The data is based on the Harmonized World Soil Database version 1.1 (HWSD) constructed by the Food and Agriculture Organization of the United Nations (FAO) and the Vienna International Institute for Applied Systems (IIASA). The data source of China is 1: 1 million soil data in the second national land survey provided by the Nanjing Soil Research Institute. The data can provide model input parameters for modelers, in agricultural perspective, it can be used to study eco-agricultural zoning, food security and climate change. The data format is grid and the projection is WGS84. The soil classification system used is mainly FAO-90. The main fields of the soil property table include: SU_SYM90 (the soil name in the FAO90 soil classification system); SU_SYM85 (FAO85 classification); T_TEXTURE (top soil texture); DRAINAGE (19.5); REF_DEPTH (soil reference depth); AWC_CLASS (19.5); AWC_CLASS (soil effective water content); PHASE1: Real (soil phase); PHASE2: String (soil phase); ROOTS: String (depth classification with obstacles to the bottom of the soil); SWR: String (soil moisture characteristics); ADD_PROP: Real (a specific soil type related to agricultural use in the soil unit); T_GRAVEL: Real (gravel volume percentage); T_SAND: Real (sand content); T_SILT: Real (silt content); T_CLAY: Real (clay content); 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 (pH) T_CEC_CLAY: Real (cation exchange capacity of clay soil); T_CEC_SOIL: Real (cation exchange capacity of soil) T_BS: Real (basic saturation); T_TEB: Real (exchangeable base); T_CACO3: Real (carbonate or lime content) T_CASO4: Real (sulfate content); T_ESP: Real (exchangeable sodium salt); T_ECE: Real (conductivity). The attribute field beginning with T_ indicates the upper soil attribute (0-30cm), and the attribute field beginning with S_ indicates the lower soil attribute (30-100cm). For the meaning of specific attribute values, please refer to the documentation * .pdf and database * .mdb in the folder.
0 2020-03-26
The dataset of ground truth measurements synchronizing with MODIS, ALOS PALSAR and AMSR-E was obtained in the Biandukou foci experimental area on May 24, 2008. Observation items included: (1) the surface temperature in No. 1 (grassland), No. 2 (the rape land), No. 3 (the rape land), No. 4 (the wheat land) and No. 5 quadrate (wheat and rape); (2) the soil moisture by WET in No. 2 quadrate; (3) GPR and WET; (4) The spectrum by ASD Fieldspec FRTM (Boulder, Co, USA), 350nm-2500nm, 3nm for the visible near-infrared band and 10nm for the shortwave infrared band). The spectrum data were archived in the ASCII format, with the first five rows as the file header and the following two columns as wavelength (nm) and reflectance (percentage) respectively, and can be opened by .txt or wordpad. The .txt file was not reflectance but intermediate file for further calculation. Raw data were binary files direct from ASD (by ViewSpecPro). The surface radiative temperature and the physical temperature were measured by the handheld infrared thermometer. Besides, the cover type was also recorded. The data can be opened by Microsoft Office. Soil moisture was acquired by WET and the cutting ring. The data can be opened by Microsoft Office. Six data files were included, soil moisture, the surface temperature, GPR, coverage photos and preprocessed data, ground objects spectrum and satellite images.
0 2019-05-23
1 km land cover map of heihe river basin is ran youhua et al. (2009;2011) develop a subset of China's 1 km land cover map (MICLCover) incorporating multi-source local information.The MICLCover land cover map adopts the IGBP land cover classification system, based on the evidence theory, which integrates the 1:100,000 land use data of China in 2000, the vegetation pattern of China vegetation atlas (1:100,000), the 1:100,000 glacier distribution map of China, the 1:100,000 swamp wetland map of China and the land cover product of MODIS in 2001 (MOD12Q1).The verification results of MICLCover showed that the overall consistency of MICLCover and China's land use map reached 88.84% on the level of 7 categories. Among them, the consistency of cultivated land, city, wetland and water type reached more than 95%.Through visual comparison with the land cover data product of MODIS2001 and IGBPDISCover land cover map in three typical areas, MICLCover keeps the overall accuracy of China's land use map and increases the leaf attribute and leaf shape information of China's vegetation map, while reflecting more detailed local land cover details.Using the national forest resources survey data, the verification results in gansu, yunnan, zhejiang, heilongjiang and jilin provinces showed that the accuracy of forest types of MICLCover was significantly improved compared with that of MODIS land cover products.The forest type of MICLCover was verified with the forest resource survey data of qilian mountain national nature reserve administration of gansu province. The results showed that the accuracy of MICLCover forest type in this area was 82.94%. Anyhow, MICLCover land cover map while maintaining the overall precision of the Chinese land use data condition, supplement the vegetation map of China on vegetation types and vegetation season phase information, update the Chinese wetland figure, Chinese ice figure the latest information, the accuracy of China's land cover data is greatly improved, more general classification system, the data can provide higher precision for land surface process model of land cover information.
