Through the observation of tissue sections of root system, stem and leaf of Ammopiptanthus mongolicus, it is found that Ammopiptanthus mongolicus has morphological characteristics of efficient absorption, transportation and storage of water. Through the study of physiology and biochemistry of Ammopiptanthus mongolicus, the physiological and molecular mechanism of Ammopiptanthus mongolicus adapting to water stress through osmotic adjustment under drought stress was preliminarily confirmed. Through the study of physiological characteristics of Ammopiptanthus mongolicus under drought conditions, the change rule of proline accumulation with the process of drought stress was found, which may participate in the regulation mechanism of Ammopiptanthus mongolicus adapting to water stress as an important osmotic regulator. Furthermore, 7 full-length genes involved in proline synthesis, metabolism and transport of Ammopiptanthus mongolicus were cloned and obtained.
SU Yanhua
This dataset is the FPAR observation in the artificial oasis experimental region of the middle stream of the Heihe River Basin. The observation period is from 24 May to 19 July, 2012 (UTC+8). Measurement instruments: AccuPAR (Beijing Normal University) Measurement positions: Core Experimental Area of Flux Observation Matrix 18 corn samples, 1 orchard sample, 1 artificial white poplar sample Measurement methods: For corn, to measure the incoming PAR on the canopy, transmission PAR under the canopy, reflected PAR on the canopy, reflected PAR under the canopy. For orchard and white poplar forest, to measure the incoming PAR outside of the canopy, transmission PAR under the canopy. Corresponding data: Land cover, plant height, crop rows identification
MA Mingguo
China 1:100000 data of land use is a major application in the Chinese Academy of Sciences "five-year" project "the national resources and environment remote sensing macroscopic investigation and study of dynamic organized 19 Chinese Academy of Sciences institute of remote sensing science and technology team, by means of satellite remote sensing, in three years based on Landsat MSS, TM and ETM remote sensing data established China 1:100000 images and vector of land use database.The main contents include: China 1:100,000 land use data;China 1:100,000 land use graph data and attribute data. The data was directly clipped from China's 1:100,000 land-use data.A hierarchical land cover classification system was adopted for the land use data of heihe basin of 1:100,000, and the whole basin was divided 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 26 secondary categories.The data type is vector polygon, which is stored in Shape format.There are two types of data projection: WGS84/ALBERS;Data coverage covers the new heihe watershed boundary (lack of outer Mongolia data). Land use classification attributes: The first class type and the second class type attributes encode the spatial distribution position Cultivated paddy field 113 is mainly distributed in alluvial plain, basin and valley Cultivated paddy field 112 distributed in hilly valley narrow valley platform or beach (with irrigation conditions) Cultivated paddy field 111 is mainly distributed in mountain valley narrow valley platform or beach (with better irrigation conditions) Arable land 124 is mainly distributed in mountainous areas, the slope is generally more than 25 degrees (belongs to the steep slope hanging land), should be returned to forest. Cultivated dry land 123 is mainly distributed in basins, piedmont belts, river alluvial, diluvial or lacustrine plains (water shortage and poor irrigation conditions). Cultivated dry land 122 is mainly distributed in hilly areas (shaanxi, gan, ning, qing).In general, the plot is distributed on gentle slopes and x and sockets of hills. Arable land 121 is mainly distributed in the mountainous area, with an elevation of 4000 meters below the slope (gentle slope, mountainside, steep slope platform, etc.) and mountain front belt. Woodlands have woodlands (trees) 21 mainly distributed in the mountains (below 4000 meters above sea level) or in the slope, valley two slopes, mountain tops, plains.In qinghai nanshan, qilian mountains are. Woodland shrub 22 is mainly distributed in the higher mountain areas (below 4500 m), most of the distribution of hillside and valley and sand. Forest dredging 23 mainly distributed in the mountains, hills, plains and sandy land, gobi (soil, gravel) edge. Other woodlands 24 are mainly distributed in the oasis ridge, river, roadside and rural residential areas around. Grassland 31 is generally distributed in mountainous areas (gentle slopes), hills (steep slopes) and interriver beaches, gobi desert, sandy hills, etc. The covered grassland 32 is mainly distributed in dry places (next door low-lying land and sandy hills, etc.). Grassland low cover grassland 33 mainly grows in drier places (loess hills and sandy edges). The river channel 41 is mainly distributed in the plain, the cultivated land between the rivers and the valleys in the mountains. Water lakes are mainly distributed in low-lying areas. The reservoirs are mainly distributed in the intermountain lowlands and intersandy hills in qinghai province. Water area glaciers and permanent snow 44 mainly distributed in the plain, the valley between the river, there are surrounding residents and arable land. Waters and beaches are mainly distributed on the top of (over 4000) mountains.
