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
In the ecosystem, soil and vegetation are two interdependent factors. Plants affect soil and soil restricts vegetation. On the one hand, there are a lot of nutrients such as carbon, nitrogen and phosphorus in the soil. On the other hand, the availability of soil nutrients plays a key role in the growth and development of plants, directly affecting the composition and physiological activity of plant communities, and determining the structure, function and productivity level of ecosystems. Soil moisture content (or soil moisture content): In the 9 sections from Daxihaizi to taitema lake in the lower reaches of Tarim River, plant sample plots are set in the direction perpendicular to the river channel according to the arrangement of groundwater level monitoring wells. Dig one soil profile in each sample plot, collect one soil sample from 0-5 cm, 5-15 cm, 15-30 cm, 30-50 cm, 50-80 cm, 80-120 cm and 120-170cm soil layers from bottom to top in each profile layer, each soil sample is formed by multi-point sampling and mixing of corresponding soil layers, each soil layer uses aluminum boxes to collect soil samples, weighs wet weight on site, and measures soil moisture content (or soil moisture content) by drying method. Soil nutrient: the mixed soil sample is used for determining soil nutrient after removing plant root system, gravel and other impurities, air-drying indoors and sieving. Organic matter is heated by potassium dichromate, total nitrogen is treated by semi-micro-Kjeldahl method, total phosphorus is treated by sulfuric acid-perchloric acid-molybdenum antimony anti-colorimetric method, total potassium is treated by hydrofluoric acid-perchloric acid-flame photometer method, effective nitrogen is treated by alkaline hydrolysis diffusion method, effective phosphorus is treated by sodium bicarbonate leaching-molybdenum antimony anti-colorimetric method, effective potassium is treated by ammonium acetate leaching-flame photometer method, PH and conductivity are measured by acidimeter and conductivity meter respectively (water to soil ratio is 5: 1). Soil water-soluble total salt was determined by in-situ salinity meter. Drought stress is the most common form of plant adversity and is also the main factor affecting plant growth and development. Plant organs will undergo membrane lipid peroxidation under adverse circumstances, thus accumulating malondialdehyde (MDA), the final decomposition product of membrane lipid peroxide. MDA content is an important indicator reflecting the strength of membrane lipid peroxidation and the damage degree of plasma membrane, and is also an important parameter reflecting the damage of water stress to plants. At the same time, under adverse conditions, the increased metabolism of reactive oxygen species in plants will lead to the accumulation of reactive oxygen species or other peroxide radicals, thus damaging cell membranes. Superoxide dismutase (SOD) and peroxidase (POD) in plants can remove excess active oxygen in plants under drought and other adversities, maintain the metabolic balance of active oxygen, protect the structure of the membrane, and finally enhance the resistance of plants to adversities. The analysis samples take Populus euphratica, Tamarix chinensis and Phragmites communis as research objects. According to the location of groundwater monitoring wells, six sample plots are set up starting from the riverside, with an interval of 50 m between each sample plot, which are sample plots 1, 2, 3, 4, 5 and 6 in turn. Fresh leaves of plants are collected, stored at low temperature, and pretreated (dried or frozen) on the same day. PROline (Pro), cell membrane system protective enzymes superoxide dismutase (SOD) and peroxidase (POD) were tested indoors. Preparation of enzyme solution: weigh 0.5g of fresh material and add 4.5mL pH7.8 with ph 7.8. The materials were homogenized in a pre-frozen mortar, which was placed in an ice bath. Centrifuge at 10000 r/min for 15 min. The supernatant was used