The 1 km / 5-day Lai data set of Heihe River basin provides the 5-day Lai synthesis results of 2010-2014. The data uses Terra / MODIS, Aqua / MODIS, as well as domestic satellites fy3a / MERSI and fy3b / MERSI sensor data to build a multi-source remote sensing data set with a spatial resolution of 1 km and a time resolution of 5 days. Multi-source remote sensing data sets can provide more angles and more observations than a single sensor in a limited time. However, due to the difference of on orbit running time and performance of sensors, the observation quality of multi-source data sets is uneven. Therefore, in order to make more effective use of multi-source data sets, the algorithm first classifies the quality of multi-source data sets, which can be divided into first level data, second level data and third level data according to the observation rationality. The third level data are observations polluted by thin clouds and are not used for calculation. The purpose of quality evaluation and classification is to provide the basis for the selection of the optimal data set and the design of inversion algorithm flow. Leaf area index product inversion algorithm is designed to distinguish mountain land and vegetation type, using different neural network inversion model. Based on global DEM map and surface classification map, PROSAIL model is used for continuous vegetation such as grassland and crops, and gost model is used for forest and mountain vegetation. Using the reference map generated by the measured ground data of the forests in the upper reaches of Heihe River and the oasis in the middle reaches, and scaling up the corresponding high-resolution reference map to 1km resolution, compared with the Lai product, the product has a good correlation between the farmland and the forest area and the reference value, and the overall accuracy basically meets the accuracy threshold of 0.5%, 20% specified by GCOS. By cross comparing this product with Lais products such as MODIS, geov1 and glass, the accuracy of this Lai product is better than that of similar products compared with reference value. In a word, the synthetic Lai data set of 1km / 5 days in Heihe River Basin comprehensively uses multi-source remote sensing data to improve the estimation accuracy and time resolution of Lai parameter products, so as to better serve the application of remote sensing data products.

This data set provides a 1 km resolution Digital Elevation Model (DEM) of Antarctica. The DEM combines measurements from the European Remote Sensing Satellite-1 (ERS-1) Satellite Radar Altimeter (SRA) and the Ice, Cloud, and land Elevation Satellite (ICESat) Geosciences Laser Altimeter System (GLAS). The ERS-1 data are from two long repeat cycles of 168 days initiated in March 1994, and the GLAS data are from 20 February 2003 through 21 March 2008. The data set is approximately 240 MB comprised of two gridded binary files and two Environment for Visualizing Images (ENVI) header files viewable using ENVI or other similar software packages. The data are available via FTP.

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.

This data set is one of the results of the project "Determination of Cultivated Land Use Coefficient and Land Use Change Research in Zhangye City". It is a land use database in Zhangye City based on Landsat TM and ETM remote sensing data. The land use data adopts a hierarchical land cover classification system, which divides the land use types of Zhangye City into 6 first-class categories (cultivated land, forest land, grassland, water area, land for urban and rural industrial and mining residents and unused land) and 25 second-class categories. The data range includes Shandan, Minle, Linze, Gaotai, Sunan Yugu Autonomous County and Ganzhou District. The classification standard adopts the land use classification standard used by the Chinese Academy of Sciences since 1986. The data type is vector polygon and stored in Shape format. The data range covers Zhangye City.

The data set contains observation data from the Tianlaochi small watershed automatic weather station. The latitude and longitude of the station are 38.43N, 99.93E, and the altitude is 3100m. Observed items are time, average wind speed (m/s), maximum wind speed (m/s), 40-60cm soil moisture, 0-20 soil moisture, 20-40 soil moisture, air pressure, PAR, air temperature, relative humidity, and dew point temperature , Solar radiation, total precipitation, 20-40 soil temperature, 0-20 soil temperature, 40-60 soil temperature. The observation period is from May 25, 2011 to September 11, 2012, and all parameter data are compiled on a daily scale.

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”

This data includes experimental data of grassland interception control and observation data of maximum water holding capacity of grassland. The maximum water holding capacity experiment was carried out in 2011. The main vegetation types selected are Carex, Polygonum viviparum, Plantago asiatica and Potentilla chinensis. The maximum water holding capacity experiment was carried out on each type of samples and the samples were photographed. The specific data obtained are shown in the document. The grassland canopy interception was carried out in the growing season of 2012, and was completed by artificial rainfall control experiment. At the end of the growing season, the main types of grassland in the basin were sampled according to grazing and grazing ban. During artificial rainfall, rainfall and penetrating rainfall are recorded every 1min. Finally, the grassland canopy interception is calculated by the difference between rainfall and penetrating rainfall.

In the middle of August 2013, photosynthesis of population was measured, and plant species: red sand. The group photosynthesis measurement system consists of li-8100 closed-circuit soil carbon flux automatic measurement system (li-cor, USA) and assimilation box designed and manufactured by Beijing ligotai science and Technology Co., Ltd. li-8100 is an instrument produced by li-cor company of USA for soil carbon flux measurement. The concentration of CO2 and H2O is measured by infrared gas analyzer. The length, width and height of assimilation boxes were all 50 cm. The assimilator is controlled by li-8100. After the measurement parameters are set, the instrument can run automatically.

A small lysimeter was made by ourselves, which simulated the natural conditions and selected typical desert plants as the object to study the water consumption and its law. Repeat 3 times for each plant. In 2011, the experiment of physiological water demand and water consumption of desert plants was carried out with the soil water content kept at (50 ± 10)% of the field water capacity; in 2012, the experiment of physiological water demand and water consumption was carried out with the soil water content kept at (20 ± 5)% of the field water capacity under stress.

A small lysimeter was made by ourselves, which simulated the natural conditions and selected typical desert plants as the object to study the water consumption and its law. Repeat 3 times for each plant.

The meteorological field is located in 2700m grassland in the Pailougou watershed of Qilian Mountain. The date of data recording is from May 2013 to September 2013, including air humidity at 1.5m, air temperature at 3.0m, atmospheric pressure at 2.8m, precipitation at 1.3m, wind speed at 2.2m and total solar radiation at 3.1m. The units are%, ℃, PA, m, m/s and W·m-2, respectively.

In July and mid August 2012, plant species: Caragana. Using Li-6400 portable photosynthesis system (li-cor, USA) and li-3100 leaf area meter, the photosynthetic physiological characteristics of desert plants were observed. The symbols in the observation data have the following meanings: Obs, number of observations;Photo, net photosynthetic rate, moles of CO2 times m minus 2 times s minus 1; Cond, stomatal conductance, mol H2O•m -- 2•s -- 1;Ci, intercellular CO2 concentration, moles of CO2 times mol-1; Trmmol, transpiration rate, mmol H2O•m -- 2•s -- 1;Vpdl, water vapor pressure deficit, kPa; Area, leaf Area, cm2;Tair, atmospheric temperature, ℃; Tleaf, leaf surface temperature, ℃;CO2R, CO2 concentration in the reference chamber, moles of CO2•mol-1; CO2S, sample chamber CO2 concentration, moles of CO2•mol-1;H2OR, water in the reference chamber, mmol H2O•mol-1; H2OS, sample chamber moisture, mmol H2O•mol-1;PARo, photon flux density, mole •m -- 2•s -- 1; Rh-r, reference room air relative humidity, %;Rh-s, relative humidity of air in sample room, %; PARi, photosynthetic effective radiation, moles •m -- 2•s -- 1;Press, atmospheric pressure, kPa; Others are the state parameters of the instrument at the time of measurement.