Soil moisture is an important boundary condition of earth-atmosphere exchanges, and it has been defined as an essential climate variable by GCOS. Vegetation optical depth is a physical variable to measure the attenuation of vegetation in microwave radiative transfer model, and it has been proved to be a good indicator of vegetation water content and biomass. This dataset uses the multi-channel collaborative algorithm (MCCA) to retrieve both soil moisture and polarized vegetation optical depth with SMAP brightness temperature. The algorithm uses a self-constraint relationship between land parameters and an analytical relationship between brightness temperature at different channels to perform the retrieval process. The MCCA does not depend on other auxiliary data on vegetation properties and can be applied to a variety of satellites. The soil moisture product from this dataset includes the soil moisture content in the unfrozen period and the liquid water content in the frozen period. Both horizontal- and vertical-polarization vegetation optical depth are retrieved. So far as we know, it is the first polarization-dependent vegetation optical depth product at L-band. This dataset was validated by 19 dense soil moisture observation networks (9 core validation sites used by SMAP team and 13 sites not used by them), and the widely used soil climate analysis network (SCAN). It was found that ubRMSE (unbiased root mean square error) of MCCA retrieved soil moisture is generally smaller than that of other SMAP products.
ZHAO Tianjie, PENG Zhiqing , YAO Panpan, SHI Jiancheng
This data set is hyperspectral observation data of typical vegetation along Sichuan Tibet Railway in September 2019, using the airborne spectrometer of Dajiang M600 resonon imaging system. Including the hyperspectral data observed in the grassland area of Lhasa in 2019, with its own latitude and longitude. The hyperspectral survey was mainly sunny. Before flight, whiteboard calibration was carried out; when data were collected, there was a target (that is, the standard reflective cloth suitable for the grass), which was used for spectral calibration; there were ground mark points (that is, letters with foam plates), and the longitude and latitude coordinates of each mark were recorded for geometric precise calibration. The DN value recorded by Hyperspectral camera of UAV can be converted into reflectivity by using Spectron Pro software. Hyperspectral data is used to extract spectral characteristics of different vegetation types, vegetation classification, inversion of vegetation coverage and so on.
ZHOU Guangsheng, JI Yuhe, LV Xiaomin, SONG Xingyang
The vegetation type map was created by the random forest (RF) classification approach, based on 319 ground-truth samples, combined with a set of input variables derived from the visible, infrared, and thermal Landsat-8 images. According to vegetation characteristics, four types include alpine swamp meadow (ASM), alpine meadow (AM), alpine steppe (AS), and alpine desert (AD) were classified in this map. Based on a spatial resolution of 30 m, the map can provide more detailed vegetation information.
ZHOU Defu, ZOU Defu, ZOU Defu, Zhao Lin, ZHAO Lin, Liu Guangyue, LIU Guangyue, Du Erji, DU Erji, LI Zhibin , LI Zhibin, Wu Tonghua, WU Xiaodong, CHEN Jie CHEN Jie
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
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
The data set includes the estimated data on the SOS (start of season) and the EOS (end of season) of vegetation in Sanjiangyuan based on GIMMS3g version 1.0, the latest version of the GIMMS NDVI data set. Two common phenological estimation methods were adopted: the threshold extraction method based on polynomial fitting (the term “poly” was included in the file names) and the inflection point extraction method based on double logistic function fitting (the term “sig” was included in the file names). These data can be used to analyse the relationship between vegetation phenology and climate change. The temporal coverage ranges from 1982 to 2015, and the spatial resolution is 8 km.
