Er’ba Reservoir surface temperature of water body can offer in situ calibration data for TASI, WiDAS and L band sensor used in aerospace experiment. Observation Site: This site is 14 KM away from East of ZhangYe city. It’s located in Er’ba village, JianTan town, ZhangYe city. The coordinates of this site: 38°54′57.14" N, 100°36′57.39" E. Observation Instrument: The observation system consists of two SI-111 infrared radiometers (Campbell, USA) and two 109SS temperature probes (Campbell, USA). Two SI-111 sensors, one installed vertically downward to water surface, another face to south of zenith angle 35°. Temperature probes float under water surface at 0 cm. SI-111 sensor installed at 3.0 m height, 3.4 m away from water edge. Observation Time: This site operates from 27 May, 2012 to 27 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： Water surface infrared temperature (by SI-111), sky infrared temperature (by SI-111), water surface temperature (by 109ss) can be obtained. Dataset is stored in *.dat file, which can be read by Microsoft excel or other text processing software (UltraEdit, et. al). Table heads meaning: TarT_Atm, Sky infrared temperature (℃) @ facing south of zenith angle 35°; SBT_Atm, body temperature of SI-111 sensor (℃) measured sky; TarT_Sur, water surface infrared temperature @ 3.0 m height; SBT_Sur, body temperature of SI-111 sensor (℃) measured water surface; WaterT_1, WaterT_2, water surface temperature (℃) measured by 109SS temperature probes. 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.

The data set provided the cloudless Fractional Snow Cover area (FSC) time-series product basing on the MODIS data and covered the Heihe River Basin from January 2010 to December 2013. They also provide the high spatial (500 m) and temporal (1 day) resolution. Firstly, the end-member were automatically extracted by the fast autonomous spectral end-member determination (N-FINDR) maximizing volume iteration algorithm. Combining N-FINDR with the orthogonal subspace projection (OSP) approach, we propose an improved end-member extraction algorithm using a maximizing, volume-based iterative method. All the 6 end-members were extracted including snow, soil, water, bare land, vegetation, and cloud, respectively. Then, the 10-day spectral library time series based on prior knowledge of Heihe basin are built for 2009. The primary data were produced using the fully constrained least squares (FCLS) linear spectral mixture analysis method by the spectral library. Finally，the cubic spline interpolation algorithm were used to the eliminate the cloud pixels completely and obtain the data set. The data are validated by the fractional snow cover derived from Landsat imagery and the results indicate that the improved algorithm can obtain the end-member information accurately, and the retrieved fractional snow cover has better accuracy than the MODIS fractional snow-cover product (MOD10A1). So the data set can provide more accurate input for the hydrology and climate model.

The dataset of ground truth measurement synchronizing with the airborne LiDAR mission and Envisat ASAR was obtained in the Yingke oasis and Huazhaizi desert steppe foci experimental areas on Jun. 19, 2008. The Envisat ASAR data were in AP mode and VV/VH polarization combinations, and the overpass time was approximately at 11:17 (Beijing Time). The observation item was soil moisture by TDR ( the probe with a length of 5cm) in the maize plot of Yingke oasis station, the wheat plot and some temporary sample points (details in GPS.txt).

The dataset of airborne Polarimetric L-band Multibeam Radiometers (PLMR) was acquired on 2 August, 2012, located in the middle reaches of the Heihe River Basin. The aircraft took off at 9:00 am (UTC+8) from Zhangye airport and landed at 14:00 pm, with the flight time of 5 hours. The flight was performed in the altitude of about 2300 m and at the speed of about 220-250 km during the observation, corresponding to an expected ground resolution of about 700 m. The PLMR instrument flown on a small aircraft operates at 1.413 GHz (L-band), with both H- and V-polarizations at incidence angles of ±7.5°, ±21.5° and ±38.5°. PLMR ‘warm’ and ‘cold’ calibrations were performed before and after each flight. The processed PLMR data include 2 DAT files (v-pol and h-pol separately) and 1 KMZ file for each flying day. The DAT file contains all the TB values together with their corresponding beam ID, incidence angle, location, time stamp (in UTC) and other flight attitude information as per headings. The KMZ file shows the gridded 1-km TB values corrected to 38.5 degrees together with flight lines. Cautions should be taken when using these data, as the RFI contaminations are often higher than expected at v-polarization.

