The main contents of this data set are forest, shrub and grassland sample plot survey data.The fixed samples are located in the drainage ditch valley of qilian mountain and the dayaokou valley where the hydrology observation and test site of the water source conservation forest research institute of gansu province is located. The information of the sample is as follows: Number elevation quadrat size longitude latitude surface type G1 2715 20 × 20 100 ° 17 '12 "38 ° 33' 29" qinghai spruce forest G2 2800 20×36 100°17 '07 "38°33' 27" moss spruce forest G3 2840 20×20 100°17 '37 "38°33' 05" moss spruce forest G4 2952 20 × 20 100 ° 17 '59 "38 ° 32' 47" qinghai spruce forest G5 3015 20 × 20 100 ° 18 '06 "38 ° 32' 42" qinghai spruce forest G6 3100 20 × 20 100 ° 18 '13 "38 ° 32' 31" thicket qinghai spruce forest G7 3300 23.5 × 20 thickets qinghai spruce forest G8 2800 20×20 100°13 '30 "38°33' 29" moss spruce forest B1 2700 12.8×25 moss spruce forest B2 2800 20×20 100°17 '38 "38°32' 59" moss spruce forest B3 2900 20×20 100°17 '59 "38°32' 51" grass spruce forest B4 3028 20×20 100°17 '59 "38°32' 39" moss spruce forest B5 3097 20×20 100°18 '02 "38°32' 32" moss spruce forest B6 3195 20 × 20 100 ° 18 '06 "38 ° 32' 25" qinghai spruce forest B7 2762 20 × 20 100 ° 17 '08 "38 ° 33' 21" qinghai spruce forest B8 2730 20×20 100°17 '06 "38°33' 27" moss spruce forest GM1 3690 5×5 100°18 '02 "38°32' 02" caragana scrub (middle) GM2 3690 5×5 100°18 '02 "38°32' 02" caragana scrub (rare) GM3 3700 5×5 100°18 '03 "38°32' 03" caragana + jilaliu shrub (dense) GM4 3600 5×5 100°18 '10 "38°32' 06" caragana + jila willow thicket (middle) GM5 3600 5×5 100°18 '10 "38°32' 06" caragana + jila willow shrub (sparse) GM6 3600 5×5 100°18 '10 "38°32' 06" caragana + jila willow thicket (dense) GM7 3500 5×5 100°18 '14 "38°32' 08" caragana + jila willow thicket (middle) GM8 3500 5×5 100°18 '14 "38°32' 08" caragana + jila willow thicket (dense) GM9 3500 5×5 100°18 '14 "38°32' 08" caragana + jila willow thicket (rare) GM10 3400 5×5 100°18 '18 "38°32' 12" golden pheasant scrub (rare) GM11 3400 5×5 100°18 '18 "38°32' 12" golden pheasant + golden raspberry shrub (dense) GM12 3400 5×5 100°18 '18 "38°32' 12" golden pheasant scrub (rare) GM13 3300 5 × 5 100 ° 18 '21 "38 ° 32' 21" giraliu thicket GM14 3300 5 × 5 100 ° 18 '21 "38 ° 32' 21" caragana + jila shrub GM15 3300 5 × 5 100 ° 18 '21 "38 ° 32' 21" caragana + jila shrub YC3 2700 1×1 100°17 '14 "38°33' 33" needle thatch field YC4 2750 1×1 100°17 '18 "38°33' 32" needle thatch field YC5 2800 1×1 100°17 '21 "38°33' 33" needle thatch field YC6 2850 1×1 100°17 '25 "38°33' 33" needle thatch field YC7 2900 1×1 100°17 '31 "38°33' 32" aster + needle thatch field YC8 2950 1×1 100°17 '44 "38°33' 23" needle thatch field YC9 2980 1×1 100°17 '48 "38°33' 25" needle thatch field The sample geodesic tree data were surveyed from July to August 2007.The survey included: 1. Basic survey of sample plots in drainage ditch basin: A) sample land setting: sample land number, elevation, slope direction, slope position, slope, soil layer thickness, sample land size, longitude and latitude, community type, soil type, operation status, age B) survey of each wood in the sample plots: sample plot number, tree number, tree species, tree classification, chest diameter, tree height, undershoot height, crown radius 2. Soil profile survey record sheet Including forest/vegetation status, major tree species, forest age, soil name, surface soil erosion, parent rock and material, drainage conditions, land use history, soil profile (soil layer, moisture, color, texture, structure, root system, gravel content) 3. Standard ground cover factor Standard land area, dominant tree species, stand/vegetation origin, elevation, slope direction, slope position, slope, cutting and utilization method, afforestation land preparation type, survey method, canopy coverage, living ground cover, dead cover cover, litter thickness (undivided strata, semi-decomposed layer, decomposed layer) 4. Canopy survey: 5. Draft quadrat (1m×1m) survey record sheet Including species name, number, coverage, average height 6. Results of determination of soil physical properties in source forest of qilian mountain (land sample survey) Contains the soil physical properties measurement process (+ wet mud weight aluminum box, aluminum box, soil moisture content, suddenly bulk density, etc.), bringing biomass measurement (total fresh weight of shrub and herb, fresh weight of sample, sample dry weight, etc.), litter dry weight (including mosses) layer and the largest capacity calculation process (of moss and litter thickness, total fresh weight, fresh weight of samples, the dry weight of the sample, soaking for 24 h after heavy, maximum water holding capacity, the largest water depth, the biggest hold water rate, maximum moisture capacity) 7. Bush sample survey: Including species name, number, coverage, average height 8. Standard sample land setting and questionnaire for each wooden inspection ruler Including tree species, tree classification, age, chest diameter, number of height, undershoot height, crown radius 9. Litter layer survey record sheet Including litter (decomposed layer, semi-decomposed layer, decomposed layer) thickness 10. Update survey records: Including tree species, natural regeneration (height <30cm, height 31-50cm, height >51cm), artificial regeneration (height <30cm, height 31-50cm, height >51cm) This data set can provide ground measured data for remote sensing inversion of forest structure parameters.

