The leaf epidermis micromorphological structure of the constructive species in the arid area of the middle and lower reaches of Heihe River Basin. The plant material number is consistent with the number in the sampling table. Refer to the sampling table number to determine the material and its distribution position.
LIU Yubing
The algorithm firstly adopts the canopy BRDF model and represents the canopy reflectivity as a function of a series of parameters such as LAI/FAPAR, wavelength, reflectivity of soil and leaves, aggregation index, incidence and observation Angle.The parameter table is established for several key parameters as the input of inversion.Then input the pre-processed surface reflectance data and land cover data, and invert LAI products by look-up table (LUT) method.See references for detailed algorithms. Image format: tif Image size: about 1M per scene Time range: 2000-2012 Temporal resolution: 8 days Spatial resolution: 1km
FAN Wenjie
This dataset is the Fractional Vegetation Cover observation in the artificial oasis experimental region of the middle stream of the Heihe River Basin. The observations lasted for a vegetation growth cycle from May 2012 to September 2012 (UTC+8). Instruments and measurement method: Digital photography measurement is implemented to measure the FVC. Plot positions, photographic method and data processing method are dedicatedly designed. Details are described in the following: 0. 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. 1. For row crop like corn, the plot is set to be 10×10 m2, and for the orchard, plot scale is 30×30 m2. Shoot 9 times along two perpendicularly crossed rectangular-belt transects. The picture generated of each time is used to calculate a FVC value. “True FVC” of the plot is then acquired as the average of these 9 FVC values. 2. The photographic method used depends on the species of vegetation and planting pattern: Low crops (<2 m) in rows in a situation with a small field of view (<30 ), rows of more than two cycles should be included in the field of view, 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. 3. High vegetation in rows (>2 m) Through the top-down photography of the low vegetation underneath the crown and the bottom-up photography beneath the tree crown, the FVC within the crown projection area can be obtained by weighting the FVC obtained from the two images. Next, the low vegetation between the trees is photographed, and the FVC that does not lie within the crown projection area is calculated. Finally, the average area of the tree crown is obtained using the tree crown projection method. The ratio of the crown projection area to the area outside the projection is calculated based on row spacing, and the FVC of the quadrat is obtained by weighting. 4. FVC extraction from the classification of digital images. 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.
MU Xihan, HUANG Shuai, MA Mingguo
Vegetation survey data is essential to study the structure and function of the ecosystems. The North Tibet is abundant in grassland ecosystems, including alpine meadow, alpine grassland, and alpine degraded grassland. Due to the unique geographical location, high altitude and anoxic environment, the community survey data in the North Tibetan Plateau is relatively rare. Based on the accumulation of preliminary work, the research team carried out a more comprehensive vegetation survey in 15 counties of the North Tibetan Plateau in the growing season of 2017. This data set includes biomass data inside and outside the fences of the 23 sampling plots from Nagqu to Ritu of the North Tibet Transect. This data set can be used for productivity spatial analysis and mode calibration.
