, the probe can measure 0-5cm soil temperature at the same time Soil texture: soil samples measured in Beijing Normal University Soil roughness: measured by roughness meter provided by northeast geography 3. Data size: 2.5m 4. Data format:. Xls
0 2020-03-13
The data set contains the location information and soil systematic type data of typical soil samples from the Heihe River Basin from July 2012 to August 2014. The typical soil sample collection method in the Heihe River Basin is representative sampling, which refers to the typical soil types that can be collected in the landscape area, and collects highly representative samples as much as possible. According to the Chinese soil systematic classification, the soil type of each section is divided based on the diagnostic layer and diagnostic characteristics. The sample points are divided into 8 soil orders: organic soil, anthropogenic soil, Aridisol, halomorphic soil, Gleysol, isohumicsoill , Cambisol, Entisol, and 39 sub-categories.
0 2020-07-30
The population data of Zhangye City from 2001 to 2012 include: annual population density and natural population growth rate, Data source: Statistical Bureau of Zhangye City. Statistical yearbook of Zhangye City. 2001-2012, Department of water resources of Gansu Province. Bulletin of water resources of Gansu Province. 2001-2012. Water Affairs Bureau of Zhangye City. Comprehensive annual report of water resources of Zhangye City, 1999-2011
0 2020-07-28
According to the sample survey data, in August 2013, 30 forest plots were set up in the Tianlaochi watershed, with a plot size of 10 m×20 m. The long side of the plot was parallel to the slope of the hillside, including 26 blocks of Picea crassifolia forest. 2 blocks of Sabina Przewalsskii forest and 2 mixed forests of Picea and Sabina. In the plot, the diameter of the breast of each tree (the diameter of the trunk at a height of 1.3 m) is measured by a diameter tape, and the height of each tree and the height under the branches (the height of the first live branch at the lower end of the canopy) is measured by a hand-held ultrasonic altimeter. The north-south direction and the east-west crown width are measured with a tape measure, and the sample site is positioned by differential GPS. The parallel version of HASM-AD algorithm is used to simulate the classified LIDAR point cloud data. DEM is generated from ground points, DSM is generated from all points, and the height of surface features is obtained by differential operation between DSM and DEM. In forest area, it is called Canopy Height Model (CHM). A circular window with a given search radius is used to find the local maximum value on CHM. If the central pixel value is the maximum value, it is determined as the crown vertex. The pixel attribute value of the tree vertex is the tree height, and the spatial resolution is 1m.
0 2019-07-21
The dataset is the HWSD Soil texture data set of the qaidam basin. The data is from the Harmonized World Soil Database (HWSD) constructed by the United Nations food and agriculture organization (FAO) and Vienna institute for international applied systems (IIASA), which was released in version 1.1 on March 26, 2009.The data resolution is 1km.The main soil classification system adopted is fao-90.The main fields in the soil property list include SU_SYM90 (soil name in the FAO90 soil classification system) SU_SYM85(FAO85 classification) T_TEXTURE(top layer soil texture) (19.5);ROOTS: String(deep classification of obstacles to the bottom of the soil);SWR: String (soil moisture content characteristics);ADD_PROP: Real (specific type of soil in a soil unit related to an agricultural use);T_GRAVEL: Real (percent by volume);T_SAND: Real;T_SILT: Real (silt content);T_CLAY: Real;T_USDA_TEX: Real (USDA soil texture classification);T_REF_BULK: Real (soil bulk density);T_OC: Real (organic carbon content);T_PH_H2O: Real T_CEC_CLAY: Real;T_CEC_SOIL: Real (cation exchange capacity of soil) T_BS: Real (basic saturation);T_TEB: Real (commutative base);T_CACO3: Real (carbonate or lime content) T_CASO4: Real (sulfate content);T_ESP: Real (exchangeable sodium);T_ECE: Real.The attribute field beginning with T_ represents the upper soil attribute (0-30cm), and the attribute field beginning with S_ represents the lower soil attribute (30-100cm) (FAO 2009).This data can provide model input parameters for earth system modelers, and agricultural perspectives can be used to study eco-agricultural zoning, food security and climate change.
0 2020-10-10
The dataset is the HWSD Soil texture data set of the qaidam basin. The data is from the Harmonized World Soil Database (HWSD) constructed by the United Nations food and agriculture organization (FAO) and Vienna institute for international applied systems (IIASA), which was released in version 1.1 on March 26, 2009.The data resolution is 1km.The main soil classification system adopted is fao-90.The main fields in the soil property list include SU_SYM90 (soil name in the FAO90 soil classification system) SU_SYM85(FAO85 classification) T_TEXTURE(top layer soil texture) (19.5);ROOTS: String(deep classification of obstacles to the bottom of the soil);SWR: String (soil moisture content characteristics);ADD_PROP: Real (specific type of soil in a soil unit related to an agricultural use);T_GRAVEL: Real (percent by volume);T_SAND: Real;T_SILT: Real (silt content);T_CLAY: Real;T_USDA_TEX: Real (USDA soil texture classification);T_REF_BULK: Real (soil bulk density);T_OC: Real (organic carbon content);T_PH_H2O: Real T_CEC_CLAY: Real;T_CEC_SOIL: Real (cation exchange capacity of soil) T_BS: Real (basic saturation);T_TEB: Real (commutative base);T_CACO3: Real (carbonate or lime content) T_CASO4: Real (sulfate content);T_ESP: Real (exchangeable sodium);T_ECE: Real.The attribute field beginning with T_ represents the upper soil attribute (0-30cm), and the attribute field beginning with S_ represents the lower soil attribute (30-100cm) (FAO 2009).This data can provide model input parameters for earth system modelers, and agricultural perspectives can be used to study eco-agricultural zoning, food security and climate change.