WANG Xufeng
The dataset of ground truth measurement synchronizing with EO-1 Hyperion was obtained in the Yingke oasis and Huazhaizi desert steppe foci experimental areas on May 25, 2008. Observation items included: (1) Atmospheric parameters on the ICBC resort office roof by CE318 (produced by CIMEL in France). The total optical depth, aerosol optical depth, Rayleigh scattering coefficient, column water vapor in 936 nm, particle size spectrum and phase function were then retrieved from these observations. The optical depth in 1020nm, 936nm, 870nm, 670nm and 440nm were all acquired by CE318. Those data include the raw data in k7 format and can be opened by ASTPWin. ReadMe.txt is attached for detail. Processed data (after retrieval of the raw data) in Excel format are on optical depth, rayleigh scattering, aerosol optical depth, the horizontal visibility, the near surface air temperature, the solar azimuth, zenith, solar distance correlation factors, and air column mass number. (2) Ground object reflectance spectra f new-born rape and the bare land in Biandukou foci experimental area by ASD FieldSpec (350~2500 nm) from BNU. Raw data were binary files direct from ASD (by ViewSpecPro), and pre-processed data on reflectance were in Excel format. (3) Soil moisture (0-40cm) by the cutting ring and the soil temperature (0-40cm) by the thermocouple in Huazhaizi desert No. 1 plot and the windbreak forest; and soil moisture and the soil temperature (0-100cm) in Yingke oasis maize field. Data were archived in Excel format. (4) LAI. The maximum leaf length and width of each alfalfa and barley were measured. Data were archived in Excel format. (5) Coverage of maize and wheat in Yingke oasis maize field, of vegetation (Reaumuria soongorica) in Huazhaizi desert No. 1 and 2 plots by the self-made coverage instrument and the camera (2.5m-3.5m above the ground). Based on the length of the measuring tape and the bamboo pole, the size of the photo can be decided GPS date were also collected and the technology LAB was applied to retrieve the coverage of the green vegetation. Besides, such related information as surroundings environment was also recorded. Data included the primarily measured image and final fraction of vegetation coverage.
CHEN Ling, QIAN Yonggang, REN Huazhong, WANG Haoxing, YAN Guangkuo, GE Yingchun, SHU Lele, WANG Jianhua, XU Zhen, GUANG Jie, LI Li, XIN Xiaozhou, ZHANG Yang, ZHOU Chunyan, TAO Xin, YAN Binyan, YAO Yanjuan
The dataset of ground truth measurement synchronizing with Landsat TM was obtained in the Yingke oasis and Huazhaizi desert steppe foci experimental areas on May 20, 2008. Observation items included: (1) LAI in Yingke oasis maize field. The maximum leaf length and width of each alfalfa and barley were measured. Data were archived in Excel format. (2) Reflectance spectra in Yingke oasis maize field by ASD FieldSpec (350-2500nm, the vertical canopy observation and the transect observation) from Institute of Remote Sensing Applications (CAS), and in Huazhaizi desert No. 2 plot by ASD FieldSpec (350-1603nm, the vertical observation and the transect observation for reaumuria soongorica and the bare land) from Beijing Academy of Agriculture and Forestry Sciences. The grey board and the black and white cloth were also used for calibration spectrum. Raw data were binary files direct from ASD (by ViewSpecPro), and pre-processed data on reflectance were in Excel format. (3) the radiative temperature by 3 handheld radiometers in Yingke oasis maize field (Institute of Remote Sensing Applications, BNU and Institute of Geographic Sciences and Natural Resources respectively, the vertical canopy observation and the transect observation), and by 3 handheld infrared thermometers in Huazhaizi desert No. 2 plot (the vertical vegetation and bare land observation). The data included raw data (in Word format), recorded data and the blackbody calibrated data (in Excel format). (4) the radiative temperature of maize, wheat and the bare land of Yingke oasis maize field by ThermaCAM SC2000 (1.2m above the ground, FOV = 24°×18°). The data included raw data (read by ThermaCAM Researcher 2001), recorded data and the blackbody calibrated data (archived in Excel format). (5) Photosynthesis of maize, wheat and the bare land of Yingke oasis maize field by LI6400, carried out according to WATER specifications. Raw data were archived in the user-defined format (by notepat.exe) and processed data were in Excel format. (6) Maize albedo by the shortwave radiometer in Yingke oasis maize field. R =10H (R for FOV radius; H for the probe height). Data were archived in Excel format. (7) Atmospheric parameters in Huazhaizi desert No. 2 plot by CE318 (produced by CIMEL in France). The total optical depth, aerosol optical depth, Rayleigh scattering coefficient, column water vapor in 936 nm, particle size spectrum and phase function were then retrieved from these observations. The optical depth in 1020nm, 936nm, 870nm, 670nm and 440nm were all acquired by CE318. Those data include the raw data in k7 format and can be opened by ASTPWin. ReadMe.txt is attached for detail. Processed data (after retrieval of the raw data) in Excel format are on optical depth, rayleigh scattering, aerosol optical depth, the horizontal visibility, the near surface air temperature, the solar azimuth, zenith, solar distance correlation factors, and air column mass number. (8) Coverage fraction of Reaumuria soongorica by the self-made coverage instrument and the camera (2.5m-3.5m above the ground) in Huazhaizi desert No. 2 plot. Based on the length of the measuring tape and the bamboo pole, the size of the photo can be decided. GPS data was used for the location and the technology LAB was used to retieve the coverage fractionof the green vegetation. Besides, such related information as the surrounding environment was also recorded. Data included the vegetation iamge and coverage (by .exe). (9) The radiative temperature of Reaumuria soongorica canopy and the bare land by 2 fixed automatic thermometers (FOV: 10°; emissivity: 0.95) in Huazhaizi desert No. 2 plot, observing straight downwards at intervals of 1s. Raw data, blackbody calibrated data and processed data were all archived in Excel format.