The fractional vegetation cover observation was carried out for the typical underlying surface in the lower reaches of the Heihe River Basin during the aviation flight experiment in 2014. The observation started on 24 July, 2014 and finished on 1 August, 2014. 1. Observation time On days of 24 July, 27 July, 30 July, 31 July and 1 August, 2014 2. Samples method Large areas with homogeneous vegetation (greater than 100 m * 100 m) were chosen as the observation samples. And forty field samples were selected according to the characteristics of vegetation distribution in the low reaches. The land-use types including the cantaloupe, the Tamarix chinensis, the reeds, the weeds, the Karelinia caspica, the Sophora alopecuroides and so on. 3. Observation methods 3.1 Instruments and measurement method Digital photography measurement is implemented to measure the FVC. Plot positions, photographic method and data processing method are dedicatedly designed. In field measurements, a long stick with the camera mounted on one end is beneficial to conveniently measure various species of vegetation, enabling a larger area to be photographed with a smaller field of view. The stick can be used to change the camera height; a fixed-focus camera can be placed at the end of the instrument platform at the front end of the support bar, and the camera can be operated by remote control. 3.2 Photographic method The photographic method used depends on the species of vegetation and planting pattern. A long stick with the camera mounted on one end is used for the Tamarix chinensisi and reeds. For the Tamarix chinensisi and reeds, rows of more than two cycles should be included in the field of view (<30), and the side length of the image should be parallel to the row. If there are no more than two complete cycles, then information regarding row spacing and plant spacing are required. The FVC of the entire cycle, that is, the FVC of the quadrat, can be obtained from the number of rows included in the field of view. For other vegetation , the photos of FVC were obtained by directly photographing for the lower heights of the vegetation. 3.3 Method for calculating the FVC The detail method of the FVC calculation can be found in the reference below. Many methods are available to extract the FVC from digital images, and the degree of automation and the precision of identification are important factors that affect the efficiency of field measurements. This method, which is proposed by the authors, has the advantages of a simple algorithm, a high degree of automation and high precision, as well as ease of operation (see the reference). 4 Data storage The observation recorded data were stored in excel and the original FVC data were stored in photos.

The dataset of airborne LiDAR mission in the Dayekou flight zone on Jun. 20, 2008 included peak pulse data (*.LAS), full waveform data (.lgc), CCD photos, DEM, DSM and DOM. The DEM, DSM and DOM data are stored along with the Dataset of airborne LiDAR mission in the Dayekou flight zone on Jun. 23, 2008. The flight routes were as follows: {| ! flight route ! startpoint lat ! startpoint lon ! endpoint lat ! endpoint lon ! altitude (m) ! length (km) ! photos |- | 1 || 38°32′05.38″ || 100°12′24.59″ || 38°29′32.76″ || 100°18′35.69″ || 3650 || 10.1 || 49 |- | 2 || 38°32′11.13″ || 100°12′28.42″ || 38°29′42.06″ || 100°18′30.89″ || 3650 || 9.9 || 46 |- | 3 || 38°32′16.88″ || 100°12′32.24″ || 38°29′47.81″ || 100°18′34.72″ || 3650 || 9.9 || 47 |- | 4 || 38°32′22.63″ || 100°12′36.07″ || 38°29′56.20″ || 100°18′32.15″ || 3650 || 9.7 || 45 |- | 5 || 38°32′28.38″ || 100°12′39.90″ || 38°30′02.62″ || 100°18′34.33″ || 3650 || 9.7 || 47 |- | 6 || 38°32′37.44″ || 100°12′35.66″ || 38°30′10.63″ || 100°18′32.68″ || 3650 || 9.8 || 44 |- | 7 || 38°32′46.50″ || 100°12′31.43″ || 38°30′19.72″ || 100°18′28.37″ || 3650 || 9.8 || 47 |}

