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
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
1. Data overview The data set of the base camp integrated environmental observation system is a set of ENVIS (IMKO, Germany) which was installed at the base camp observation point by qilian station.It is stored automatically by ENVIS data mining system. 2. Data content This data set is the scale data from January 1, 2012 to December 31, 2012.Including air temperature 1.5m, humidity 1.5m, air temperature 2.5m, humidity 2.5m, soil moisture 0cm, precipitation, wind speed 1.5m, wind speed 2.5m, wind direction 1.5m, geothermal flux 5cm, total radiation, surface temperature, ground temperature 20cm, ground temperature 40cm, ground temperature 60cm, ground temperature 80cm, ground temperature 120cm, ground temperature 160cm, CO2, air pressure. 3. Space and time scope Geographical coordinates: longitude: 99° 53’e;Latitude: 38°16 'N;Height: 2980.2 m.
0 2020-03-10
This dataset includes eight scenes, covering the artificial oasis eco-hydrology experimental area of the Heihe River Basin, which were acquired on (yy-mm-dd hh:mm) 2012-05-24, 2012-06-04, 2012-06-26, 2012-07-07, 2012-07-29, 2012-08-09, 2012-08-14, 2012-08-25. The data were all acquired around 19:00 (BJT) at StripMap mode with product level of MGD. Within them, the former six images are of HH/VV polarization with low incidence angle (22-24°), while the later two images acquired on 2012-08-14 and 2012-08-25 are of VV/VH polarization with higher incidence angle (39-40°). TerraSAR-X dataset was acquired from German Space Agency (DLR) through the general proposal of “Estimation of eco-hydrological variables using TerraSAR-X data in the Heihe River Basin, China” (project ID: HYD2096).
0 2020-10-13
This data is from "China 1:100,000 land use data".China 1:100,000 land use data was constructed in three years based on Landsat MSS, TM and ETM remote sensing data by using satellite remote sensing as a means to organize remote sensing science and technology teams from 19 institutes affiliated to the Chinese academy of sciences (cas) in the "eighth five-year plan" major application project "national macro survey and dynamic research on remote sensing of resources and environment".The land use data of guizhou province adopts a hierarchical land cover classification system, which divides the country into 6 primary categories (arable land, forest land, grassland, water area, urban and rural areas, industrial and mining areas, residential land and unused land) and 31 secondary categories.It is the most accurate land use data product in China and has played an important role in national land resource survey, hydrological and ecological research.
0 2020-03-17
The output data of the distributed eco hydrological model (gbehm) in the upper reaches of Heihe River includes the spatial distribution data series of 1-km grid. Region: upper reaches of Heihe River (Yingluo gorge), temporal resolution: Monthly Scale, spatial resolution: 1km, period: 2015-2070 (future scenario). The data include precipitation, evapotranspiration, runoff depth and average temperature. All data are in ASCII format. Please refer to the basin.asc file in the reference directory for the spatial range of the basin. Projection parameters of model results: sphere_Arc_Info_Lambert_Azimuthal_Equal_Area
0 2020-03-27
A land surface temperature and upward/downward shortwave radiation observation system was set up on the roof, which locate on the edge of No.4 eddy covariance system (EC4) of the MUlti-Scale Observation EXperiment on Evapotranspiration over heterogeneous land surfaces 2012 (MUSOEXE-12). This observation site can offer in situ calibration data for TASI, WiDAS and L band sensor used in aerospace experiment. Observation Site: This point is located in a large and homogeneous adobe roof in Shiqiao Village, Xiaoman Town, Zhangye City. Land surface of observation site is relatively flat and uniform, and also not tall trees around. It’s about 20 meters away from southwest No.4 eddy covariance system (EC4) observation points. The coordinates of this site: 38°52′38.50″ N，100°21′27.00″ E。 Observation Instrument: Observation system is composed of a SI-111 infrared radiometer (Campbell, USA) installed vertically downward, two CMP3 pyranometer (Kipp&Zonen, Netherlands) one upward, another downward. Observation height is 1.0 m, data logging by a Campbell CR850 logger. Sensor orientation： Observation mounting arm has 3 m long, parallel to roof edge, azimuth angle: 156° (East by south 66°) Observation Time: This site operates from 23 June, 2012 to 20 September, 2012. Observation data laagered by every 5 seconds uninterrupted. Output data contained sample data of every 5 seconds and mean data of 1 minute. Accessory data: Land surface (adobe roof) temperature, downward/upward total solar radiation, surface albedo. Dataset is stored in *.dat file, which can be read by Microsoft excel or other text processing software (UltraEdit, et. al). Table heads meaning: Rs_downwell, downward shortwave radiation (W/m^2); Rs_upwell, upward (reflect) shortwave radiation (W/m^2); albedo, calculate by Rs_upwell/ Rs_downwell. SBT_C, body temperature of SI-111 sensor (℃); Target_C, Target of surface temperature (℃). Dataset is stored day by day, named as: data format + site name + interval time + date + time. The detailed information about data item showed in data header introduction in dataset.