CHAI Yuan, CHEN Ling, KANG Guoting, LI Jing, QIAN Yonggang, REN Huazhong, WANG Haoxing, WANG Jindi, XIAO Zhiqiang, YAN Guangkuo, SHU Lele, GUANG Jie, LI Li, Liu Qiang, LIU Sihan, XIN Xiaozhou, ZHANG Hao, ZHOU Chunyan, TAO Xin, YAN Binyan, YAO Yanjuan, TIAN Jing, LI Xiaoyu
The dataset of ground truth measurement synchronizing with the airborne WiDAS mission was obtained in the Yingke oasis and Huazhaizi desert steppe foci experimental areas on Jun. 29, 2008. WiDAS, composed of four CCD cameras, one mid-infrared thermal imager (AGEMA 550), and one infrared thermal imager (S60), can acquire VNIR, MIR and TIR band data. The simultaneous ground data included: (1) Atmospheric parameters in Huazhaizi desert No. 2 plot from CE318 (produced by CIMEL in France). The total optical depth, aerosol optical depth, Rayleigh scattering coefficient, column water vapor in 936 nm, particle size spectrum and phase function were then retrieved from these observations. The optical depth in 1020nm, 936nm, 870nm, 670nm and 440nm were all acquired by CE318. Those data include the raw data in .k7 format and can be opened by ASTPWin. ReadMe.txt is attached for detail. Processed data in Excel format are on optical depth, rayleigh scattering, aerosol optical depth, the horizontal visibility, the near surface air temperature, the solar azimuth, zenith, solar distance correlation factors, and air column mass number. (2) Emissivity of maize and wheat in the Yingke oasis by portable 102F (2.0~25.0um) from BNU. Warm blackbody, cold blackbody, the target and the au-plating board of known emissivity. Raw data of those four measurements were archived in *.WBX, *.CBX, *.SAX and *.CBX Besides, the spectral radiance and emissivity calculated by 102F were archived in *.RAX and *.EMX, respectively. Meanwhile, the final spectral emissivity of targets were also calculated by TES (ISSTES). (3) LAI of mazie and wheat in Yingke oasis maize field. The maximum leaf length and width of leaves were measured. Data were archived as Excel files of Jul. 2. (4) FPAR (Fraction of Photosynthetically Active Radiation) of maize and wheat by SUNSACN and the digital camera in Yingke oasis maize field. FPAR= (canopyPAR－surface transmissionPAR－canopy reflection PAR+surface reflectionPAR) /canopy PAR; APAR=FPAR* canopy PAR. Data were archived in MS Office Word format. (5) the radiative temperature by the automatic thermometer (FOV: 10°; emissivity: 0.95), measured at nadir with time intervals of one second in Yingke oasis maize field (one from BNU and the other from Institute of Remote Sensing Applications), Huazhaizi desert maize field (only one from BNU for continuous radiative temperature of the maize canopy) and Huazhaizi desert No. 2 plot (two for reaumuria soongorica canopy and the background bare soil). Raw data, blackbody calibrated data and processed data were all archived as Excel files. (6) the component temperature in Yingke oasis maize field (by the handheld radiometer and the thermal image from BNU), Yingke oasis wheat field and Huazhaizi desert maize field. For maize, the component temperature included the vertical canopy temperature, the bare land temperature and the plastic film temperature; for the wheat, it included the vertical canopy temperature, the half height temperature, the lower part temperature and the bare land temperature. The data included raw data (in MS Office Word format), recorded data and the blackbody calibrated data (in Excel format). (7) Maize albedo by the shortwave radiometer in Yingke oasis maize field. R =10H (R for FOV radius; H for the observation height). Data were archived in MS Office Excel format. (8) the radiative temperature by the handheld radiometer in Yingke oasis maize field and Huazhaizi desert maize field (the vertical canopy observation and the transect observation for both fields), and Huazhaizi desert No. 2 plot (the NE-SW diagonal observation). The data included raw data (in .doc format), recorded data and the blackbody calibrated data (in Excel format). (9) ground object reflectance spectra in Yingke oasis maize field by ASD FieldSpec (350～2 500 nm) from BNU. The vertical canopy observation and the line-transect observation were used. The data included raw data (from ASD, read by ViewSpecPro), recorded data and processed data on reflectance (in Excel format).