for determination of superoxide dismutase, peroxidase and malondialdehyde (MDA). PRO determination: put 0.03 g of material into a 20 mL large test tube, add 10mL ammonia-free distilled water, seal it, put it in a boiling water bath for 30min, cool it, filter, filtrate 5 mL+ ninhydrin 5 mL, develop color in boiling water for 60min, and extract with toluene. The extract was colorized with Shimadzu UV-265 UV spectrophotometer at 515 nm. SOD activity was measured by NBT photoreduction. The order of sample addition for enzyme reaction system is: pH 7.8 PBS 2.4mL+ riboflavin 0.2 mL+ methionine 0.2 mL+EDTA0.1 mL+ enzyme solution 0.1 mL+NBT0.2 mL. Then the test tube was reacted under 40001ux light for 20 min, and photochemical reduction was carried out. SOD activity was measured at 650 nm wavelength by UV-265 ultraviolet spectrophotometer. POD activity determination: the reaction mixture was 50 ml PBS with pH 6.0+28 μ L guaiacol+19 UL30% H2O2. 2 mL of reaction mixture +1 mL of enzyme solution, immediately start timing, reading every 1 min, reading at 470 nm. Determination of chlorophyll: ethanol acetone mixed solution method. After cutting the leaves, the mixed solution of 0.2 g and acetone: absolute ethanol = 1: 1 was weighed as the extraction solution. After extracting in the dark for 24 h, the leaves turned white and chlorophyll was dissolved in the extraction solution. The OD value of chlorophyll was measured by spectrophotometer at 652nm. Determination method of soluble sugar: phenol sulfate method is adopted. (1) The standard curve is made by taking 11 20 ml graduated test tubes, numbering them from 0 to 10 points, and adding solution and water according to Table 1 respectively. Then add 1 ml of 9% phenol solution to the test tube in sequence, shake it evenly, then add 5 ml of concentrated sulfuric acid from the front of the tube for 5 ~ 20 s, the total volume of the colorimetric solution is 8 ml, and leave it at constant temperature for 30 minutes for color development. Then, with blank as control, colorimetric determination was carried out at 485 nm wavelength. With sugar as abscissa and optical density as ordinate, a standard curve was drawn and the equation of the standard curve was obtained. (2) Extraction of soluble sugar: fresh plant leaves are taken, surface dirt is wiped clean, cut and mixed evenly, 0.1-0.3 g are weighed, 3 portions are respectively put into 3 calibration test tubes, 5-10 ml distilled water is added, plastic film is sealed, extraction is carried out in boiling water for 3O minutes, the extraction solution is filtered into a 25 ml volumetric flask, repeated flushing is carried out, and the volume is fixed to the calibration. (3) Absorb 0.5 g of sample solution into the test tube, add 1.5 ml of distilled water, and work out the content of soluble sugar in the same way as the standard curve. The amount of solution and water in each test tube Pipe number 0 1-2 3-4 5-6 7-8 9-10 1.100μg/L sugar solution 0.20 0.40 0.60 1.0 2. water/ml 2.0 1.8 1.6 1.4 1.2 1.0 3. Soluble sugar content/μ g 0 20 40 60 80 100 Determination of malondialdehyde: thiobarbituric acid method. Fresh leaves were cut to pieces, 0．5 g was weighed, 5% TCA5 ml was added, and the homogenate obtained after grinding was centrifuged at 3 000 r／rain for 10 rain. Take 2 ml supernatant, add 0.67% TBA 2 ml, mix, boil in 100 water bath for 30 rain, cool and centrifuge again. Using 0.67% TBA solution as blank, the OD values at 450, 532 and 600 nm were determined. Methods for analysis and testing of plant hormones (GA3, ABA, CK, IAA): 0.1 0.005 g plant samples were taken and ground in liquid nitrogen. 500μl methanol was extracted overnight at 4℃. Centrifuge the sample and freeze-dry the supernatant. 30μl10％% CH3CN dissolved the sample. 10μl of sample solution was analyzed by HPLC. The external standard method was used to quantify plant hormones. Standard plant hormones were purchased from sigma Company. See (Ruan Xiao, Wang Qiang, et al., 2000, Journal of Plant Physiology.26 (5), 402-406) for analysis methods.
