Based on the geostationary satellites and reanalysis data, the China Regional Atmospheric Driving Dataset is a set of atmospheric driving data sets with high spatiotemporal resolution prepared by the China Meteorological Administration, with a spatial resolution of 0.1 ° × 0.1 ° and a temporal resolution of 1 Hours, covering a range of 75 ° -135 ° east longitude and 15 ° -55 ° north latitude, include 6 elements of near-surface temperature, relative humidity, ground pressure, near-surface wind speed, incident solar radiation on the ground, and ground precipitation rate. The preparation process of precipitation products is as follows: The 6-hour cumulative precipitation estimated from the multi-channel data of the China Fengyun-2 geostationary satellite is integrated with the 6-hour cumulative precipitation from conventional ground observations to obtain 6-hour cumulative precipitation spatial distribution data, and then use the high-resolution cloud classification information retrieved from the multi-channel inversion of the geostationary satellites determines the interpolation time weight of the cumulative precipitation and obtains an estimated one-hour cumulative precipitation. The preparation process of the radiation data is as follows: The surface incident solar radiation based on FY-2C, uses the radiation transmission model DISORT (Discrete Ordinates Radiative Transfer Program for a Multi-Layered Plane-parallel Medium) to calculate the radiation transmission and obtains the data of surface incident solar radiation in China. Preparation process of other elements: The space and time interpolation method is used for the NCEP reanalysis data of 1.0 ° × 1.0 ° to obtain driving factors such as near-surface air temperature, relative humidity, ground pressure, and near-surface wind speed of 0.1 ° × 0.1 ° per hour. Physical meaning of each variable: Meteorological Elements || Variable Name || Unit || Physical Meaning | Surface temperature || TBOT || K || Surface temperature (2m) | Surface pressure || PSRF || Pa || Surface pressure | Relative humidity on the ground || RH || kg / kg || Relative humidity near the ground (2m) | Wind speed on the ground || WIND || m / s || Wind speed near the ground (anemometer height) | Surface incident solar radiation || FSDS || W / m2 || Surface incident solar radiation | Precipitation Rate || PRECTmms || mm / hr || Precipitation Rate For more information, see the data documentation published with the data.

The data is a dataset of reservoir distribution in the Tarim River Basin. It is comprehensively prepared using topographic maps and remote sensing images. The scale is 250,000. Projection: latitude and longitude. The data includes spatial data and attribute data. The attribute field: Name (reservoir name) reflects the Tarim River Basin in 2000. The distribution of left and right reservoirs.

The data is the distribution data of the settlements in the Tarim River Basin, mainly including the distribution of cities, counties, towns, and villages in the Tarim River Basin. The data mainly has two attribute fields: Code (settlement code), Name (settlement name)

The dataset is a lake distribution map of Tarim River Basin, with a scale of 250000, projection: latitude and longitude, data including spatial data and attribute data, and lake attribute fields: NAME (name of lake) and CODE (lake code)

The data is a dataset of rivers in the Tarim River Basin. It is revised according to topographic maps and TM remote sensing images. The scale is 250,000. The data includes spatial data and attribute data. The attribute data fields are: HYD_CODE (river code), Name (river name), SHAPE_leng ( River length).

The dataset covers western China. MSS remote sensing images Dataset properties: Pixel Size: 60m Reflective bands 4-7 (Landsat 1-3) and Bands 1-4 (Landsat 4-5) Output Format: GeoTIFF Resampling method: cubic convolution (CC) Map Projection: UTM – WGS 84 Polar Stereographic for the continent of Antarctica. Image Orientation: Map (North Up) Data sources were partially downloaded from http://eros.usgs.gov/ and some were collected from various projects. The data folder is named the row and column number where the image is located. The folder contains the MSS 4 band images (* .tif), header files (* .met, * .hdr), and thumbnails (jpg). The naming format of image files is row and column number_TM image mark (2m), and image acquisition time_band number. It is mainly used for thematic analysis and compilation of different scale thematic maps on agriculture, forestry, water, soil, geology, geography, geography, surveying and mapping, regional planning, and environmental monitoring.