The fixed forest sample plot is located in the drainage ditch of Dayekou, Qilian Mountain, where the hydrological observation field of Gansu Water Conservation Forest Research Institute is located. From July 2003 to August 2003 and from July 2007 to August 2007, the tree survey of the sample plot was completed by technicians from Gansu Water Conservation Forest Research Institute and Institute of environment and Engineering in cold and dry areas of Chinese Academy of Sciences. A total of 17 fixed forest samples were observed, including the survey of sample plot factors and the survey of each tree. The observation factors of sample plots mainly include forest farm, longitude and latitude coordinates, slope direction, slope position, slope, soil thickness, canopy density of arbor layer, leaf area index, etc. The main instruments used in the measurement are tape, DBH, flower pole, tree measuring instrument, compass and fish eye camera. The measurement factors of each tree include DBH, height of tree, height under branch, crown width in cross slope direction, crown width along slope direction, growth status of single tree, etc. For details, please refer to the metadata of "Heihe River Integrated Remote Sensing joint test: fixed sample plot tree survey data set (2003)" and "Heihe River Integrated Remote Sensing joint test: fixed sample plot tree survey data set (2007)". The Lai in this data set is the supplementary measurement data during the joint remote sensing experiment of Heihe River in 2008. That is to say, the supplementary measurement of Lai has been done in these fixed plots. The supplementary observation time of Lai was from June 1 to 13, 2008. 15 of the 17 fixed plots were investigated. Four instruments were used to observe each plot. In addition to the commercial instruments such as hemiview fish eye camera, LAI-2000 and trac, these instruments also use the canopy analysis instrument made by Beijing Normal University. In each 20 m × 20 m plot, trac measures along two parallel routes perpendicular to the direction of sunlight incidence, which can basically represent the entire quadrat; hemiview fisheye camera and LAI-2000 measure the same points, that is, take three points on the trac line, plus the center point of the quadrat, a total of 7 measuring points. This set of data set can provide ground data for the study of remote sensing inversion method of forest structure parameters.

This data set includes the observation data of the automatic meteorological station from January 2008 to September 2009 in Linze Inland River Basin Comprehensive station. The station is located in Linze County, Zhangye City, Gansu Province, with longitude and latitude of 100 ° 08 ′ e, 39 ° 21 ′ N and altitude of 1382m. The observation items include: atmospheric temperature and humidity gradient observation (1.5m and 3.0m), wind speed (2.2m and 3.7m), wind direction, air pressure, precipitation, net radiation and total radiation, carbon dioxide (2.8m and 3.5m), soil tension, multi-layer soil temperature (20cm, 40cm, 60cm, 80cm, 120cm and 160cm) and soil heat flux (5cm, 10cm and 15cm). Please refer to the instruction document published with the data for specific header and other information.