WANG Jianhua, LIU Jiyuan
The dataset of ground truth measurement synchronizing with MODIS was obtained in the Linze grassland foci experimental area on Jun. 22, 2008. Simultaneous east-west ground measurements on the canopy temperature, the half-height temperature and the land surface radiative temperature were carried out by the hand-held infrared thermometer at intervals of 125m in 8 quadrates (2km×2km), No.1 quadrate (H01-H08) on Jun. 22, No.2 quadrate (H09-H16) on Jun. 23,No.3 quadrate (H17-H24) on Jun. 22, No.4 quadrat (H25-H32) on Jun. 23, No.5 quadrate (H33-H40) on Jun. 22, No.6 quadrate (H41-H48) on Jun. 23, No,7 quadrate (H49-H56) and No.8 quadrate (H57-H64) on Jun. 23. Data were archived in Excel format. See WATER: Dataset of setting of the sampling plots and stripes in the foci experimental area of Linze station for more information.
CHAO Zhenhua, NIAN Yanyun, WANG Xufeng, LIANG Wenguang
This data set is collected according to the output results of tesim ecological process model, including biomass, plant N and P content, evapotranspiration, NPP and other model output results. Some of the results are obtained by field measurement, some by laboratory analysis of field samples, some by literature.
PENG Hongchun
This dataset contains the LAI measurements from the Sidaoqiao in the downstream of the Heihe integrated observatory network from June 16 to October 18 in 2018. The site was located in Ejina Banner in Inner Mongolia Autonomous Region. The elevation is 870 m. There are 2 observation samples, around Sidaoqiao superstation (101.1374E, 42.0012N) and Mixed forest station (101.1335E, 41.9903N), each of which is about 30m×30m in size. Five sub-canopy nodes and one above-canopy node are arranged in each sample. The LAI data is obtained from LAINet measurements following four steps: (1) the raw data is light quantum (level 0); (2) the daily LAI can be obtained using the software LAInet (level 1); (3) the invalid and null values are screened and using the 7 days moving averaged method to obtain the processed LAI (level 2); (4) for the multi LAINet nodes observation, the averaged LAI of the nodes area is the final LAI (level 3). The released data are the post processed LAI products and stored using *.xls format. For more information, please refer to Liu et al. (2018) (for sites information), Qu et al. (2014) for data processing) in the Citation section.
Qu Yonghua, XU Ziwei, LI Xin
Trunk sap flow is an effective tool for measuring transpiration of a single plant. In this project, the trunk sap flow data of Populus euphratica in the lower reaches of Heihe River was measured by HRM (ICT, Australia) with a frequency of 0.5h. In the growth season of 2012-2013, the installation location is the north and lateral roots (50cm underground depth, 30cm away from the trunk) at the DBH (1.3m).
SI Jianhua
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.