The object of this dataset is to support the atmospheric correction data for the satellite and airborne remote-sensing. It provides the atmospheric aerosol and the column content of water vapor. The dataset is sectioned into two parts: the conventional observations data and the observations data synchronized with the airborne experiments. The instrument was on the roof of the 7# in the Wuxing Jiayuan community from 1 to 24 in June. After 25 June, it was moved to the ditch in the south of the Supperstaiton 15. The dataset provide the raw observations data and the retrieval data which contains the atmosphere aerosol optical depth (AOD) of the wavebands at the center of 1640 nm, 1020 nm, 936 nm, 870 nm, 670 nm, 500 nm, 440 nm, 380 nm and 340 nm, respectively, and the water vapor content is retrieved from the band data with a centroid wavelength of 936 nm. The continuous data was obtained from the 1 June to 20 September in 2012 with a one minute temporal resolution. The time used in this dataset is in UTC+8 Time. Instrument: The sun photometer is employed to measure the character of atmosphere. In HiWATER, the CE318-NE was used.

The data set include crop leaf stomatal conductance observed at four sample regions, that is the soil moisture control experimental field at Daman county, and the super station, and Shiqiao sample plots at Wuxing village in Zhangye city. 1) Objective Crop leaf stomatal conductance, a key biophysical parameter, was observed as model parameter or a priori knowledge for crop growth model, or evapotranspiration estimation. 2) Measuring instruments Leaf porometer. 3) Measuring site a. the soil moisture control experimental field at Daman county, Twelve soil water treatments are set. The crop leaf stomatal conductance for each treatment is measured on 17, 23 and 29 May, and 3, 9, 14 and 24 June, and 5 and 12 July. b. the Super Station The crop leaf stomatal conductance at the super station is measured on 22 and 28 May, 5, 11, 18, and 25 June, and 1, 8, 15, 22 and 31 July, 9, 15 and 22 August, and 3 and 11 September. c. the Shiqiao sample site The crop leaf stomatal conductance at the Shiqiao village is measured on 17, 22 and 28 May, 4, 11, 17 and 25 June, 1, 8, 15, 22, and 30 July, 8, 16 and 27 August, and 9 September. 4) Data processing The observational data was recorded in the sheets and reorganized in the EXCEL sheets. The time used in this dataset is in UTC+8 Time.

The dataset of ground truth measurements synchronizing with Envisat ASAR was obtained in No. 1 and 2 quadrates of the Biandukou foci experimental area on Oct. 18, 2007, during the pre-observation period. The ASAR data were in AP mode and VV/VH polarization combinations, and the overpass time was approximately at 11:17 BJT. Both the quadrates were divided into 3×3 subsites, with each one spanning a 30×30 m2 plot. 25 sampling points were chosen, including centers and corners. Simultaneous with the satellite overpass, numerous ground data were collected: the soil temperature , volumetric soil moisture (cm^3/cm^3), soil salinity (s/m), soil conductivity (s/m) by the Hydra probe, the surface radiative temperature by the handheld infrared thermometer, gravimetric soil moisture, volumetric soil moisture, and soil bulk density by drying soil samples from the cutting ring (100cm^3). Meanwhile, vegetation parameters as height, coverage and water content were also observed. Those provide reliable ground data for the development and validation of soil moisture, soil freeze/thaw algorithms and the forward model from active remote sensing approaches.