This data set was acquired by L & K band airborne microwave radiometer on July 8, 2008 in Linze flight area. The frequency of L-band is 1.4GHz, and the backsight is 35 degrees to obtain dual polarization (H and V) information; the frequency of K-band is 18.7ghz, and there is no polarization information. The plane took off from Zhangye airport at 10:00 (Beijing time, the same below) and landed at 13:38. 10: At 23-13:10, the flight altitude was about 1900m and the flight speed was about 230-250km / hr. Among them, 12:21-12:27 low flying Linze reservoir line 1-6 has a relative altitude of 100m and a flight speed of 190km / hr. 12: 56-13:08 low flying desert marking twice (line 1-7, first North to south, then south to North). The original data is divided into two parts: microwave radiometer data and GPS data. The L and K bands of microwave radiometer are non imaging observations. The digital values obtained from the instantaneous observation are recorded in the text file, and the longitude and latitude as well as the aircraft attitude parameters are recorded in the GPS data. When using microwave radiometer to observe data, it is necessary to convert the digital value recorded into the bright temperature value according to the calibration coefficient (the calibration coefficient file is filed with the original observation data). At the same time, through the clock records of microwave radiometer and GPS, we can connect the microwave observation with GPS record and match the geographic coordinate information for the microwave observation. Due to the coarse observation resolution of microwave radiometer, the effects of aircraft yaw, roll and pitch are generally ignored in data processing. According to the target and flight relative altitude (H), after calibration and coordinate matching, the observation information can also be gridded. The resolution (x) of L band and K band is consistent with that of observation footprint. The reference resolution is: L band, x = 0.3H; K band, x = 0.24h. After the above steps, we can get the products that users can use directly.

Observation time: 2008-06-05 ~ 2008-06-15.A sample strip with a length of 1Km and a width of 20m was set up to cross the super sample plot from the starting point of the super sample plot at the geantan forest station in ohnoguchi.The compass was used to determine the direction of the sample, and the azimuth was 115 degrees north by east, which was basically consistent with the flight route.20 meters ×20 meters of sample land shall be arranged every 50 meters in the sample belt, a total of 20 pieces of sample land.There is some overlap between the sample belt and the super sample land. The center of the no.1 sample land of the sample belt is located at the center of the super sample land. The observation data is shown in the measurement data set per wood of the super sample land.This data set records the observation data of sample 2 ~ 20.These data include the following three parts: 1) tree data of sample plots: each wood of 2 ~ 20 plots was measured: chest diameter, tree height, crown width and undershoot height.Laser altimeter and ultrasonic altimeter were used to measure the height of big trees and under branches, flower rod was used to measure the height of small trees and under branches, chest diameter was used to measure the chest diameter of trees, and crown width was measured with a leather tape measure. 2) sample location data: the sample location is roughly determined by using a tape measure and compass. The coordinates of the center point of the sample are accurately measured using the French THALES DGPS measurement system (model z-max).The observation method is to use two GPS receivers to conduct synchronous static measurement, one in the reference station and the other in the mobile station. The observation lasts 30 minutes. The data processing software provided by the system is used for post-processing difference. 3) LAI observation data: LAI area index (LAI) of each sample plot was measured by lai-2000 and HemiView.

The data set is based on the geodetic coordinate data and other auxiliary data of the corner points of 16 subsamples of super sample plots, the setting points of lidar base station of the foundation and the base points of each tree trunk measured by the total station. The data acquisition time of total station is from June 3, 2008 to June 12, 2008, which is divided into two groups. One total station is used respectively, with the models of topcon602 and topcon7002. A total of 1468 Picea crassifolia trees in the super sample plot were measured, and all the corner points of the sub sample plot and the top points of the stake set on the base station of lidar were located. These positioning results are the main data content of the dataset. In addition, on June 3, 2008, June 4, 2008, June 6, 2011, the differential GPS z-max was used to locate all the stake vertices. By manually measuring the height of each stake, the height of the surface under the stake was calculated, and finally the three-dimensional coordinate position of the surface of each tree and the topographic map of super sample plot were generated. These data constitute the secondary data of the dataset. This data set can provide detailed ground observation data for the establishment of real three-dimensional forest scene, the development and correction of various three-dimensional forest remote sensing models, and ground validation data for the extraction of airborne lidar forest parameters.