0 2020-04-06
This glacial lake inventory receives joint support from the International Centre for Integrated Mountain Development (ICIMOD) and the United Nations Environment Programme/Regional Resources Centre for Asia and the Pacific (UNEP/RRC-AP), Cold and Arid Region Environmental and Engineering Research Institute (CAREERI). 9. This glacial lake cataloging uses Landsat (TM and ETM), Aster and other remote sensing data. It reflects the current situation of glacial lakes with areas larger than 0.01 km2 in the Himalayas in 2004. 10. Glacial lake catalogue coverage: the Himalayan region, Pumqu (Arun), Rongxer (Tama Koshi), Poiqu (Bhote-Sun Koshi), Jilongcangbu (Trishuli), Zangbuqin (Budhigandaki), Majiacangbu (Humla Karnali) and others. 11. Glacial Lake cataloging includes glacial lake cataloging, glacial lake type, glacial lake orientation, glacial lake width, glacial lake area, glacial lake depth, glacial lake length and other attributes. 12. Data projection information： Projection: Transverse_Mercator False_Easting: 500000.000000 False_Northing: 0.000000 Central_Meridian: 87.000000 Scale_Factor: 0.999600 Latitude_Of_Origin: 0.000000 Linear Unit: Meter (1.000000) Geographic Coordinate System: GCS_WGS_1984 Angular Unit: Degree (0.017453292519943299) Prime Meridian: Greenwich (0.000000000000000000) Datum: D_WGS_1984 Spheroid: WGS_1984 Semimajor Axis: 6378137.000000000000000000 Semiminor Axis: 6356752.314245179300000000 Inverse Flattening: 298.257223563000030000 For a detailed data description, please refer to the data file and report.
0 2020-06-09
The data set includes the river level observation data of No. 4 point in the dense runoff observation of the middle reaches of Heihe River from May 20, 2015 to March 11, 2016. The instrument maintenance was completed again on May 20, 2015. The observation point is located in Heihe bridge, Shangbao village, Jing'an Township, Zhangye City, Gansu Province. The riverbed is sandy gravel with unstable section. The longitude and latitude of the observation point are n39.065 °, e100.433056 °, 1431m above sea level, and 58m wide river channel. In 2012, hobo pressure type water level gauge was used for water level observation with acquisition frequency of 30 minutes; since 2013, sr50 ultrasonic distance meter was used with acquisition frequency of 30 minutes. On June 25, 2014, the instrument was damaged and re purchased. The record was restarted on May 20, 2015. The data includes the following parts: Water level observation, observation frequency 30 minutes, unit (cm); For information of hydrometeorological network or station, please refer to Li et al.(2013), and for observation data processing, please refer to He et al.(2016).
0 2020-03-03
This dataset contains the spectra of white cloth and black cloth obtained in the simultaneous time during the airborn remote sensing which supports the airboren data preprocessing as CASI, SASI and TASI , and the spetra of the typical targets in the middle reaches of the Heihe River Basin. Instruments: SVC-HR1024 from IRSA, ASD Field Spec 3 from CEODE, Reference board Measurement method: the spectra radiance of the targets are vertically measured by the SVC or ASD; before and after the target, the spectra radiance of the reference board is measured as the reference. This dataset contains the spectra recorded by the SVC-HR1024 ( in the format of .sig which can be opened by the SVC-HR1024 software or by the notepad ) and the ASD (in the format of .asd), the observation log (in the format of word or excel), and the photos of the measured targets. Observation time: 15-6-2012, the spectra of typical targets in the EC matrix using SVC 16-6-2012, the spectra of typical targets in the wetland by SVC 29-6-2012, the spectra of typical vegetation and soil in Daman site and Gobi site by ASD 29-6-2012, the spectra of white cloth and black cloth by ASD which is simultaneous with the airborne CASI data 30-6-2012, the spectra of vegetation and soil in the desert by ASD 5-7-2012, the spectra of white cloth and black cloth by ASD which is simultaneous with the airborne CASI data 7-7-2012, the spectra of corn in the Daman site for the research of daily speral variation. 8-7-2012, the spectra of white cloth and black cloth by ASD which is simultaneous with the airborne CASI data 8-7-2012, the spectra of corn in the Daman site by ASD for the research of daily speral variation 9-7-2012, the spectra of corn in the Daman site by ASD for the research of daily speral variation 10-7-2012, the spectra of corn in the Daman site by ASD for the research of daily speral variation 11-7-2012, the spectra of corn in the Daman site by ASD for the research of daily speral variation. The time used in this dataset is in UTC+8 Time.
0 2019-09-15
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