The aim of the simultaneous observation of land surface temperature is obtaining the land surface temperature of different kinds of underlying surface, including greenhouse film, the roof, road, ditch, concrete floor and so on, while the sensor of thermal infrared go into the experimental areas of artificial oases eco-hydrology on the middle stream. All the land surface temperature data will be used for validation of the retrieved land surface temperature from thermal infrared sensor and the analysis of the scale effect of the land surface temperature, and finally serve for the validation of the plausibility checks of the surface temperature product from remote sensing. 1. Observation time and other details On 25 June, 2012, ditch and asphalt road surface temperatures were observed once every five minutes using handheld infrared thermometers recorded. On 26 June, 2012, ditch and asphalt road surface temperatures were observed once every five minutes using handheld infrared thermometers while greenhouse film and concrete floor surface temperatures were observed once every one second using self-recording point thermometer. On 29 June, 2012, concrete floor surface temperatures were observed continuously using handheld infrared thermometers during the sensor of TASI go into the region. At the same time, greenhouse film and concrete floor surface temperatures were observed once every one second using self-recording point thermometer. On 30 June, 2012, asphalt road, ditch, bare soil, melonry and ridge of field surface temperatures were observed continuously using handheld infrared thermometers during the sensor of TASI go into the region. At the same time, greenhouse film and concrete floor surface temperatures were observed once every one second using self-recording point thermometer. On 10 July, 2012, asphalt road, ditch, bare soil, melonry and ridge of field surface temperatures were observed once every one minute using handheld infrared thermometers during the sensor of TASI go into the region. At the same time, concrete floor surface temperatures were observed once every six second using self-recording point thermometer. On 26 July, 2012, asphalt road, concrete floor, bare soil and melonry surface temperatures were observed once every one minute using handheld infrared thermometers during the sensor of WiDAS go into the region. At the same time, greenhouse film and concrete floor surface temperatures were observed once every six second using self-recording point thermometer. On 2 August, 2012, corn field and concrete floor surface temperatures were observed using handheld infrared thermometers. At the same time, greenhouse film and concrete floor surface temperatures were observed once every six second using self-recording point thermometer. For corn field, twelve sites were selected according to the flight strip of the WiDAS sensor, and for each site one plot surface temperatures were recorded continuously during the sensor of WiDAS go into the region. On 3 August, 2012, corn field and concrete floor surface temperatures were observed using handheld infrared thermometers. At the same time, greenhouse film and concrete floor surface temperatures were observed once every six second using self-recording point thermometer. For corn field, fourteen sites were selected according to the flight strip of the WiDAS sensor, and for each site three plots surface temperatures were recorded continuously during the sensor of WiDAS go into the region. 2. Instrument parameters and calibration The field of view of the self-recording point thermometer and the handheld infrared thermometer are 10 and 1 degree, respectively. The emissivity of the latter was assumed to be 0.95. The observation heights of the self-recording point thermometer for the greenhouse film and the concrete floor were 0.5 m and 1 m, respectively. All instruments were calibrated three times (on 6 July, 5 August and 20 September, 2012) using black body during observation. 3. Data storage All the observation data were stored in excel.

The dataset of photosynthesis was observed by LI-6400XT Portable Photosynthesis System in the artificial oasis eco-hydrology experimental area of the Heihe River Basin. Observation items included two main crops in the middle reaches of Heihe river: wheat and maize, which located in the town of Pingchuan in Linze and the Super Station of Wuxing, respectively. Observation periods lasted from mid-May to September. This dataset included the raw observation data and the pretreatment data of wheat and maize observed by LI-6400 during the observation periods. Objectives of observation: The photosynthetic datasets can be used in the study of plant physiological ecology characteristic and the simulation and validation for the eco-hydrological models. Instrument and theory of the observation: (1) Measuring instrument: LI-6400XT Portable Photosynthesis System; (2) Measuring theory: Using the infrared gas analyzer to measure the change of CO2 concentration, and then measuring the differences of CO2 concentration between the sample chamber and the referenced chamber so as to acquire the net productivity of the leaf. Time and site of observation: (1) Observation site of the wheat: in the town of Pingchuan in Linze; Observation time: 2012-05-17，2012-06-08 to 2012-6-13; (2) Observation site of the maize: in the Super Station of Wuxing; Observation time: from 2012-05-19 to 2012-08-15. The time used in this dataset is in UTC+8 Time. Data processing: The raw data of LI-6400 were archived in text format and can be opened by text editor or excel, the preprocessed data were in Excel format. Every time period of observation was archived in a single document, named as “date + type + time”, every leaf was recorded 3 times, and then added a remark.

The dataset of spectral reflectance measurements was obtained in the A'rou foci experimental area on Mar. 12, 2008. The land was covered with snow 10cm deep. Observed objects included snow, sandstone, grass and ice. The 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. Raw data were binary files direct from ASD (by ViewSpecPro).