1. Data overview: water footprint and virtual water trade of tertiary industry in gansu province in 1997, 2002 and 2007 2. Data content: input-output value flow statement of gansu province, input-output value flow statement of primary industry, secondary industry and tertiary industry of gansu province, water use data, water footprint and virtual water trade data 3. Spatial and temporal scope: data time is 1997, 2002 and 2007;The space scope is gansu province 4. Data description: The data in this part are mainly the socio-economic and regional water supply and consumption data of gansu province, including the following 5 documents: (1) table of input and output of gansu province. XLS: value flow table of input and output of gansu province in 1997, 2002 and 2007, raw data of social economy. (2) input and output table of gansu province. XLS: input and output table of primary industry, secondary industry and tertiary industry of gansu province in 1997, 2002 and 2007 (3) summary table of water use data. XLS: original water use data. (4) calculation results of gansu province. (5) description of virtual water trade data of gansu province. For detailed data description, please refer to "gansu province virtual water trade data description" word document.

NDVNDVI project belongs to the national natural science foundation "environment and ecological science in western China" major research program, led by professor gao qiong of Beijing normal university. The project runs from 2003.1-2005.12. Remittance data of the project: 1. Monitoring data of photosynthesis of 8 plants in ansai station in 2002 (excel) 2. Monitoring data of photosynthesis of 6 plants near the lime temple of ijin horo banner in July 2003 (excel) 3. Monitoring data of photosynthesis of 5 kinds of plants in wufen gutter of huangfuchuan, jungeer banner in July 2003 (excel)

This data is the restoration of the distribution of the main ancient irrigation canals in the middle and upper reaches of the Heihe River Basin from the Ming Dynasty to the Republic of China. It is based on the basic data of reprinting ganzhenzhi, reconstructing the new records of Suzhou and ganzhoufu, and combined with the topographic map and image of the 1960s. It is provided in the form of ArcGIS software ShapeFile, GCS krasovsky 1940 coordinate system, and trans Mercator projection grid. The data type is linear vector, and its attributes include name, source, length, irrigation area, etc.

This data is SWAT scenario simulation data in the middle and upper reaches of Heihe River Basin. Scenarios include historical trend scenario (HT), ecological protection scenario (EP), strict ecological protection scenario (SEP), economic development scenario (ED) and rapid economic development scenario (red). Firstly, the dyna_clue model is used to simulate the land use change under different scenarios, and then the simulated land use map under different scenarios is imported into the SWAT model to simulate the daily and monthly runoff scenario data of the upstream outlet (Yingluo gorge) and the middle outlet (Zhengyi gorge) of the Heihe River Basin (assuming other conditions are the same). The period is 2011-2030. The data format is excel.

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". In 1995, guizhou province adopted a hierarchical land cover classification system, which divided 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.

The super sample plot is composed of 16 sub samples. In order to locate each tree in the sample plot and facilitate the location of the base station point for ground-based radar observation, it is necessary to measure the geodetic coordinates of the sub sample plot corner point and the preset base station point for ground-based radar. The location of these points and each tree is measured by total station. Because the total station measures relative coordinates, in order to obtain geodetic coordinates, it is necessary to use differential GPS (DGPS) to measure at least one reference point around the super sample plot with high precision. In addition, we also use DGPS to observe the geodetic coordinates of all corner points of the subsample, and the measurement results can form the verification of the total station measurement results. The data set is based on all the positioning results measured by DGPS, excluding the positioning results of total station. The measurement time is from June 1 to 13, 2008, using the French Thales differential GPS measurement system, model z-max. The observation method is to use two GPS receivers for synchronous static measurement, one is the base station, which is set next to Gansu Water Conservation Forest Research Institute (the WGS geodetic coordinate of the base station is a first-class benchmark introduced from Zhangye City through multi station observation using z-max). The other is the mobile station, which is placed on the observation point of super sample plot. The observation time of each point varies from 10, 15, 20, 25, 30 minutes. The specific time depends on the satellite signal. The signal difference time is measured for several minutes more. Finally, the final positioning result is obtained by using the processing software of the instrument. WGS geodetic coordinate system is used for the positioning results. Firstly, six temporary control points were measured in the open area next to the super sample plot, providing reference points for the total station to measure the position of trees in the super sample plot. Then, flow stations were set up on each corner of 16 sub plots of super plot, and the coordinates of corner points were measured, and 41 observation points were obtained. The dataset stores the positioning results of these 47 points. This data is only for project use and not for external sharing.