CHEN Ling, GUO Xinping, REN Huazhong, WANG Tianxing, XIAO Yueting, YAN Guangkuo, CHE Tao, GE Yingchun, GAO Shuai, LI Hua, LI Li, LIU Sihan, SU Gaoli, WU Mingquan, XIN Xiaozhou, ZHOU Chunyan, ZHOU Mengwei, FAN Wenjie, SHEN Xinyi, YU Fan, YANG Guijun, Liu Liangyun
The data set contains NPP products data produced by the maximum synthesis method of the three source regions of the Yellow River, the Yangtze River and the Lancang River. The data of remote sensing products MOD13Q1, MOD17A2, and MOD17A2H are available on the NASA website (http://modis.gsfc.nasa.gov/). The MOD13Q1 product is a 16-d synthetic product with a resolution of 250 m. The MOD17A2 and MOD17A2H product data are 8-d synthetic products, the resolution of MOD17A2 is 1 000 m, and the resolution of MOD17A2H is 500 m. The final synthetic NPP product of MODIS has a resolution of 1 km. The downloaded MOD13Q1, MOD17A2, and MOD17A2H remote sensing data products are in HDF format. The data have been processed by atmospheric correction, radiation correction, geometric correction, and cloud removal. 1) MRT projection conversion. Convert the format and projection of the downloaded data product, convert the HDF format to TIFF format, convert the projection to the UTM projection, and output NDVI with a resolution of 250 m, EVI with a resolution 250 m, and PSNnet with resolutions of 1 000 m and 500 m. 2) MVC maximum synthesis. Synthesize NDVI, EVI, and PSNnet synchronized with the ground measured data by the maximum value to obtain values corresponding to the measured data. The maximum synthesis method can effectively reduce the effects of clouds, the atmosphere, and solar elevation angles. 3) NPP annual value generated from the NASA-CASA model.
Kamel Didan*, Armando Barreto Munoz, Ramon Solano, Alfredo Huete
The dataset of LAI measurements was obtained in the Linze station foci experimental area. (1) LAI of maize, desert scrub and the poplar measured by the fisheye camera (CANON EOS40D with a lens of EF15/28), shooting straight downwards, with exceptions of higher plants, which were shot upwards in Wulidun farmland quadrates (Jun. 3, 4 and 29, May 28 and 30 and Jul. 11), inside Linze station quadrates (Jun. 19, 25 and 30, Jul. 3 and 10, May 27), the desert transit zone (May 28 and 30) and the poplar forest (May 30). Sample points were archived in coordiantes.xls. Data included original photos (.JPG) and those processed by can_eye5.0 (in excel). For more details, see Readme file. (2) LAI measured by the ruler and the set square in Wulidun farmland quadrate inside Linze station on May 22, 23, 24, 28 and 30 and Jul. 11, 2008. Part of the samples were also measured by LI-3100 and compared with those by manual work for further correction. Data were archived as Excel files. (3) LAI and SD of maize measured by LAI2000 in Wulidun farmland quadrates (Jun. 24 and 29 and Jul. 10) and inside Linze station quadrates (Jun. 19, 25 and 30, Jul. 3, 9 and 10). Data educed from LAI2000 periodically were archived as text files (.txt) and marked with one ID. Raw data (table of word and txt) and processed data (Excel) were included. Besides, observation time, the observation method and the repetition were all archived. 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.
