The dataset of spectral reflectance observations was obtained by ASD (Analytical Sepctral Devices) in the Yingke oasis and Huazhaizi desert steppe foci experimental areas. Reflectance was calculated based on the equation R = (DN1/DN0)×R0, DN1 indicating DN of the targets, R0 and DN0 the reflectance and DN of the grey board. The reflectance spectra of maize and wheat canopy, the component leaf of the maize and BRDF in Yingke oasis maize field, Yingke oasis wheat field, Huazhaizi desert maize field, the transect spectrum in Huazhaizi desert No. 1 and 2 plots and Linze and Biandukou foci experimental area were measured on May 20, 24, 25, 28 and 30, Jun. 1, 4, 9, 14, 16, 18, 20, 22, 23, 24, 26, 29 and 30, Jul. 1, 4, 5, 6, 7, 9 and 11, 2008. Four ASD devices were used, from Peking University (350-2500nm), Institute of Remote Sensing Applications (350-2500nm), Beijing Academy of Agriculture and Forestry Sciences (350-1065nm) and BNU respectively. The reference boards were 40%, 50% and 99%. The above spectral reflectance dataset was synchronizing with WiDAS (Wide-angle Infrared Dual-mode line/area Array Scanner), OMIS-II and various spaceborne sensors. Raw data were binary files direct from ASD (by ViewSpecPro), and pre-processed data on reflectance were in Excel format.
CHEN Ling, REN Huazhong, WANG Haoxing, XIAO Yueting, YAN Guangkuo, ZHOU Hongmin, GE Yingchun, LI Xin, SHU Lele, GUANG Jie, LIU Sihan, SU Gaoli, XIA Chuanfu, Wen Jianguang, ZHANG Yang, ZHOU Chunyan, FAN Wenjie, TAO Xin, YAN Binyan, YAO Yanjuan, YANG Guijun, CHENG Zhanhui, Liu Liangyun, YANG Tianfu
GIMMS (glaobal inventory modelling and mapping studies) NDVI data is the latest global vegetation index change data released by NASA C-J-Tucker and others in November 2003. The dataset includes the global vegetation index changes from 1981 to 2006, the format is ENVI standard format, the projection is ALBERS, and its time resolution is 15 days and its spatial resolution is 8km. GIMMS NDVI data recorded the changes of vegetation in 22a area in the format of satellite data. 1. File format: The GIMMS-NDVI dataset contains all rar compressed files with a 15-day interval from July 1981 to 2006. After decompression, it includes an XML file, an .HDR header file, an .IMG file, and a .JPG image file. 2. File naming: The naming rules for compressed files in the NOAA / AVHRR-NDVI data set are: YYMMM15a (b) .n **-VIg_data_envi.rar, where YY-year, MMM-abbreviated English month letters, 15a-synthesized in the first half of the month, 15b-synthesized in the second half of the month, **-Satellite. After decompression, there are 4 files with the same file name, and the attributes are: XML document, header file (suffix: .HDF), remote sensing image file (suffix: .IMG), and JPEG image file. In this data set, the user uses the remote sensing image file with the suffix .IMG to analyze the vegetation index. Remote sensing image files with suffix of .IMG and .HDF used by users to analyze vegetation indices can be opened in ENVI and ERDAS software. 3. The data header file information is as follows: Coordinate System is: PROJECTION ["Albers_Conic_Equal_Area"], PARAMETER ["standard_parallel_1", 25], PARAMETER ["standard_parallel_2", 47], PARAMETER ["latitude_of_center", 0], PARAMETER ["longitude_of_center", 105], PARAMETER ["false_easting", 0], PARAMETER ["false_northing", 0], UNIT ["Meter", 1]] Pixel Size = (8000.000000000000000, -8000.000000000000000) Corner Coordinates: Upper Left (-3922260.739, 6100362.950) (51d20'23.06 "E, 46d21'21.43" N) Lower Left (-3922260.739, 1540362.950) (71d16'1.22 "E, 8d41'42.21" N) Upper Right (3277739.261, 6100362.950) (151d 8'57.22 "E, 49d 9'35.37" N) Lower Right (3277739.261, 1540362.950) (133d30'58.46 "E, 10d37'13.35" N) Center (-322260.739, 3820362.950) (101d22'21.08 "E, 35d42'18.02" N) Band 1 Block = 900x1 Type = Int16, ColorInterp = Undefined Computed Min / Max = -16066.000,11231.000 4. Conversion relationship between DN value and NDVI NDVI = DN / 1000, divided by 10000 after 2003 The NDVI value should be between [-1,1]. Data outside this interval represent other features, such as water bodies.
