The land use / land cover data set of Heihe River Basin in 2011 is the Remote Sensing Research Office of Institute of cold and drought of Chinese Academy of Sciences. Based on the remote sensing data of landsatm and ETM in 2011, combined with field investigation and verification, a 1:100000 land use / land cover image and vector database of Heihe River Basin is established. The data set mainly includes 1:100000 land use graph data and attribute data in the lower reaches of Heihe River Basin. The land cover data of 1:100000 (2011) in Heihe River Basin and the previous land cover are classified into six first-class categories (cultivated land, forest land, grassland, water area, urban and rural residents, industrial and mining land and unused land) and 25 second-class categories by the same hierarchical land cover classification system. The data type is vector polygon and stored in shape format.
0 2020-07-30
The dataset of ground truth measurements synchronizing with Envisat ASAR was obtained in No. 1 and 2 quadrates of the Biandukou foci experimental area on Oct. 18, 2007, during the pre-observation period. The ASAR data were in AP mode and VV/VH polarization combinations, and the overpass time was approximately at 11:17 BJT. Both the quadrates were divided into 3×3 subsites, with each one spanning a 30×30 m2 plot. 25 sampling points were chosen, including centers and corners. Simultaneous with the satellite overpass, numerous ground data were collected: the soil temperature , volumetric soil moisture (cm^3/cm^3), soil salinity (s/m), soil conductivity (s/m) by the Hydra probe, the surface radiative temperature by the handheld infrared thermometer, gravimetric soil moisture, volumetric soil moisture, and soil bulk density by drying soil samples from the cutting ring (100cm^3). Meanwhile, vegetation parameters as height, coverage and water content were also observed. Those provide reliable ground data for the development and validation of soil moisture, soil freeze/thaw algorithms and the forward model from active remote sensing approaches.
0 2019-09-12
SPAC system is a comprehensive platform for observation of plant transpiration water consumption and environmental factors. In this project, a set of SPAC system is set up in the Alxa Desert eco hydrological experimental study. The main observation data include temperature, relative humidity, precipitation, photosynthetic effective radiation, etc. the sampling frequency is one hour. This data provides basic data support for the study of plant transpiration water environmental response mechanism.
0 2020-03-06
The dataset of airborne WiDAS mission was obtained in the Zhangye-Yingke-Huazhaizi flight zone on Jun. 1, 2008. Data available for general users include Level-2C data (after geometric, radiometric and atmospheric corrections). Level-1B browse image (after intra-band matching) and Level-2B browse image (intra-band after registration). The raw data, Level-1A, and data processing parameters were filed; applications would be evaluated prior to access. Data processing started Aug. 2008 and ended Apr. 2009, and in Nov. 2009, CCD data were reprocessed to adjust radiometric calibration. The raw data set included 12 flight routs, some of which were repeated. There was discrepancy about 1.4s between exposure time of CCD images at 650nm/750nm and that of 550nm/700nm. Images in different bands has been matched during pre-processing. However, in areas with large elevation changes, intra-bands match error still existed. The flying time of each route was as follows: {| ! id ! flight ! relative height ! starttime ! endtime ! data size ! data state ! data quality ! ground targets |- | 1 || 3#15 || 1500m || 13:35:46 || 13:39:37 || 59 || incomplete || incomplete |- | 2 || 3#13 || 1500m || 13:43:21 || 13:51:33 || 75 || incomplete || incomplete |- | 3 || 3#11 || 1500m || 13:54:41 || 14:03:17 || 41 || incomplete || incomplete || the resort, Yingke oasis maize field, and wheat field |- | 4 || 3#11a || 1500m || 14:07:23 || 14:14:46 || 111 || incomplete || incomplete || the resort, Yingke oasis maize field, and wheat field |- | 5 || 3#9 || 1500m || 14:18:21 || 14:26:17 || 119 || processed;complete || good || wetland park, Zhangye city, Yingke oasis maize field, and wheat field, Huazhaizi desert maize plot |- | 6 || 3#7 || 1500m || 14:31:01 || 14:38:25 || 112 || processed;complete || good |- | 7 || 3#5 || 1500m || 14:42:05 || 14:50:01 || 120 || incomplete || incomplete || Huazhaizi desert plot 1 |- | 8 || 3#3 || 1500m || 14:53:49 || 15:02:41 || 134 || processed;complete || good || Huazhaizi desert plot 2 |- | 9 || 3#1 || 1500m || 15:07:01 || 15:14:41 || 116 || processed;complete || good |- | 10 || 3#11b || 1500m || 15:20:05 || 15:26:37 || 99 || processed;complete || good || the resort, Yingke oasis maize field, and wheat field |- | 11 || 3#13a || 1500m || 15:30:45 || 15:39:01 || 125 || processed;complete || good |- | 12 || 3#5a || 1500m || 15:42:48 || 15:50:05 || 111 || processed;complete || good || Huazhaizi desert plot 1 |}