0 2019-09-14
The 30 m / month synthetic photosynthetic effective radiation absorption ratio (fAPAR) data set of Heihe River basin provides the monthly Lai synthetic 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, considering different vegetation types, based on land cover classification map, combined with 30 m /Monthly synthetic leaf area index (LAI) products were produced by fapar-p model based on energy conservation. Based on the principle of energy conservation, the algorithm considers the multiple bounces between vegetation, soil and vegetation, as well as the influence of various factors such as sky scattered light. By analyzing the process of the interaction between photons and canopy, from the point of view that the movement of photons in the canopy is equal to the probability of re collision when multiple scattering occurs, a uniform and continuous vegetation fAPAR model is established. In addition, the effects of various factors on the fAPAR model were analyzed, including soil and leaf reflectance, aggregation index, and G function. The algorithm is highly dynamic, and can get better results for different soil background, vegetation type, radiation conditions, light and observation geometry, weather conditions. Compared with the data of corn canopy par measurement in Yingke irrigation area of Zhangye City, Gansu Province on July 8, 2012, the 30 m / month fAPAR product has a high consistency with the ground observation data, and the error with the observation value is less than 5%. In a word, the 30 m / month synthetic photosynthetic effective radiation absorption ratio (fAPAR) data set of Heihe River Basin comprehensively uses the multi temporal and multi angle observation data to improve the estimation accuracy and time resolution of parameter products, and better serves the application of remote sensing data products.
0 2020-03-13
The parameter inversion study project of soil moisture and snow water equivalent on the Tibetan Plateau in the past 20 years is part of the key research plan of Environmental and Ecological Science for West China of the National Natural Science Foundation of China. The person in charge is Jiancheng Shi, a researcher at the Institute of Remote Sensing Applications of the Chinese Academy of Sciences. The project ran from January 2004 to December 2007. The data collection of the project: the Monthly MODIS Snow Cover Product of Tibetan Plateau (2001-2005). Based on the image data acquired by MODIS, combined with ASTER image data, the data set carried out snow cover area classification and change analysis at a subpixel level on the Tibetan Plateau. The research mainly focused on studying the subpixel snow cover area classification algorithm, including the statistical regression method and the mixed-pixel decomposition method using the normalized snow index. In the mixed-pixel decomposition, a linear mixed model was adopted, and snow and non-snow end members were automatically extracted using the normalized snow index and the normalized vegetation index. On the basis of the subpixel snow cover area classification algorithm, the snow cover area variation on the Tibetan Plateau was analyzed. Using the method of establishing a decision tree, clouds and snow were detected, cloud-removal was performed, and the subpixel of the Tibetan Plateau was formed by synthesis and mosaicking of the time series images. The snow cover area classification database analyzes and describes the spatial distribution and variation characteristics of the snow cover area of the Tibetan Plateau.
0 2019-09-12
The dataset includes soil physical and chemical attributes: pH value, organic matter fraction, cation exchange capacity, root abundance, total nitrogen (N), total phosphorus (P), total potassium (K), alkali-hydrolysable N, available P, available K, exchangeable H+, Al3+, Ca2+, Mg2+, K+ , Na+, horizon thickness, soil profile depth, sand, silt and clay fractions, rock fragment, bulk density, porosity, structure, consistency and soil color. Quality control information (QC) was provided. The resolution is 30 arc-seconds (about 1 km at the equator). The vertical variation of soil property was captured by eight layers to the depth of 2.3 m (i.e. 0- 0.045, 0.045- 0.091, 0.091- 0.166, 0.166- 0.289, 0.289- 0.493, 0.493- 0.829, 0.829- 1.383 and 1.383- 2.296 m) for convenience of use in the Common Land Model and the Community Land Model (CLM). 1.THSCH.nc: Saturated water content of FCH 2.PSI_S.nc: Saturated capillary potential of FCH 3.LAMBDA.nc: Pore size distribution index of FCH 4.K_SCH.nc: Saturate hydraulic conductivity of FCH 5.THR.nc: Residual moisture content of FGM 6.THSGM.nc: Saturated water content of FGM 7.ALPHA.nc: The inverse of the air-entry value of FGM 8.N.nc: The shape parameter of FGM 9.L.nc: The pore-connectivity parameter of FGM 10.K_SVG.nc: Saturated hydraulic conductivity of FGM 11.TH33.nc: Water content at -33 kPa of suction pressure, or field capacity 12.TH1500.nc: Water content at -1500 kPa of suction pressure, or permanent wilting point
0 2019-09-12
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