CHEN Yaning, HAO Xingming
The dataset of ground truth measurements synchronizing with airborne Polarimetric L-band Multibeam Radiometer (PLMR) mission was obtained in upper reaches of the Heihe River Basin on 1 August, 2012. PLMR is a dual-polarization (H/V) airborne microwave radiometer with a frequency of 1.413 GHz, which can provide multi-angular observations with 6 beams at ±7º, ±21.5º and ±38.5º. The PLMR spatial resolution (beam spot size) is approximately 0.3 times the altitude, and the swath width is about twice the altitude. The measurements were conducted along two transects respectively located at the west and east branches of the Babaohe River and two sampling plots in the A’rou foci experimental area. Along the transects, soil moisture was sampled at every 50 m in the west-east direction. In order to keep the ground measurements following the airborne mission as synchronous as possible in temporal, measurements were made discontinuously. In the A’rou foci experimental area, two sampling plots were identified with areas of 1.5 km × 0.6 km and 0.85 km × 0.6 km. In each plot, soil moisture was sampled at every 50 m in the west-east direction and 100 m in the north-south direction. Steven Hydro probes were used to collect soil moisture and other measurements. Concurrently with soil moisture sampling, vegetation properties were measured at some typical sampling plots. Observation items included: Soil parameters: volumetric soil moisture (inherently converted from measured soil dielectric constant), soil temperature, soil dielectric constant, soil electric conductivity. Vegetation parameters: biomass, vegetation water content, canopy height. Data and data format: This dataset includes two parts of measurements, i.e. soil and vegetation parameters. The former is as shapefile, with measured items stored in its attribute table. The measured vegetation parameters are recorded in an Excel file.
LI Xin, MA Mingguo, WANG Shuguo
Photosynthesis of Populus euphratica is mainly affected by atmospheric CO2 concentration, intercellular CO2 concentration, photosynthetic active radiation and leaf temperature when groundwater level is deep and shallow, but with the decrease of groundwater level, atmospheric CO2 concentration and photosynthetic active radiation become the main factors limiting photosynthesis of Populus euphratica. This is because when the groundwater depth is low, the groundwater supply is sufficient, and the leaves are not limited by the water supply. When the photosynthetic effective radiation is strong, the air temperature and leaf temperature are relatively high, and the relative humidity of the air is small. At this time, the photosynthesis and transpiration are both strong. Stomata mainly adapt to strong transpiration by increasing stomatal conductance, i.e. reducing stomatal resistance. At the same time, CO2 in the air continuously enters cells through open stomata, and becomes the raw material for photosynthesis together with intercellular CO2, thus causing the decrease of CO2 concentration in the air and intercellular space, which is the CO2 supply limitation that often causes photosynthesis inhibition in photosynthesis. However, when subjected to water stress, the supply of CO2 is no longer the main reason for limiting photosynthesis. When the photosynthetic effective radiation increases, the net photosynthetic rate, transpiration rate and stomatal conductance all increase. When the supply of CO2 concentration is relatively sufficient, photosynthesis will be slowed down due to the shortage of water, another necessary raw material for photosynthesis. Water use efficiency and water productivity of plants are of great practical significance for measuring and screening species in arid regions. The flow rate was 400μmol/ s and the leaf temperature was kept at 26°C using the L I-6400 portable photosynthesis analyzer, the CO2 concentration in the reference chamber was kept at 360μmol/ mol or 720μmol/ mol using the CO2 injection system, and the photosynthetically active radiation (PAR) was set at 2000,1500,1200,1000,500,300,50,0 μ mol/(m2) using the 6400-02B L ED light source. s) 。 Twelve healthy and mature leaves were selected from the east, south, west and north of each Populus euphratica to the middle and upper parts respectively, from 8 :00 to 20 :00, and photosynthetic apparatus Li 6400 (Li 6400, LiCOR, Lincoln, NE, USA) respectively measured the net photosynthetic rate (Pn), transpiration rate (Tr), stomatal conductance (gs) and other gas exchange parameters of each leaf, simultaneously measured the atmospheric CO2 concentration (Ca), intercellular CO2 concentration (Ci), photosynthetic effective radiation (Pa r), atmospheric temperature (T a), leaf surface temperature (Tl), air relative humidity (RH) and other parameters, and repeated readings for each leaf 3 times. Water use efficiency (WUE) = Pn/ Tr, stomatal limitation (Ls )= 1-Ci/Ca.