ZHANG Xianzhou, NIU Ben
The research project on the breeding strategies of desert plants in hexi region of gansu province belongs to the national natural science foundation "environment and ecological science in western China" major research plan, led by professor an lizhe of lanzhou university. The project runs from January 2004 to December 2007. Remittance data of the project: 1. Effect of super - dry preservation on seeds The data is in Word format and contains a lot of analysis charts. A comparative study was conducted on the changes of vitality of overlord seeds and rhizoma coptidis seeds stored at 45℃, room temperature and 15℃ respectively, and the effects of dampening treatment, artificial aging and ultra-dry treatment on electrical conductivity and physiological activity indexes of seeds were conducted.The details are as follows: Energy change of seeds was preserved at 45℃ FIG. 1 germination rate (%) of overlord seeds stored at 45℃、FIG. 2 germination index of overlord seeds stored at 45℃、FIG. 3 vigor index of the seeds stored at 45℃. Change of seed vigor at room temperature FIG. 4 germination rate (%) of overlord seeds stored at room temperature、FIG. 5 germination index of overlord seeds stored at room temperature、FIG. 6 vigor index of overlord seeds preserved at room temperature. 15℃ preservation of seed vitality changes FIG. 7 germination rate of overlord seeds stored at 15℃ (%)、FIG. 8 germination index of alba seeds stored at 15℃、FIG. 9 vigor index of the seeds stored at 15℃. Changes of seed vigor of rhizoma coryzae at 45℃ FIG. 10 germination rate (%) of rhizoma coptidis seeds stored at 45℃、FIG. 11 germination index of the seeds of rhizoma coryzae at 45℃、FIG. 12 vigor index of seeds of corydalis corydalis preserved at 45℃. Changes of seed vigor of rhizoma coryzae at room temperature FIG. 13 germination rate (%) of rhizoma corydalis seeds preserved at room temperature、FIG. 14 germination index of seeds preserved at room temperature、FIG. 15 vigor index of seeds of corydalis corydalis preserved at room temperature Changes of seed vigor of rhizoma corydalis in 15℃ storage FIG. 16 germination rate (%) of rhizoma coptidis seeds stored at 15℃、FIG. 17 germination index of the seeds of rhizoma coptidis preserved at 15℃、FIG. 18 vigor index of seeds of corydalis sativus preserved at 15℃ Effect of slow wetting treatment on relative conductivity of seeds FIG. 28 changes in the relative conductivity of arrobatus seeds without dampening treatment、FIG. 29 changes of relative conductivity of overlord seeds after slow wetting treatment、FIG. 31 changes of relative electrical conductivity of seeds of rhizoma coryzae after dampening treatment Effects of artificial aging treatment on seed of archaea chinensis l FIG. 34 effects of artificial aging treatment on germination rate of overlord seeds、FIG. 35 effect of artificial aging treatment on seed vigor index、FIG. 36 effects of artificial aging treatment on the relative conductivity of overlord seeds Effects of artificial aging treatment on seeds of coryza sativa l FIG. 37 effect of artificial aging treatment on germination rate of seeds of coryza sativa l、FIG. 38 effect of artificial aging treatment on seed vigor index of rhizoma coryzae、FIG. 39 effects of artificial aging treatment on the relative electrical conductivity of the seeds of coryza sativa l Effects of artificial aging on the content of aldehydes in seeds after 15 days FIG. 52 effects of artificial aging treatment on the content of aldehydes in the seeds after 15 day、FIG. 53 effects of artificial aging treatment on the content of aldehydes in seeds of prunus chinense after 15 days, Effect of super - dry treatment on physiological activity index of seed Table 31 effect of super - dry treatment on physiological activity index of monkshood seed Table 32 influence of hyperdrying treatment on physiological activity index of seeds of coryza sativa l 2. Micromorphological and structural characteristics of the skin of desert plants (including experimental conditions, microscopic images of the skin microstructure and analysis of distribution of 47 plants, genus, species code, list of length and weight of long and short axes of seeds, and list of seed elements)
AN lizhe
This data includes the fAPAR and Lai data collected in 2011. The acquisition equipment is SunScan and LAI-2000. Among them, fAPAR measures 4 times of spread value. The sampling points are located in Zhangye agricultural demonstration base on July 30, 2011, next to national highway 312 in Ejina banner on August 4, sandaoqiao in Ejina banner on August 5 and Jiuquan Satellite Launch Center on August 6, 2011. Around Zhangye from July 4 to July 15, 2012.
FAN Wenjie
The dataset of object spectral was obtained in the Linze station foci experimental area from May 25 to Jul. 11, 2008. The measurement instrument is ASD Spectroradiometer (350～2 500 nm) from BNU and the reference board (40% before Jun. 15 and 20% hereafter). The selected typical objects included maize field, soil, soil with known moisture and desert scrub. The measured quadrates included Wulidun farmland quadrates (May 28 and 30, Jun. 16 and 29 and Jul. 11), the desert transit zone strips (May 28 and 30 and Jun. 16) and Linze station quadrates (May 23 and Jul. 9) Besides, soil samples were collected inside Linze station quadrates on Jun. 24 and 30, 2008. Raw spectral data were archived as binary files, which were recorded daily in detail, and pre-processed data on reflectance and transmittivity were archived as text files (.txt). See the metadata record “WATER: Dataset of setting of the sampling plots and stripes in the Linze station foci experimental area” for more information of the quadrate locations.