DONG Jian, LI Jing, Li Xiangyun, Qu Yonghua, SONG Danxia, SUN Qingsong, XIAO Yueting, XIAO Zhiqiang, YU Yingjie, ZHOU Hongmin, JIANG Hao, LI Shihua,
The dataset of ground truth measurement synchronizing with PROBA CHRIS was obtained in the Yingke oasis and Huazhaizi desert steppe foci experimental areas on Jun. 22, 2008. Observation items included: (1) Albedo by the shortwave radiometer in Huazhaizi desert No. 2 plot. R =10H (R for FOV radius; H for the probe height). Data were archived in Excel format. (2) BRDF of maize in Yingke oasis maize field by ASD (350-2 500 nm) from Beijing University and the observation platform of BNU make. The maximum height of the platform was 5m above the ground with the azimuth 0~360° and the zenith angle -60°~60°; BRDF in Huazhaizi desert No. 2 plot by ASD from Institute of Remote Sensing Applications (CAS) and the observation platform of its own make, whose maximum height was 2m above the ground with the zenith angle -70°~70°. Raw data were binary files direct from ASD (by ViewSpecPro), and pre-processed data on reflectance were in Excel format. (3) Atmospheric parameters in Huazhaizi desert No. 2 plot by CE318 (produced by CIMEL in France). The total optical depth, aerosol optical depth, Rayleigh scattering coefficient, column water vapor in 936 nm, particle size spectrum and phase function were then retrieved from these observations. The optical depth in 1020nm, 936nm, 870nm, 670nm and 440nm were all acquired by CE318. Those data include the raw data in .k7 format and can be opened by ASTPWin. ReadMe.txt is attached for detail. Processed data (after retrieval of the raw data) in Excel format are on optical depth, rayleigh scattering, aerosol optical depth, the horizontal visibility, the near surface air temperature, the solar azimuth, zenith, solar distance correlation factors, and air column mass number.
CHEN Ling, GUO Xinping, REN Huazhong, ZOU Jie, LIU Sihan, ZHOU Chunyan, FAN Wenjie, TAO Xin
The NDVI data set is the latest release of the long sequence (1981-2015) normalized difference vegetation index product of NOAA Global Inventory Monitoring and Modeling System (GIMMS), version number 3g.v1. The temporal resolution of the product is twice a month, while the spatial resolution is 1/12 of a degree. The temporal coverage is from July 1981 to December 2015. This product is a shared data product and can be downloaded directly from ecocast.arc.nasa.gov. For details, please refer to https://nex.nasa.gov/nex/projects/1349/.
The National Center for Atmospheric Research
The dataset of ground truth measurements synchronizing with ASTER was obtained in the Linze station foci experimental area on May 28, 2008. Observation items included: (1) soil moisture (0-5cm) measured once by the cutting ring method at the corner points of the 40 subplots of the west-east desert transit zone strip once by cutting ring method in the corner points of nine subplots of the north-south desert transit zone, once by the cutting ring method and once by ML2X Soil Moisture Tachometer in the center points of nine subplots of the farmland. The preprocessed soil volumetric moisture data were archived as Excel files. (2) surface radiative temperature measured by the handheld infrared thermometer (5# and 6# from Cold and Arid Regions Environmental and Engineering Research Institute which were both calibrated) in 40 subplots of the west-east desert transit zone strip (repeated 14-30 times), and nine subplots of the north-south desert transit zone strip (repeated 12-30 times). Data were archived as Excel files. (3) BRDF of maize and desert scrub measured by ASD Spectroradiometer (350～2 500 nm) from BNU, the 40% reference board , two observation platforms of BNU make and one of Institute of Remote Sensing Applications make in Wulidun farmland quadrates and the desert transit zone strips. 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). (4) LAI measured by two methods in the the Wulidun farmland quadrates and Linze station quadrates. One is manual method. The LAI, plant height and the spacing of selected samples were measured by the ruler and the number of the sapmles in the quadrate were counted. Then the LAI can be calculated. The other method is LI-3100. Data were archived as Excel files.