CHEN Yaning, HAO Xingming
The experimental project of vegetation degradation mechanism and reconstruction in Yuanjiang dry-hot valley in Yunnan belongs to the major research program of "Environmental and Ecological Science in Western China" of the National Natural Science Foundation. The principal is researcher Cao Kunfang of Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences. The project runs from January 2004 to December 2007. Data collected for this project include: 1. Excel table of multi-year average temperature and rainfall in Yuanjiang dry-hot valley (1961-2004), with attribute fields including monthly average temperature and monthly average rainfall. 2. excel table of annual average temperature (1750-2006) in the middle of Hengduan Mountain in China based on tree ring, with attribute fields including year and reconstructed average temperature. 3. excel table of summer temperatures (1750-2006) in the central Hengduan Mountains in southern China based on tree rings. The attribute fields include the year and the reconstructed average temperature in summer (April-September). 4. excel table of drought index (1655-2005) in central Hengduan Mountains of China based on tree rotation, with attribute fields including year and reconstruction of drought index in spring (March-May). 5. pdf file of growth dynamic graph of leaves and branches. it records the growth dynamic trend line and leaf dynamic trend graph of plants with s-type, f-type, intermediate-type and S+SD-type branches from March 22, 2004 to April 8, 2005. 6.32 Phenological Summary Tables of Woody Plants (word Document: Specific Name, Number of Observed Plants/Branches, Type of Branch Extension, Leaf Phenology, Length of Current Year Branches (cm), Total Leaves on Branches, Leaf Area (cm2), Non-leaf Period (Months), Flowering Period, Fruit Ripening Period and Fruit Type) 7. Seasonal Changes of Relative Water Content of Plant Leaves in Yuanjiang Dry-hot Valley (March 2003-February 2004) Excel Table 8. Seasonal Changes of Photosynthesis of 6 Representative Plants in Yuanjiang Dry-hot Valley (Maximum Photosynthetic Rate, Stomatal Conductance, Water Use Efficiency, Maximum Subefficiency of photosystem II) excle Table (2003-2005) 9. excle Table of Long-term Water Use Efficiency (Isotope) Data of Representative Plants in Yuanjiang Dry-hot Valley (Water Use Efficiency in Dry and Wet Seasons of Shrimp Flower, Red-skin Water Brocade Tree, Three-leaf Lacquer, Phyllanthus emblica, Pearl Tree, Dried Sky Fruit, Cyclobalanopsis glauca, West China Small Stone Accumulation, Geranium, Tiger thorn, Willow and Pigexcrement Bean) 10. word Document of List of Plants in Mandan Qianshan, Yuanjiang
CAO Kunfang
The data set mainly includes observation data of each tree in the super site, and the observation time is from June 2, 2008 to June 10, 2008. The super site is set around the Dayekou Guantan Forest Station. Since the size of the super site is 100m×100m, in order to facilitate the forest structure parameter survey, the super site is divided into 16 sub-sample sites, and tally forest measurement is performed in units of sub-samples. The tally forest measurement factors include: diameter, tree height, height under branch, crown width in transversal slope direction, crown width in up and down slope direction, and tindividual tree growth status. The measuring instruments are mainly: tape, diameter scale, laser altimeter, ultrasonic altimeter, range pole and compass. The data set also records the center point latitude and longitude coordinates of 16 sub-samples (measured by Z-MAX DGPS). The data set can be used for verification of remote sensing forest structure parameter extraction algorithm. The data set, together with other observation data of the super site, can be used for reconstruction of forest 3D scenes, establishment of active and passive remote sensing mechanism models, and simulation of remote sensing images,etc.
CHEN Erxue, BAI Lina, WANG Bengyu, TIAN Xin, LIU Qingwang, CAO Bin, Yang Yongtian, Zhihai Gao, Bingxiang Tan, GUO Zhifeng, WANG Xinyun, FU Anmin, ZHANG Zhiyu, NI Wenjian, WANG Qiang, BAO Yunfei, WANG Dianzhong, ZHANG Yang, ZHAO Liqiong, LIANG Dashuang, WANG Shunli, ZHAO Ming, LEI Jun, NIU Yun, LUO Longfa
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
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.