LI Jing, Li Xiangyun, Qu Yonghua, SUN Qingsong, XIAO Zhiqiang, YU Yingjie, LIU Sihan, BAI Yanfen, WANG Yang, CHEN Shaohui, JIANG Hao, LI Shihua
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.
CHEN Erxue, GUO Zhifeng, LIU Qingwang, WANG Bengyu, TIAN Xin, WANG Xinyun, FU Anmin, ZHANG Zhiyu, NI Wenjian, WANG Qiang, CAO Bin, Yang Yongtian, Zhihai Gao, Bingxiang Tan, WANG Dianzhong, ZHANG Yang, ZHAO Liqiong, LIANG Dashuang
This data set is the surface evapotranspiration data of Four Typical Shrub Communities in hulugou watershed. The observation period is from July 16 to August 23, 2013, which is the daily scale data. The data content includes precipitation data, evaporation and infiltration data observed by lysimeter. The data set can be used to analyze the evapotranspiration data of alpine shrub and forest. Data quality information: data quality is high, daily evapotranspiration data observation is complete. Data source description: a small lysimeter with an inner diameter of 25 cm and a depth of 30 cm was selected for evapotranspiration under the canopy. Two lysimeters were set up in each sample plot of evapotranspiration under the Bush, and one lysimeter was set up for each kind of Bush in the transplanting experiment. The undisturbed undisturbed soil column with the same height as the barrel shall be placed in the inner barrel during the layout, and the outer barrel shall be buried in the soil. During the embedding, the outer barrel shall be 0.5-1.0 cm higher than the ground, and the outer edge of the inner barrel shall be designed with a 2.0 cm wide rain shield to prevent the surface runoff from entering the lysimeter. Lysimeter was set up in the nearby meteorological station to measure the evapotranspiration of grassland, and a small evapotranspiration meter with an inner diameter of 25 cm and a depth of 30 cm was set up in the Picea koraiensis forest sample plot to measure the evaporation under the forest. All lysimeters shall be weighed on time at 20:00 every day (electronic balance sensing capacity is 1.0 g, which is equivalent to 0.013 mm evaporation). During observation, windproof treatment shall be done to ensure the accuracy of measurement. Data processing method: evapotranspiration is mainly calculated by mass conservation in lysimeter method. According to lysimeter design principle, evapotranspiration is mainly determined by mass difference in two consecutive days. Because it is weighed every day, it is calculated by water balance.
SONG Yaoxuan, LIU Zhangwen
The monthly average vegetation index data of Heihe River Basin is based on MODIS 1 km and 250 m NDVI products. From 250 m products, the grid value of Heihe River Basin is proposed as precision control, and the 1 km product is modified by HASM method. The monthly average vegetation index of Heihe River Basin from 2001 to 2011 was obtained by fusing multi-source NDVI data using HASM method. Resolution: 1km * 1km The average precipitation data set of Heihe River Basin adopts the data information of 21 meteorological conventional observation stations in Heihe River Basin and its surrounding areas and 13 national reference stations around Heihe River basin provided by Heihe planning data management center. The daily precipitation data of each station from 1961 to 2010 is calculated. If the coefficient of variation is greater than 100%, the daily precipitation distribution trend can be obtained by using the geographic weighted regression to calculate the relationship between the station and the geographical terrain factors; if the coefficient of variation is less than or equal to 100%, the relationship between the station precipitation value and the geographical terrain factors (longitude, latitude, elevation) is calculated by ordinary least square regression, and the daily precipitation score is obtained HASM (high accuracy surface modeling method) was used to fit and modify the residual error after removing the trend. Finally, the trend surface results and residual correction results are added to get the annual average precipitation distribution of Heihe River Basin from 1961 to 2010. Time resolution: annual average precipitation from 1961 to 2010. Spatial resolution: 500M.