SONG Jinling, FU Zhuo, LI Shihua, ZOU Jie, ZHANG Xuelong, WANG Shunli, ZHAO Ming, LEI Jun, NIU Yun, LUO Longfa, LING Feilong, HE Qisheng, CHEN Erxue
The dataset includes the chlorophyll content of vegetation in different site which has different types of vegetation, acquired on 8 July, 2012, in order to validate the Chlorophyll products. Observation instruments: Sampling, Acetone extraction method Measurement methods: To analyze the influence height on chlorophyll , we select 12 different corn samples based on the height of corn. To compare the chlorophyll content of different types of vegetation, we also select 3 types of vegetation sample on the first EC tower, 1 beans sample near the seventeenth EC tower and 3 reed samples on wetland. A total of selected 19 different samples are analyzed in the laboratory in the College of Life Science, Hexi. We extract chlorophyll a, chlorophyll b, the content of total chlorophyll of selected samples. Dataset contents: Chlorophyll a, chlorophyll b, the content of total chlorophyll Measurement time: 8 July, 2012
Jia Shuzhen
This dataset contains the LAI measurements from the Daman superstation in the middle reaches of the Heihe integrated observatory network from June 11 to September 18 in 2018. The site (100.372° E, 38.856°N) was located in the maize surface, near Zhangye city in Gansu Province. The elevation is 1556 m. There are 3 observation samples, each of which is about 30m×30m in size, and the latitude and longitude ranges are (100.373297°E~100.374205°E, 38.857871°N~38.858390°N), (100.373918°E~100.373897°E, 38.854025°). N~38.854941°N), (100.368007°E~100.369044°E, 38.850678°N~38.851580°N). Five sub-canopy nodes and one above-canopy node are arranged in each sample. The LAI data is obtained from LAINet measurements following four steps: (1) the raw data is light quantum (level 0); (2) the daily LAI can be obtained using the software LAInet (level 1); (3) the invalid and null values are screened and using the 7 days moving averaged method to obtain the processed LAI (level 2); (4) for the multi LAINet nodes observation, the averaged LAI of the nodes area is the final LAI (level 3). The released data are the post processed LAI products and stored using *.xls format. For more information, please refer to Liu et al. (2018) (for sites information), Qu et al. (2014) for data processing) in the Citation section.
LIU Shaomin, Qu Yonghua, XU Ziwei, LI Xin
This dataset includes 5 sub-datasets obtained from measurements in the flux observing matrix at observing site No.15 (the Daman superstation) and 13. Specifically, the sub-datasets include the following: (1) a dataset that contains atmospheric water vapor D/H and 18O/16O isotopic and flux ratio measurements from site No.15 from 27 May to 21 September in 2012, (2) a dataset that contains D/H and 18O/16O isotopic ratios of water in soil and in corn xylem at site No.15 from 27 May to 21 September 2012, (3) a dataset that contains atmospheric water vapor D/H and 18O/16O isotopic ratios at site No.13 when airborne surveys occurred, and (4) a dataset that contains D/H and 18O/16O isotopic ratios of water in soil and in corn xylem at sites No.13 and 15 when airborne surveys occurred, (5) a dataset that contains the ratios of evaporation and transpiration to evapotranpiration at site No.15. The experiment area was located in a corn cropland in the Daman irrigation district of Zhangye, Gansu Province, China. The positions of observing sites No.15 and 13 were 100.3722° E, 38.8555° N and 100.3785° E, 38.8607° N, respectively, with an elevation of 1552.75 m above sea level. The atmospheric water vapor D/H and 18O/16O isotopic and flux ratios at site No.15 were continuously measured using an in situ observation system. The system consisted of an H218O, HDO and H2O analyzer (Model L1102-i, Picarro Inc.), a CTC HTC-Pal liquid auto sampler (LEAP Technologies) and a multichannel solenoid valve (Model EMT2SD8 MWE, Valco Instruments CO. Inc.). The heights of the two intakes were 0.5 and 1.5 m above the corn canopy. The water vapor D/H and 18O/16O isotopic ratio analyzer recorded signals at 0.2 Hz; data were recorded for 2 minutes per intake. The data were block-averaged to hourly intervals. The sampling frequency of soil and xylem at site No. 15 was 1-3 days. The atmospheric water vapor D/H and 18O/16O isotopic and flux ratios at site