WANG Shunli, LUO Longfa, WANG Rongxin, CHE Zongxi, JING Wenmao
I. Overview The long-term sequence China Vegetation Index dataset is mainly for the normalized vegetation index (NDVI), based on four bands synthesized every 10 days from 1 April 1998 to 31 December 2011 with a spatial resolution of 1 km. Spectral reflectance and 10-day maximized NDVI dataset. Ⅱ. Data processing description The VEGETATION sensor was launched by SPOT-4 in March 1998, and has received SP0T VGT data for global vegetation coverage observation since April 1998. It has a very complete and efficient image ground processing mechanism system. The VEGETATION data is mainly received by the Kiruna ground station in Sweden. The image quality monitoring center in Toulouse, France is responsible for image quality and provides related parameters (such as calibration coefficients). Finally, the image processing and archiving center of VITO Institute in Belgium Global VEGETATION data archiving and user orders. Among them, VGT-P (prototype) data products mainly provide scientific researchers with high-quality physical quantity prototype data in order to facilitate their research and development of algorithms and application models. The data undergoes strict systematic error correction and resampling into a longitude and latitude network projection, the pixel resolution is lkm, and the pixel brightness value is the reflectivity of the ground features on the top layer of the atmosphere. In addition to providing four bands of raw data, relevant auxiliary parameters such as atmospheric conditions, system information (solar zenith angle, azimuth, field of view, and reception time) and terrain data are also provided according to user needs. VGT-S (synthesis) products provide atmospheric-corrected surface reflectance data, and use multi-band synthesis techniques to obtain a normalized vegetation index (w) data set with lkm resolution. VGI-S products include the spectral reflectance and NDVI data set (s1) of four bands synthesized daily, the spectral reflectance of four bands synthesized every 10 days, and the maximum NDVI data set (S10) every 10 days to reduce cloud and The impact of BRDF, while S10 was also resampled into 4km resolution (S10.4) and 8km resolution (S10.8) datasets. VGT-S products are widely used for their high time resolution. This data set contains the spectral reflectance of four bands synthesized every 10 days and the 10-day maximized NDVI data set (S10). The pre-processing of SPOT source data includes atmospheric correction, radiation correction, and geometric correction. NDVI data with a maximum of 10 days of synthesis is generated, and the values of -1 to -0.1 are set to -0.1, and then formula YDN = (JNDVI +0.1) /0.004 Convert to a YDN value from 0 to 250. Ⅲ. Data content description The long-term sequence China Vegetation Index dataset is mainly for the normalized vegetation index (NDVI), based on four bands synthesized every 10 days from 1 April 1998 to 31 December 2011 with a spatial resolution of 1 km. Spectral reflectance and 10-day maximized NDVI dataset. The SPOT-VEGETATION-NDVI data set contains .zip compressed files with time resolution from April 1, 1998 to December 31, 2011. After decompression, it is an ESRI-GRID file with a scene every 10 days. The SPO-VEGETATION-NDVI data set naming rules are: v-yymmdd, where v is the abbreviation of vegetation, yymmdd represents the date of the file, and is the main identifier that distinguishes other files. Ⅳ. Data usage description An important feature of the Vegetation Index product is that it can be converted into leaf crown biophysical parameters. Vegetation index (VI) also plays an "intermediate variable" in the acquisition of vegetation biophysical parameters (such as foliar index LAI, green shade, fAPAR, etc.). The relationship between vegetation indices and vegetation biophysical parameters is currently being studied using globally representative ground, aircraft and satellite observation datasets. These data can be used to evaluate the performance of the VI algorithm before satellite launch, and also provide the conversion coefficient between the vegetation index product and the biophysical characteristics of the leaf crown. The use of biophysical data is part of the Vegetation Index Verification Program. Vegetation index products will play a major role in several Earth Observation System (EOS) studies and are also part of global and regional biosphere model products in recent years.