YUE Tianxiang, ZHAO Na
The data set include crop biomass observed at four sample regions, that is the soil moisture control experimental field at Daman county, and the EC plots, the super station, and Shiqiao sample plots at Wuxing village in Zhangye city. 1) Objective Crop biomass, a key biophysical parameter, was observed for calibration and validation of crop growth model and the retrieval of other biophysical parameters as well as the application in eco-hydrological models. 2) Measurement instrument: Electronic balance (±0.1g) and oven. 3) Measurement site a. the soil moisture control experimental field at Daman county, Twelve soil water treatments are set. The wheat biomass 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 EC site Maize biomass at 14 EC site (EC-2,EC-3,EC-5,EC-6,EC-7,EC-8,EC-9, EC-10, EC-11, EC-12, EC-13, EC-14, EC-15, EC-16) are measured on 14, 21, 25 and 31 May, 7, 13, 23 and 28 June, 3, 13, 18 and 23 July, 3, 12 and 28 August. c. the super station Maize biomass 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. d. the Shiqiao sample site Maize biomass 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.
Xu Fengying, Wang Jing, Ma Chunfeng, Huang Yongsheng, LI Xin, MA Mingguo
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). Please refer to Liu et al. (2018) for sites information in the Citation section.
Qu Yonghua, XU Ziwei, LI Xin
The dataset of ground truth measurements synchronizing with EO-1 Hyperion was obtained in the Yingke oasis foci experimental area from Sep. 5 to Sep. 10, 2007 during the pre-observation period. It was carried out by the 3rd and 2nd sub-projects of CAS’s West Action Plan along Zhangye city-Yingke oasis-Huazhaizi, and on the very day of 10, one scene of Hyperion was captured. sampling plot time north latitude east longitude elevation notes 1 9:58 38°53′53.2″ 100°26′09.7″ 1500 cauliflower land east to the road 2 10:51 38°52′39.8″ 100°25′33.1″ 1510 cabbage land east to the road 3 11:35 38°52′39.0″ 100°25′34.6″ 1510 east to No. 2 sampling plot, maize and intercropping wheat reaped 4 12:24 38°51′53.0″ 100°25′08.0″ 1510 maize seed 5 13:08 38°51′54.2″ 100°25′09.5″ 1520 north to No. 4 sampling plot, maize and intercropping wheat reaped 6 14:40 38°51′23.5″ 100°24′45.0″ 1510 west to the road, maize seed, serious blights (red spider) 7 15:40 38°49′26.6″ 100°23′23.7″ 1540 intercrop land of sea buckthorn and beet 8 16:18 38°49′06.9″ 100°23′30.5″ 1540 tomato land, rich of amaranth weeds 9 16:18 38°49′06.4″ 100°23′30.8″ 1540 beet land 10 16:18 38°49′06.9″ 100°23′30.5″ 1540 tomato land with less weeds 11 10:30 38°48′28.3″ 100°24′11.4″ 1540 sea buckthorn seedling land west to the road 12 11:24 38°48′09.3″ 100°24′10.1″ 1550 sun flower land east to the road, intercropping wheat reaped 13 12:38 38°46′16.3″ 100°23′14.2″ 1600 dry rice land 14 12:45 38°46′16.2″ 100°23′14.0″ 1600 rape land 15 12:54 38°46′15.6″ 100°23′13.8″ 1600 buckwheat land 16 14:52 38°45′55.5″ 100°23′00.1″ 1610 maize (without intercrop) 17 15:28 38°45′57.5″ 100°22′28.3″ 1630 maize (without intercrop) 18 16:20 38°43′17.3″ 100°22′53.4″ 1730 gobi (Bassia dasyphylla and margarite dominate) 19 17:40 38°42′31.8″ 100°22′56.8″ 1780 