0 2019-09-12
"Coupling and Evolution of Hydrological-Ecological-Economic Processes in Heihe River Basin Governance under the Framework of Water Rights" (91125018) Project Data Convergence-MODIS Products-Land Use Data in Northwest China (2000-2010) 1. Data summary: Land Use Data in Northwest China (2000-2010) 2. Data content: Land use data of Shiyanghe River Basin, Heihe River Basin and Shulehe River Basin in Northwest China from 2000 to 2010 obtained by MODIS
0 2020-07-30
The data is a fisheye photo above the interception barrel of the Picea crassifolia plot in the Tianlaochi small watershed of Qilian Mountain. The plot has a latitude and longitude of 38.44N, 99.91E, and an altitude of 2793m. Photo DSC_0008——DSC_0097 corresponds to Fisheye photos above interception barrels 1 to 90 respectively. The camera is directly above the interception barrel and the lens is 1m above the ground. It is used to estimate the cover or LAI of Qinghai spruce forest, and the pictures are processed with Gap Light Analyzer software.
0 2020-03-13
This data set includes the continuous observation data set of soil texture, roughness and surface temperature measured by vehicle borne microwave radiometer from November 22 to 24, 2013 in Desert Park desert, 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 22-24, 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: 7.4M 4. Data format:. Xls
0 2020-03-13
Meteorological elements are indicators of atmospheric variables or phenomena indicating weather conditions at a given place and at a given time. We used automatic forest weather station to monitor the meteorological elements data of Pailugou Watershed at 2800m above sea level. The main meteorological elements monitored include total radiation, net radiation, temperature, relative humidity, wind speed, and wind direction, which basically reflect the changes in meteorological elements in the Qinghai spruce forest.
0 2019-09-14
Select the soil mechanical composition data of 0-20cm depth of soil surface, select the optimal spatial prediction mapping method of soil composition data, and make the spatial distribution data product of soil texture (particle size composition). The American system classification is used as the standard of soil particle classification. The source data of this data set comes from the soil sampling data integrated by the data center of cold and dry areas and the major research plan integration project of Heihe River Basin (spatial interpolation and dynamic simulation analysis of vegetation and environmental elements in the upper reaches of Heihe River basin / approval No. 91325204).
0 2020-03-28
Based on the data information of 21 regular meteorological observation stations in Heihe River Basin and its surrounding areas and 13 national benchmark stations around Heihe River provided by the data management center of Heihe plan, the daily air temperature is statistically sorted out, and the monthly air temperature data of 1961-2010 for many years is calculated, and the spatial stability analysis is carried out to calculate the coefficient of variation. If the coefficient of variation is greater than 100%, then Calculate the relationship between the station and geographical terrain factors by geographical weighted regression, and get the monthly temperature distribution trend; if the coefficient of variation is less than or equal to 100%, calculate the relationship between the station temperature value and geographical terrain factors (longitude, latitude, elevation) by ordinary least square regression, and get the monthly temperature distribution trend; use HASM (high accuracy surface modeling) for the residual after removing the trend Method). Finally, the monthly average temperature distribution of the Heihe River Basin in 1961-2010 is obtained by adding the trend surface results and the residual correction results. Time resolution: average monthly temperature for many years from 1961 to 2010. Spatial resolution: 500M.
0 2020-07-30
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