No.13 were measured using a cold traps/mass spectrometer. The sampling frequency of atmospheric water vapor, soil water and xylem water at site No.13 was the same as that of the airborne surveys. Briefly, the Picarro analyzer measurements were calibrated during every 3 h switching cycle using a two-point concentration interpolation procedure in which the water vapor mixing ratio was dynamically controlled to track the ambient water vapor mixing ratio. Possible delta stretching effects were not considered. A schematic diagram of the Picarro analyzer and its operation principles and calibration procedure are described elsewhere in the literature (Huang et al., 2014; Wen et al. 2008, 2012). The dataset of atmospheric water vapor D/H and 18O/16O isotopic and flux ratios at site No.15 includes the following variables: Timestamp (time, timestamp without time zone), Number (available record number), δD for r1 (δD for the lower intake, ‰), δD for r2 (δD for the higher intake, ‰), δ18O for r1 (δ18O for the lower intake, ‰), δ18O for r2 (δ18O for the higher intake, ‰), vapor mixing ratio for r1 (vapor mixing ratio for the lower intake, mmol/mol), vapor mixing ratio for r2 (vapor mixing ratio for the higher intake, mmol/mol), δET_D (δD of evapotranspiration, ‰), and δET_18O (δ18O of evapotranspiration, ‰). The dataset of D/H and 18O/16O isotopic ratios of water in soil and in corn xylem at site No.15 includes the following variables: Timestamp (time, timestamp without time zone), Remark (treatment: soil without mulch (Ld)=1; soil with mulch (Fm)=2; soil with male corns (F)=3; Xylem=4), δD (‰), and δ18O (‰). The dataset for the ratio of soil evaporation and transpiration to the evapotranspiration at site 15 includes the following variables: Timestamp (time, timestamp without time zone), E/ET (ratio of soil evaporation to the evapotranspiration, %), and T/ET (ratio of transpiration to the evapotranspiration, %). The mean (±one standard deviation) ratio of transpiration to evapotranspiration was 86.7±5.2% (the range was 71.3 to 96.0%). The mean (±one standard deviation) ratio of soil evaporation to the evapotranspiration was 13.3 ±5.2% (the range was 4.0 to 28.7%). The dataset of atmospheric water vapor D/H and 18O/16O isotopic ratio at site No. 13 when airborne surveys occurred includes the following variables: Timestamp1 (start time, timestamp without time zone), Timetamp2 (end time, timestamp without time zone), Height (observation height, cm), δD (‰), and δ18O (‰). The dataset of D/H and 18O/16O isotopic ratios of water in soil and in corn xylem at sites No. 13 and 15 when airborne surveys occurred include the following variables, Timestamp (time, timestamp without time zone), Remark (treatment: soil without mulch (Ld)=1; soil with mulch (Fm)=2; Xylem=4), δD (‰), δ18O (‰), and Location (observing site 13 or 15) . The missing measurements were replaced with -6999. For more information, please refer to Liu et al. (2016) (for multi-scale observation experiment or sites information), Wen et al. (2016) (for data processing) in the Citation section.
WEN Xuefa, LIU Shaomin, LI Xin
The dataset of water content of forest canopy components (the twig and the leaf) measurements was obtained at the super site (100m×100m) around the Dayekou Guantan forest station on Jun. 5, 2008. The sample tree was selected according to different diameters at breast height. 5 diameter classes were divided and in each class, 10 trees were selected and altogether 30 trees were selected as sampling trees. Branches in different parts were picked by the tree pruner and the twig and the leaf were separated manually, whose green weight was measured by the scales on the scene and dry weight by oven drying in the lab. Those provide reliable data for the reconstruction of the 3D structure of the forest scene, and for modelling active and passive remote sensing mechanisms and the simulation of remote sensing images.
BAI Lina, TIAN Xin, WANG Bengyu, CHEN Erxue
The sampling and distribution of plant materials in the arid regions of the middle and lower reaches of Heihe River Basin. The plants are mainly shrubs and a few herbs. The numbering of plant materials is consistent with the morphological structural characteristics analysis table and is used in correspondence with each other.
LIU Yubing
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.