XUE Xian, DU Heqiang
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)
GAO Qiong
The forest hydrology experimental area of Heihe River integrated remote sensing experiment includes the dense observation area of Dayekou basin and the dense observation area of Pailugou basin. Due to the concentrated distribution of the fixed sample plots in the drainage ditch basin, these sample plots lack of representativeness to the forest of the whole dayokou basin, so in June 2008, 43 temporary forest sample plots were set up in the whole dayokou basin. The data set is the ground observation data of the 43 temporary plots. In addition to the measurement and recording of stand status and site factors, Lai was also observed. The instruments used to measure each wood in the sample plot are mainly tape, DBH, flower pole, tree measuring instrument and compass. The DBH, tree height, height under branch, crown width in cross slope direction, crown width along slope direction and single tree growth were measured for each tree. WGS84 latitude and longitude coordinates of the center point of the sample plot were measured with different hand-held GPS, and the positioning error was about 5-30m. Other observation factors include: Forest Farm, slope direction, slope position, slope, soil thickness, canopy density, etc. The implementation time of these temporary sample plots is from 2 to 30 June 2008. The data set can provide ground data for the development of remote sensing inversion algorithm of forest structure parameters.
LING Feilong, HE Qisheng, ZHANG Xuelong, WANG Shunli, ZHAO Ming, LEI Jun, NIU Yun, LUO Longfa, CHEN Erxue
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
This dataset: Editor-in-Chief: Hou Xueyu Drawing: Hou Xueyu, Sun Shizhou, Zhang Jingwei, He Miaoguang. Wang Yifeng, Kong Dezhen, Wang Shaoqing Publishing: Map Press Issue: Xinhua Bookstore Year: 1979 Scale: 1: 4,000,000 It took five years to complete from May 1972 to July 1976. In the process of drawing legends and mapping, referring to the vast majority of vegetation survey data (including maps and texts) after 1949 in China, we held more than a dozen mapping seminars involving researchers from inside and outside the institute. During the layout after the mapping work was completed, many new survey data were added, especially vegetation data in western Tibet. The nature of this map basically belongs to the current vegetation map, including two parts of natural vegetation and agricultural vegetation. The legend of natural vegetation is arranged according to the seven vegetation groups. They are mainly divided according to the appearance of plant communities and certain ecological characteristics. The concept of agricultural vegetation community, like the natural vegetation community, also has a certain life form (appearance, structure, layer), species composition and a certain ecological location. In 1990, the State Key Laboratory of Resources and Environmental Information Systems of the Institute of Geographical Sciences and Resources, Chinese Academy of Sciences completed the digitization of this map, and wrote relevant data description documents. The digitized data also adopt equal product cone projection and can be converted into other projections by GIS software. This data includes a vector file in e00 format, a Chinese vegetation coding design description, a dataset description, a vegetation data layer attribute data table, and a scanned "People's Republic of China Vegetation Map-Brief Description" and other files. Data projection: Projection: Albers false_easting: 0.000000 false_northing: 0.000000 central_meridian: 110.000000 standard_parallel_1: 25.000000 standard_parallel_2: 47.000000 latitude_of_origin: 0.000000 Linear Unit: Meter (1.000000) Geographic Coordinate System: Unknown Angular Unit: Degree (0.017453292519943299) Prime Meridian: Greenwich (0.000000000000000000) Datum: D_Unknown Spheroid: Clarke_1866 Semimajor Axis: 6378206.400000000400000000 Semiminor Axis: 6356583.799999999800000000 Inverse Flattening: 294.978698213901000000
HOU Xueyu, SUN Shizhou, ZHANG Jingwei, HE Miaoguang, WANG Yifeng, KONG Dezhen, WANG Shaoqing
The project of material and energy exchange and community stability of soil-plant gas interface in oasis-gobi transition zone belongs to the major research program of "environmental and ecological science in western China" sponsored by the national natural science foundation, and is headed by professor Wang genxuan of Lanzhou university. the running time of the project is from January 2002 to December 2004. Data collected for this project: 1. Status of energy utilization rate of desert natural vegetation The data is in Excel format. The individual size of plants and biomass of green photosynthetic tissue measured by randomly selecting some plants from the desert natural vegetation sample are mainly used to explore the energy utilization rate model of desert plants in this project, including variables such as average total biomass, average biomass of photosynthetic tissue and population density. 2. Survey data on basic information of natural vegetation community institutions in sample plots The data is in Excel format, including survey and analysis data of vegetation density and average underground biomass in Lanzhou, Baiyin and Jingtai.
WANG Genxuan
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
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