Qian Jinbo, SONG Yi, WANG Zhixia, WANG Yang, PAN Xiaoduo, LI Jing, Li Xiangyun, Qu Yonghua, SUN Qingsong
The dataset of ground truth measurement synchronizing with the airborne microwave radiometers (L&K bands) mission was obtained in the Linze station foci experimental area on May 25, 2008. Observation items included: (1) soil moisture (0-5cm) measured once by the cutting ring method in the corner points of the 40 subplots of the west-east desert transit zone strip , three times in the corner points of the nine subplots of the north-south desert transit zone, once by the cutting ring and once by ML2X Soil Moisture Tachometer in the center points of nine subplots of the farmland quadrates. The preprocessed soil volumetric moisture data were archived as Excel files. (2) the surface radiative temperature by three handheld infrared thermometer (5# and 6# from Cold and Arid Regions Environmental and Engineering Research Institute, and one from Institute of Geographic Sciences and Natural Resources, which were all calibrated) in the west-east and north-south desert transit zone strip (various times synchronizing with the airplane), and Wulidun farmland quadrates (repeated twice at intervals of 15m from east to west). There are 34 sample points in total and each was repeated three times synchronizing with the airplane. Photos were taken. Data were archived as Excel files. (3) maize BRDF once by ASD Spectroradiometer (350～2 500 nm) from BNU, the reference board (40% before Jun. 15 and 20% hereafter), two observation platforms of BNU make and one of Institute of Remote Sensing Applications make in Wulidun farmland. Raw spectral data were archived as binary files, which were recorded daily in detail, and pre-processed data on reflectance 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.
DING Songchuang, GAO Song, PAN Xiaoduo, Qian Jinbo, WANG Yang, ZHU Shijie, LI Jing, XIAO Zhiqiang
The NDVI data set is the sixth version of the MODIS Normalized Difference Vegetation Index product (2001-2016) jointly released by NASA EOSDIS LP DAAC and the US Geological Survey (USGS EROS). The product has a temporal resolution of 16 days and a spatial resolution of 0.05 degrees. This version is a Climate Modeling Grid (CMG) data product generated from the original NDVI product (MYD13A2) with a resolution of 1 kilometer. Please indicate the source of these data as follows in acknowledgments: The MOD13C NDVI product was retrieved online courtesy of the NASA EOSDIS Land Processes Distributed Active Archive Center (LP DAAC), USGS/Earth Resources Observation and Science (EROS) Center, Sioux Falls, South Dakota, The [PRODUCT] was (were) retrieved from the online [TOOL], courtesy of the NASA EOSDIS Land Processes Distributed Active Archive Center (LP DAAC), USGS/Earth Resources Observation and Science (EROS) Center, Sioux Falls, South Dakota.
NASA
The data set includes the estimated data of the SOS (start of season) and the EOS (end of season) of vegetation in Sanjiangyuan based on 10-day synthetic NDVI products from the SPOT satellite. Two common phenological estimation methods were adopted: the threshold extraction method based on polynomial fitting (the term “poly” was included in the file names) and the inflection point extraction method based on double logistic function fitting (the term “sig” was included in the file names). These data can be used to analyse the relationship between vegetation phenology and climate change. The temporal coverage is from 1999 to 2013, and the spatial resolution is 1 km.
WANG Xufeng
The dataset of ground truth measurement synchronizing with Landsat TM was obtained in the A'rou foci experimental area from Jul. 10 to Jul. 12, 2008. The stellera and the whin coverage were mainly measured. Photos were taken in No. 2 quadrate of A'rou and an optional stellera land for coverage mesurement from Jul. 10 to 11, shooting straight downwards at the height of 1.5 m. The fisheye camera was Nikon D80 with a lens of Sigma 8mm F3.5 EX DG CIRCULAR FISHEYE. The vegetation height was measured on Jul. 12. One grid of 5m×5m was chosen in each of the eight quadrates (60m×60m or 120m×120m) and compartmentalized into 2.5m×2.5m, in which GPS positions by GARMIN GPS 76, species, the plant number and height were measured. Four files were included, the quadrates coordinates, stellera observations in No. 2 quadrate, the stellera quadrat investigation and TM quadrate investigation.
BAI Yanfen, Qian Jinbo, GAO Song, HAO Xiaohua, SHU Lele
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
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
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