Tucker, C.J., J.E.Pinzon, M.E.Brown
The VEGETATION sensor sponsored by the European Commission was launched by SPOT-4 in March 1998. Since April 1998, SPOTVGT data for global vegetation coverage observation has been received by Kiruna ground station in Sweden. The image quality monitoring center in Toulouse, France is responsible for image quality and provides relevant parameters (such as calibration coefficient). Finally, the Belgian flemish institute for technological research (Vito)VEGETATION processing Centre (CTIV) is responsible for preprocessing into global data of 1km per day. Pretreatment includes atmospheric correction, radiation correction, geometric correction, production of 10 days to maximize the synthesized NDVI data, setting the value of -1 to -0.1 to -0.1, and then converting to the DN value of 0-250 through the formula DN=(NDVI+0.1)/0.004. The data set is a subset extraction from China, including spectral reflectance of four bands synthesized every 10 days and 10 days' maximum NDVI. It is data from 1998 to 2007 with a spatial resolution of 1km and a temporal resolution of 10 days. File format: Hfr and img files. The file naming rule is: CHN _ NDV _ YYYMMDD, where YYYYMMDD is the date of the day represented by the file and is also the main identifier different from other files. The remote sensing image files with suffix. IMG and. HDF used by users to analyze vegetation index can be opened in ENVI and ERDAS software. Coordinate system and projection Plate_Carree (Lon/Lat) PROJ_CENTER_LON 0.000000 PROJ_CENTER_LAT 0.000000 PIXEL_SIZE_UNITS DEGREES/PIXEL PIXEL_SIZE_X 0.0089285714 PIXEL_SIZE_Y 0.0089285714 SEMI_AXIS_MAJ 6378137.000000 SEMI_AXIS_MIN 6356752.314000 UL_LON (DEG) 73.000000 UL_LAT (DEG) 54.000000 LR_LON (DEG) 135.500000 LR_LAT (DEG) 5.000000 Corner coordinates are: Corner Coordinates: Upper Left ( 69.9955357, 55.0044643) Lower Left ( 69.9955357, 14.9955358) Upper Right ( 137.0044641, 55.0044643) Lower Right ( 137.0044641, 14.9955358) Where Upper Left is the upper left corner, Lower Left is the lower left corner, Upper Right is the upper right corner, and Lower Right is the lower right corner.
Greet Janssens, Food and Agriculture Organization of the United Nations（FAO）
In 2007, 2008 and 2009, ENVISAT ASAR data 179 scenes, covering the whole Heihe River Basin. Among them, there were 63 in 2007, 71 in 2008 and 45 in 2009. Imaging mode and acquisition time are respectively: app can select polarization mode from August 15, 2007 to December 23, 2007, from January 02, 2008 to December 202009-02-15, 2008 to September 06, 2009; imp imaging mode from June 19, 2009 to July 12, 2009; WSM wide mode from January 1, 2007 to December 302008-01-01, 2007 to November 28, 2008, from March 13, 2009 to May 22, 2009. The product level is L1B, which is amplitude data without geometric correction. The ENVISAT ASAR remote sensing data set of Heihe comprehensive remote sensing joint experiment is mainly obtained through the China EU "dragon plan" project (Project No.: 5322 and 5344); the WSM wide model data in 2007 and January 2008 are obtained from Professor Bob Su of ITC; the 8-view app can be purchased from the earth observation and digital earth center of Chinese Academy of Sciences.