0 2020-07-30
The dataset of ground truth measurements for snow synchronizing with the airborne microwave radiometers (K&Ka bands) mission was obtained in the Binggou watershed foci experimental area on Mar. 30, 2008. Those provide reliable data for retrieval of snow parameters and properties, especially for dry and wet snow identification. Observation items included: (1) Snow density, snow complex permittivity, snow volumetric moisture and snow gravimetric moisture by the snowfork in BG-A; (2) Snow parameters including snow depth, the snow surface temperature synchronizing with the airborne microwave radiometers (K&Ka bands), the snow layer temperature, the snow grain size and snow density in BG-A (10 points), BG-B (6 points), BG-F (12 points), BG-H (21 points) and BG-I (20 points); For each snow pit, the snowpack was divided into several layers with 10-cm intervals of snow depth. The layer depth (by the ruler), the snow grain size (by the handheld microscope), snow density (by the cutting ring) and the snow temperature (by the probe thermometer) were obtained at each snow pit. Two files including raw data and the preprocessed data were archived.
0 2019-09-10
The total solar radiation and the total radiation of absorption and scattering material attenuation are measured by the international general solar radiation meter (li200sz, li-cor, Inc., USA). The measured data are total solar radiation, including direct and diffuse solar radiation, with a wavelength range of 400-1100nm. The unit of measurement is w / m2, and the typical error is ± 3% (incidence angle is within 60 °) under natural lighting. The data of sodankyl ä station in the Arctic comes from cooperation with the site and website download. The coverage time of sodankyl ä station in the Arctic is updated to 2018.
0 2020-10-14
This dataset is the spatial distribution map of the marshes in the source area of the Yellow River near the Zaling Lake-Eling Lake, covering an area of about 21,000 square kilometers. The data set is classified by the Landsat 8 image through an expert decision tree and corrected by manual visual interpretation. The spatial resolution of the image is 30m, using the WGS 1984 UTM projected coordinate system, and the data format is grid format. The image is divided into five types of land, the land type 1 is “water body”, the land type 2 is “high-cover vegetation”, the land type 3 is “naked land”, and the land type 4 is “low-cover vegetation”, and the land type 5 is For "marsh", low-coverage vegetation and high-coverage vegetation are distinguished by vegetation coverage. The threshold is 0.1 to 0.4 for low-cover vegetation and 0.4 to 1 for high-cover vegetation.
0 2020-10-09
This data set contains the daily values of temperature, air pressure, relative humidity, wind speed, precipitation, and total radiation observed at the Namco station from 1 October 2005 to 31 December 2016. The data set was processed as a continuous time series after the original data were quality controlled. After the systematic error caused by missing data points and sensor failure was eliminated, the data set reaches the accuracy of raw meteorological observation data required by the National Weather Service and the World Meteorological Organization (WMO). The data can provide information for professionals engaged in scientific research and training related to atmospheric physics, atmospheric environment, climate, glaciers, frozen soils and other disciplines. This data set has mainly been applied in the fields of glaciology, climatology, environmental change, cold zone hydrological processes, frozen soil science, etc. The measured parameters had the following units and accuracies: Air temperature, unit: °C, accuracy: 0.1 °C; air relative humidity, unit: %, accuracy: 0.1%; wind speed, unit: m/s, accuracy: 0.1 m/s; wind direction, unit: °, accuracy: 0.1 °; air pressure, unit: hPa, accuracy: 0.1 hPa; precipitation, unit: mm, accuracy: 0.1 mm; total radiation, unit: W/m2, accuracy: 0.1 W/m2.
0 2019-09-12
The “long-term series of daily snow depth in Eurasia” was produced using the passive microwave remote sensing data. The temporal range is 1980~2016, and the coverage is the Eurasia continent. The spatial resolutions is 0.25° and the temporal resolution is daily. A dynamic brightness temperature gradient algorithm was used to derive snow depth. In this algorithm, the spatial and temporal variations of snow characteristics were considered and the spatial and seasonal dynamic relationships between the temperature difference between 18 GHz and 36 GHz and the measured snow depth were established. The long-term sequence of satellite-borne passive microwave brightness temperature data used to derive snow depth came from three sensors (SMMR, SSM/I and SSMI/S), and there is a certain system inconsistency among them. So, the inter-sensor calibration was performed to improve the temporal consistency of these brightness temperature data before snow depth derivation. The accuracy analysis shows that the relative deviation of Eurasia snow depth data is within 30%. The data are stored as a txt file every day, each file includes a file header (projection mode) and a 720*332 snow depth matrix, and each snow depth represents a 0.25°*0.25° grid. For details of the data, please refer to data specification “Snow depth dataset of Eurasian (Version 1.0) (1980-2016).doc”
0 2020-03-13
From May to October 2012, the monthly Lai vegetation index product data of 30 meters in Heihe River Basin was retrieved by using the environmental satellite CCD image, and the inversion method was based on the look-up table method and go + Hapke model. In the inversion process, Nelson parameters are determined according to vegetation types.
0 2020-03-07
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