The research project on the function and mechanism of sand-fixing afforestation of waste lignin from straw pulp and paper making belongs to the national natural science foundation of China "environment and ecological science in western China" major research program, led by wang hanjie, a researcher of the institute of aviation meteorology and chemical protection, air force equipment research institute. The project ran from January 2004 to December 2006 Remittance data of the project: 1. 2005-08-10 - sand lake - jinsha wan test site image (JPG) 2.2006 field picture of fixed sand test (JPG) 3. Meteorological data of ningxia jinshawan meteorological station (TXT text) Observation data including dry bulb temperature, wet bulb temperature, 0, 5, 10, 15, 20cm ground temperature, evaporation and air temperature were observed at 8:00,14:00 and 20:00 on August 13, 2005 4. Growth data of jinshawan community in ningxia (TXT text) The data of crown diameter and height of four samples are included. 5. Soil water data of jinshawan, ningxia (excel) Soil moisture data of 16 samples at depths of 20CM and 12CM in clear water control area and lignin spraying area by 2 hours in the daytime on August 19, 2005. 6. Soil water data of shahu lake in ningxia (excel) On August 10,11, 2005, soil moisture data of various depths of 10CM,12CM and 20CM were obtained 7. Plant growth data of sand fixation community in shahu, ningxia (excel) Plant growth statistics of 5 sample plots: species name,x,y, base, crown, height, number of plants.

Data of the project: 1. Sample DOC information sheet: liangfeng cave, qixing cave, general cave, rhinoceros cave 2003-2004 water sample DOC data. Excel sheet 2. Excel sheet of hydrogen and oxygen isotope information of samples: secondary chemical sediments, water/vSMOW, rain 18OvSMOW and so on in liangfeng cave, seven-star cave, general cave, rhino cave 3. The sample water chemical information table of Excel table: header is as follows: sample number # T ℃ pH K + Na + (mg/l) (mg/l) Ca2 + (mg/l) magnesium 2 + (mg/l) Cl - (mg/l) SO42 - (mg/l) HCO3 - (mg/l) SIC SID SIG PPCO2 (ATM) PCO2 (Pa) error 4. Sample carbon isotope information sheet In addition, the project is accompanied by basic information and data information documents.

Tarim River is the largest inland river in China, with a total length of 2179 kilometers. Tarim River Basin is one of the vulnerable areas of ecological environment in China. Due to the lack of coordination in material and energy matching, different regions show different vulnerability characteristics in macro. According to the relevant principles of ecological environment quality evaluation, combined with the ecological environment management of the Tarim River Basin. Data is road distribution data set of Tarim River Basin, scale: 250000, projection: longitude and latitude, mainly including spatial distribution and attribute data of main roads in Heihe River Basin, attribute fields: Code (road code), name (road classification) Collect and sort out the basic, meteorological, topographical and geomorphological data of the Tarim River Basin, and provide data support for the management of the Tarim River Basin.

Tarim River is the largest inland river in China, with a total length of 2179 kilometers. Tarim River Basin is one of the vulnerable areas of ecological environment in China. Due to the lack of coordination in material and energy matching, different regions show different vulnerability characteristics in macro. According to the relevant principles of ecological environment quality evaluation, combined with the ecological environment management of the Tarim River Basin. The data is the railway distribution map of Tarim River Basin, with scale of 250000, including spatial data and attribute data, attribute field: Code (railway code) Collect and sort out the basic, meteorological, topographical and geomorphological data of the Tarim River Basin, and provide data support for the management of the Tarim River Basin.

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 landuse data of guizhou province in the late 1980s adopted a hierarchical land cover classification system, which divided the country into 6 primary categories (farmland, woodland, 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.

The data set is the HWSD soil texture data set in the Tarim River Basin. The data comes from the Harmonized World Soil Database (HWSD) constructed by the Food and Agriculture Organization of the United Nations (FAO) and the Vienna International Institute for Applied Systems (IIASA). Version 1.1 was released on March 26, The data resolution is 1km. The soil classification system used is mainly FAO-90. The main fields of the soil attribute 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); ROOTS: String (depth classification to the bottom of the soil); SWR: String (Soil moisture content characteristics); ADD_PROP: Real (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 weight); T_OC: Real (organic carbon content); T_PH_H2O: Real (pH) T_CEC_CLAY: Real (cations in the clay layer soil) Exchange capacity); 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) (FAO 2009).