Institute of Remote Sensing and Digital earth, Chinese Academy of Sciences
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 diurnal FPAR change observations was obtained in the Yingke oasis foci experimental areas. Observation items included: (1) Maize canopy reflectance spectra by ASD and 50% grey board, leaf SPAD by the chlorophyll meter and leaf photosynthesis by LI-6400 in Yingke oasis maize field on Jul. 5, 2008 (fixed point observations from 10:00-20:00 at intervals of one hour, and half an hour from 16:00) Besides, Photo: photosynthetic rate (µmol CO2 m-2 s-1), Cond: stomatal conductance (mol H2O m-2 s-1), Ci: intercellular CO2 viscosity (µmol CO2 mol-1), Trmmol: transpiration rate (mmol H2O m-2 s-1), VpdL: vapor pressure deficiency of leaves (kPa), Tleaf: leaf temperature (°C), ParIn_µm: active radiation of interior photosynthesis (µmol m-2 s-1), and ParOutµm: active radiation of outdoor photosynthesis (µmol m-2 s-1) were all archived. (2) Maize canopy reflectance spectra, leaf photosynthesis and diurnal FPAR change by ASD (Institute of Remote Sensing Applications), 50% grey board (Institute of Remote Sensing Applications), LI-6400 (Institute of Remote Sensing Applications) and SUNSCAN (Beijing academy of Agriculture and Forestry Sciences). Based on calibration lamp data (serial number: 64831), radiance spectrum on Jul. 9 by 1050 spectrometer (Beijing academy of Agriculture and Forestry Sciences) and 50% grey board and 99% white board calibration data, the spectrum data were preprocessed. Calibration was undertaken in accordance with the following precedures: a) The original DN was converted into radiance and further into readable EXCEL format by the spectrometer-matched calibration lamp data and ASD. b) Solar radiance was got by 99% white board radiance. solar radiance=the reference board radiance/the reference board reflectance. c) Spectrum from Agriculture and Forestry Sciences was sampled at an interval of 1.438nm, which was made into data at 1nm intervals by segmentation interpolation. d) Based on b=16.087a (where a is radiance before fitting and b after fitting), radiance data got by 68731 spectrograph were processed. The original maize leaf photosynthesis data (by LI-6400) were introduced into EXCEL format, diurnal changes of each leaf were archived as one single unit according to leaf classification. Maize FPAR (the fraction of photosynthetically active radiation) was got by FPAR= (canopyPAR－surface transmissionPAR－canopy reflection PAR+surface reflectionPAR) /canopy PAR; APAR= FPAR×canopy PAR. The unit for PAR was µmol m-2 s-1. The data included number (the whole leaf), observation time (hh:mm:ss), upper light (µmol m-2 s-1), upper reflectivity (µmol m-2 s-1), lower light (µmol m-2 s-1), lower reflectivity (µmol m-2 s-1) and Spread: variation coefficients of the probe optical intensity.
WANG Dacheng, YANG Guijun, CHENG Zhanhui, Liu Liangyun
The dataset of LST (land surface temperature) observed by the thermal camera (ThermaCAM SC2000 and ThermaCAM S60) at 24°×18° was obtained in the Yingke oasis, Huazhaizi desert steppe and Linze grassland foci experimental areas on May 20, 24,28 and 30, Jun. 1, 4, 16 and 29, Jul. 7, 8 and 11, 2008. Meanwhile, the optical photos were acquired in Yingke oasis maize field, Huazhaizi desert No. 1 and 2 plots, Huazhaizi desert maize field and Linze grassland. The dataset of ground truth measurement was synchronizing with WiDAS (Wide-angle Infrared Dual-mode line/area Array Scanner), OMIS-II, Landsat TM and ASTER.
HE Tao, KANG Guoting, REN Huazhong, YAN Guangkuo, WANG Haoxing, WANG Tianxing, LI Hua, Liu Qiang, XIA Chuanfu, ZHOU Chunyan, ZHOU Mengwei, CHEN Shaohui, YANG Tianfu
This dataset contains the monthly/yearly surface shortwave band albedo, fraction of absorbed photosynthetically active radiation (fPAR), leaf area index (LAI), vegetation continuous fields (tree cover and non-tree vegetation cover, VCF), land surface temperature (LST), net radiation (RN), evapotranspiration (ET), aboveground autotrophic respiration (RA-ag), belowground autotrophic respiration (RA-bg), gross primary production (GPP) and net primary production (NPP) in China from 2001 to 2018. The spatial resolution are 0.1 degree. Moreover, the dataset also includes these 11 ecosystem variables under climate-driven scenario (i.e., under no human disturbance). So, it can show the relative influences of climate change and human activities on land ecosystem in China during the 21st century.
CHEN Yongzhe, FENG Xiaoming, TIAN Hanqin, WU Xutong, GAO Zhen, FENG Yu, PIAO Shilong, LV Nan, PAN Naiqing, FU Bojie
The dataset of ground truth measurements for snow was obtained, synchronizing with airborne microwave radiometers (K&Ka bands) mission in the Binggou watershed foci experimental area on Mar. 29, 2008. Those provide reliable ground data for retrieval of snow properties and parameters, especially snow depth and snow water equivalent study. Observation items include (1) snow density, snow complex permittivity, snow volumetric moisture and snow gravimetric moisture by the snowfork in BG-A; (2) snow parameters in BG-A (18 points), BG-B (20 points), BG-EF (20 points) and BG-I (20 points): snow depth by the ruler, the snow temperature (mean of two measurements) by the probe thermometer, snow grain size by the handheld microscope, snow density by the cutting ring for each snow layer, and the snow surface temperature and the snow-soil interface temperature by the handheld infrared thermometer. For each snow pit, the snowpack was divided into several layers with 10-cm intervals of snow depth. Two files including raw data and pre-processed data were archived.