gobi (Bassia dasyphylla and Sympegma regelii dominate) 20 10:27 38°36′25.1″ 100°20′33.2″ 2260 wheatgrass dominates 21 11:10 38°36′24.4″ 100°20′38.1″ 2260 abandoned composite land 22 11:30 2260 near site 22, wheatgrass and composite cenosis 23 bare land 24 13:09 38°38′46.3″ 100°23′08.5″ 2030 alfalfa land 25 14:39 38°44′30.8″ 100°22′41.0″ 1660 poplar 26 9:47 38°58′11.4″ 100°26′18.3″ 1460 rice land Observation items included: (1) quadrat surveys (2) LAI by LAI-2000 (3) ground object reflectance spectra by ASD FieldSpec Pro (350-2500nm)from Gansu Meteorological Administration (4) the land surface temperature and the canopy radiative temperature by the hand-held thermal infrared sensor (5) the photosynthesis rate by LI-6400 (6) the radiative temperature by ThermaCAM SC2000 (7) Atmospheric parameters by CE318 to retrieve the total optical depth, aerosol optical depth, Rayleigh scattering coefficient, column water vapor in 936 nm, and various parameters at 550nm to obtain horizontal visibility with the help of MODTRAN or 6S codes (8) chlorophyll consistency by portable SPAD Those provide reliable ground data for developing and validating retrieval meathods of biophysical parameters from EO-1 Hyperion images.
MA Mingguo, LI Xin, SU Peixi, DING Songchuang, GAO Song, YAN Qiaodi, ZHANG Lingmei, WANG Xufeng, Qian Jinbo, BAI Yunjie, HAO Xiaohua, Liu Qiang, Wen Jianguang, XIN Xiaozhou, WANG Xiaoping, HAN Hui
The dataset of ground truth measurement synchronizing with Envisat ASAR was obtained in No. 1, 2 and 3 quadrates of the A'rou foci experimental area on Jul. 5 and Jul. 6, 2008. The Envisat ASAR data were in AP mode and VV/VH polarization combinations, and the overpass time was approximately at 11:14 BJT. The quadrates were divided into 4×4 subsites, with each one spanning a 30×30 m2 plot. Observation items included: (1) the quadrate investigation in No. 2 and 3 quadrates: GPS by GARMIN GPS 76, plant species by manual cognition, the plant number by manual work, the height by the measuring tape repeated 4-5 times, phenology by manual work, the coverage by manual work (compartmentalizing 0.5m×0.5m into 100 to see the percentage the stellera takes) and the chlorophyll content by SPAD 502. (2) spectrum of stellera and pasture by ASD FieldSpec (350～2 500 nm), with 20% reference board. The preprocessed canopy spectrum was archived. (3) BRDF by ASD FieldSpec (350～2 500 nm), with 20% reference board. The processed reflectance and transmittivity were archived as .txt files. (4) photosynthesis of stellera and pasture by LI-6400. The data were archived in Excel format. (5) soil moisture by WET soil moisture tachometer. Acquisition time, soil moisture (%vol), Ecp (ms/m), Tmp Eb and Ecb (ms/m) of 25 corner points were archived. (6) the soil temperature by the handheld infrared thermometer. Acquisition time, the soil temperature measured three times and the land cover types were archived. The data included the canopy reflectance on Jul. 5 and 6, photosynthesis on Jul. 5 and 6, BRDF on Jul. 5, photos on Jul. 5, the infrared land surface temperature and soil moisture by WET on Jul. 5, biomass on Jul. 5 and the surface temperature along No. 3 flight on Jul. 6.