BAI Yunjie, CAO Yongpan, CHE Tao, DU Ziqiang, HAO Xiaohua, WANG Zhixia, WU Yueru, CHAI Yuan, CHANG Sheng, QIAN Yonggang, SUN Xiaoqing, WANG Jindi, YAO Dongping, ZHAO Shaojie, ZHENG Yue, ZHAO Yingshi, LI Xiaoyu, PATRICK Klenk, HUANG Bo, LI Shihua, LUO Zhen
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.
FAN Wenjie
The dataset contains phenological camera observation data collected at the Arou Superstation in the midstream of the Heihe integrated observatory network from June 13 to November 16, 2018. The instrument was developed with data processed by Beijing Normal University. The phenomenon camera integrates data acquisition and data transmission functions. The camera captures high-quality data with a resolution of 1280×720 by looking-downward. The calculation of the greenness index and phenology are following 3 steps: (1) calculate the relative greenness index (GCC, Green Chromatic Coordinate, calculated by GCC=G/(R+G+B)) according to the region of interest, (2) perform gap-filling for the invalid values, filtering and smoothing, and (3) determine the key phenological parameters according to the growth curve fitting (such as the growth season start date, Peak, growth season end, etc.) There are also 3 steps for coverage data processing: (1) select images with less intense illumination, (2) divide the image into vegetation and soil, and (3) calculate the proportion of vegetation pixels in each image in the calculation area. After the time series data is extracted, the original coverage data is smoothed and filtered according to the time window specified by the user, and the filtered result is the final time series coverage. This data set includes relative greenness index (GCC), phenological phase and fractional cover (FC). Please refer to Liu et al. (2018) for sites information in the Citation section.
Qu Yonghua, XU Ziwei, LI Xin
The survey area is 101 ° 3 ′ 13.265 ″ longitude, 42 ° 1 ′ 53.660 ″ latitude and 883.54m altitude. The sample area is 100 × 100m, and the sample area is 20 × 20m. The crown width, height and DBH of Populus euphratica were investigated.
SI Jianhua
The dataset of the survey at the sampling plots in the transit zone between oasis and desert was obtained in the Linze station foci experimental area. Observation items included: (1) soil moisture and temperature of the soil profiles (0-10cm, 10-20cm, 20-30cm and 30-40cm) measured by the cutting ring method (50cm^3, once each layer) and the probe thermometer (15cm, twice each layer) on May 25, 2008. Data were archived as Excel files. (2) biomass (green weight and dry weight, samples from 0.5m×0.5m) with photos measured by the plant harvesting in LY07 quadrate on Jun. 22, 2008. Data were archived as Excel files. (3) vegetation coverage measured by the diagonal method on Jun. 22, 2008. By estimating the coverage along the two diagonals, the total coverage of the plot can be developed. Data were archived as Excel files.
GAO Song, PAN Xiaoduo, Qian Jinbo, SONG Yi, WANG Yang, ZHU Shijie
Leaf water potential is an important indicator of plant growth. In this project, Populus euphratica and Tamarix were selected in the lower reaches of Heihe River. Wp4c was used for 15 days to measure leaf water potential data before dawn, noon and sunset, which can provide basic data for understanding the growth conditions of desert plants.
SI Jianhua
The dataset of the structure parameter measurements for afforested forest was obtained in the Zhangye city foci experimental area. To be specific, the full height was measured by the altimeter 12km east of Zhangye city on May 30, the LAI by LAI-2000 in Linze grassland foci experimental area on Jun. 5, measurements in Yingke oasis on Jun. 14 and 17, afforested forest parameters in Jiulongjiang forest farm on Jun. 28 and LAI by LAI-2000 in Huazhaizi desert steppe foci experimental area on Jul.1, 2008. 6 files in total were archived, zhangyefroestpark.xls (31K, 5-30), Linzestation.xls (16K, 6-4), yingke1.xls ( 21K, 6-14), yingke2.xls (21K, 6-17), yingke3.xls (16K, 7-1), and jiulongjiangforestfarm.xls ( 22K, 6-28) respectively.
GAO Shuai, QIN Yuchu, WU Mingquan, WU Chaoyang
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