BAI Yanfen, BAI Yunjie, CAO Yongpan, GE Chunmei, GU Juan, HAN Xujun, HAO Xiaohua, LI Hongyi, LI Zhe, LIANG Ji, MA Mingguo, SHU Lele, WANG Xufeng, XU Zhen, ZHU Shijie, CHANG Cun, DOU Yan, MA Zhongguo, JIANG Tenglong, LIU Yan, ZHANG Pu
Nighttime light remote sensing has been an increasingly important proxy for human activities including socioeconomics and energy consumption. Defense Meteorological Satellite Program-Operational Linescan System from 1992 to 2013 and Suomi National Polar-Orbiting Partnership-Visible Infrared Imaging Radiometer Suite since 2012 are the most widely used datasets. Despite urgent needs for long-term products and pilot explorations in synthesizing them, the publicly available long-term products are limited. We propose a Night-Time Light convolutional Long Short-Term Memory (NTLSTM) network, and apply the network to produce annual Prolonged Artificial Nighttime-light DAtaset (PANDA) in China from 1984 to 2020. Model assessments between modelled and original images show that on average the Root Mean Squared-Error (RMSE) reaches 0.73, the coefficient of determination (R2) reaches 0.95, and the linear slope is 0.99 at pixel level, indicating a high confidential level of the data quality of the generated product. In urban areas, the modelled results can well capture temporal trends in newly built-up areas but slightly underestimate the intensity within old urban cores. Socioeconomic indicators (built-up areas, Gross Domestic Product, population) correlates better with the PANDA than with previous products in the literature, indicating its better potential in finding different controls of nighttime-light variances in different phases. Besides, the PANDA delineates different urban expansion types, outperforms other products in representing road networks, and provides potential nighttime-light sceneries in early years. PANDA provides the opportunity to better bridge the cooperation between human activity observations and socioeconomic or environmental fields
ZHANG Lixian, REN Zhehao, CHEN Bin, GONG Peng, FU Haohuan, XU Bing
The data used in this research was provided by the Pathfinder database of the EROS (Earth Resource Observation System) data center. The vegetation index NDVI was prepared by using the NOAA-AVHRR data source after radiation correction and geometric rough correction. Every day, each track image is processed with geometric fine correction, removal of bad lines, and removal of clouds, etc., and then NDVI calculation and synthesis. The daily NDVI calculation formula is: 1000 × (b2-b1) / (b2 + b1), where b1 and b2 are the first and second channels of AVHRR. Parameter table of Pathfinder AVHRR Parameter / Variable Definition Unit Range NDVI Normalized Vegetation Index None (-1,1) CLAVR identification Cloudiness index from CLAVR algorithm None (0,30) QC identification Data quality identification None (0,16) Scanning angle Sensor angle Radian (-1.05, 1.05) Solar zenith angle Solar zenith angle per pixel Radian (0, 1.04) Relative zenith angle Relative zenith angle of the sensor Radian (-1.05, 1.05) Ch1 reflectance Reflectance of the first channel (0.58-0.68um) Percent (0,100) Ch2 reflectance Reflectivity of the second channel (0.72--1.10um) Percentage (0, 100) Ch3 brightness temperature Bright temperature value of the third channel (3.55-3.95um) Kelvin temperature scale (160, 340) Ch4 brightness temperature Brightness value of the fourth channel (10.3-11.3um) Kelvin temperature scale (160, 340) Ch5 brightness temperature Bright temperature value of the fifth channel (11.5-12.5um) Kelvin temperature scale (160, 340) The data set includes data on NDVI in China's sub-regions from 1981 to June-September 2001, and data on tens of months in each of the years 1982, 1986, 1991, and 1996 (a total of 343 in 84 months, of which 1981 in June 1981). Data are missing in January and July 1st, and September 3rd 1994) Dataset attributes and format: This data set is stored in a year folder, which contains .HDR header files, .IMG files, and .JPG image files under the same file name. The data in the IMG is stored as integers. The naming rules are as follows: avhrrpf. *. Intfgl.yymmdd_geo where * represents ch1 or ch2 or ch4 or ch5 or ndvi, please refer to Table 1 for its specific