DING Songchuang, GE Yingchun, LI Hongyi, MA Mingguo, Qian Jinbo, WANG Yang, YU Yingjie, LIU Sihan
Vegetation functional type (PFT) is the combination of large plant species according to the ecosystem function of plant species and the way of resource utilization. Each plant functional type shares similar plant properties, which simplifies the diversity of plant species to the diversity of plant function and structure.Vegetation functional types have been used in the dynamic global vegetation model (DGVM) to predict changes in ecosystem structure and function under global change scenarios.The 1km vegetation functional pattern map of heihe basin is based on the 1km land cover map of heihe basin (MICLCover subset of heihe basin), and is divided by using the vegetation functional climate rules proposed by Bonan et al. (2002).The climate data utilize the 0.1 degree atmospheric drive data of he jie and Yang kun, developing China region from 1981 to 2008.This map can be used in the land surface process model of heihe river basin.
RAN Youhua
The sample plot survey data are as follows: in August 2013, 30 forest sample plots were set up in tianlaochi basin, with the sample plot specification of 10 m×20 m, and the long side of the sample plot was parallel to the slope direction, including 26 Qinghai spruce forests, 2 Qilian yuanberlin forests and 2 spruce-cypress mixed forests. within the sample plot, the diameter at breast height (diameter at trunk height of 1.3 m) of each tree was measured by using a ruler. Using hand-held ultrasonic altimeter to measure the tree height and the height under branches (the height of the first living branch at the lower end of the crown) of each tree, measuring the crown width in the north-south direction and the east-west direction by using a tape scale, and positioning the sample plot by using differential GPS. Taking the carbon storage data of the sample plot as the optimal control condition, using Kriging interpolation to obtain the biomass spatial distribution map driving field, using HASM algorithm to simulate the forest biomass spatial distribution map of the waterlogging pool, the simulation results conform to the vegetation distribution law of the study area, and obtain better effects.
YUE Tianxiang, ZHAO Na
The dataset of the discrimination of C3/C4 species was obtained by the handheld GPS and the digital camera in the Linze station foci experimental area on Jul. 10, 2008. Data fields included Gps, Longitude, Latitude, Photo_num and Describe (descriptions on C3/C4 vegetation and photos).
CHENG Zhanhui, Liu Liangyun
The data is the digitization of the Heihe River basin part of the 1:1 million Vegetation Atlas of China, 1:1000, 000 Vegetation Atlas of China is edited by academician Hou Xueyu, a famous vegetation ecologist (Hou Xueyu, 2001). It is jointly compiled by more than 250 experts from 53 units such as research institutes of Chinese Academy of Sciences, relevant ministries and commissions, relevant departments of various provinces and regions, colleges and universities. It is another summative achievement of vegetation ecologists in China over 40 years after the publication of monographs such as vegetation of China Basic map of natural resources and natural conditions of the family. It is based on the rich first-hand information accumulated by vegetation surveys carried out throughout the country over the past half century, and the materials obtained by modern technologies such as aerial remote sensing and satellite images, as well as the latest research achievements in geology, soil science and climatology. It reflects in detail the distribution of vegetation units of 11 vegetation type groups, 796 formations and sub formations of 54 vegetation types, horizontal and vertical zonal distribution laws, and also reflects the actual distribution of more than 2000 dominant species of plants, major crops and cash crops in China, as well as the close relationship between dominant species and soil and ground geology. The atlas is a kind of realistic vegetation map, reflecting the recent quality of vegetation in China.
HOU Xueyu
This dataset is the LAI observation in the artificial oasis experimental region of the middle stream of the Heihe River Basin. The observation period is from 24 May to 20 September 2012 (UTC+8). Measurement instruments: LAI-2000 (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: To measure the incoming sky radiation on the canopy firstly. Then the transmission sky radiation are mearued under the canopy for serveral times. The canopy LAI is retrieved by using the gap probability model.
Li Yun, Wang Yan, MA Mingguo
Lysimeter is the most effective tool for measuring water consumption per plant, which can provide daily, monthly and seasonal changes of transpiration water consumption per plant. In this project, a lysimeter measurement system for Populus euphratica seedlings is established in the lower reaches of Heihe River, with the observation frequency of 0.5h, mainly including water content changes, infiltration, evapotranspiration, etc.
SI Jianhua
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