meaning and range; yy represents the last two digits of the year; mm represents the month; dd represents the specific date. Data projection: Size is 963, 688 Coordinate System is: GEOGCS ["WGS 84", DATUM ["WGS_1984", SPHEROID ["WGS 84", 6378137,298.257223563, AUTHORITY ["EPSG", "7030"]], TOWGS84 [0,0,0,0,0,0,0], AUTHORITY ["EPSG", "6326"]], PRIMEM ["Greenwich", 0, AUTHORITY ["EPSG", "8901"]], UNIT ["degree", 0.0174532925199433, AUTHORITY ["EPSG", "9108"]], AUTHORITY ["EPSG", "4326"]] Origin = (70.035426000000001, 54.945585999999999) Pixel Size = (0.072727000000000, -0.072727000000000) Corner Coordinates: Upper Left (70.0354260, 54.9455860) (70d 2'7.53 "E, 54d56'44.11" N) Lower Left (70.0354260, 4.9094100) (70d 2'7.53 "E, 4d54'33.88" N) Upper Right (140.0715270, 54.9455860) (140d 4'17.50 "E, 54d56'44.11" N) Lower Right (140.0715270, 4.9094100) (140d 4'17.50 "E, 4d54'33.88" N) Center (105.0534765, 29.9274980) (105d 3'12.52 "E, 29d55'38.99" N) Band 1 Block = 963x1 Type = UInt16, ColorInterp = Undefined Computed Min / Max = 1.000,55480.000
Tucker, C.J., J.E.Pinzon, M.E.Brown
Gf-2 satellite is the first civil optical remote sensing satellite independently developed by China with a spatial resolution better than 1 meter. It is equipped with two high-resolution 1-meter panchromatic and 4-meter multi-spectral cameras, and the spatial resolution of the sub-satellite can reach 0.8 meters. This data set is the remote sensing image data of 6 jing gaofen-2 satellite in 2017.The folder list is: GF2_PMS1_E100.5_N37.2_20171013_L1A0002678101 GF2_PMS1_E100.5_N37.4_20171013_L1A0002678097 GF2_PMS1_E100.6_N37.6_20171013_L1A0002678096 GF2_PMS2_E100.3_N37.4_20170810_L1A0002534662 File naming rules: satellite name _ sensor name _ center longitude _ center latitude _ imaging time _L****
China Centre for Resources Satellite Data and Application
The datasets of “Land Cover Map of Heihe River Basin” provide monthly land cover classification data in 2012-2013. The HJ-1/CCD data with both high spatial resolution (30 m) and high temporal (2 days) frequency was used to construct the time series data. The NDVI curves from the time series HJ-1/CCD data can depict the variation of typical land surface. Different land use type has different NDVI curve. Rules were set to extract every land use type information. The datasets of “Land Cover Map of Heihe River Basin” hold the traditional land use types including water bodies, urban and built-up, croplands, evergreen coniferous forests, deciduous broadleaf forests and so on. Crop type classification (including maize, spring wheat, highland barely, rape and so on), snow and ice and glaciers information updates, make the datasets more detailed. Compared with previous land cover map and other products, the classification result of the datasets is visually bette. Especially in middle stream, the accuracy of crop classification is quite high compared with the data from the ground campaign. The accuracy of land cover map of the datasets in 2012 was evaluated using very high spatial resolution remote sensing data within Google Earth and data from campaign, and the overall accuracy can be as high as 92.19%. In a word, the datasets of “Land Cover Map of Heihe River Basin” is not only high in overall accuracy, but also more detailed in crop fine classification. Furthermore, it updated some new classes like glaciers and snow. The datasets of “Land Cover Map of Heihe River Basin” are consequently the classification datasets with the highest accuracy and most detailed information up to now.
ZHONG Bo, YANG Aixia
The dataset of spectral reflectance observations of the Picea crassifolia was obtained at the super site around the Dayekou Guantan forest station. Six measurements were carried out altogether, including three outdoors and three indoors. (1) Outdoor multiangle (-60°, -50°, -40°, -30°, -20°, -0°, 10°, 20°, 30°, 40°, 50° and 60°) and four-component (the sunshine and the shaded canopy, the sunshine and the shaded land) spectrum of Qinghai spruce was measured by ASD, FieldSpec Pro and the observation platform (of BNU make) on Jun. 10 and 11, 2008. Optical fibres of 1m and 10m were used as required. Data were archived as Excel files. (2) Indoor observations by the integrating sphere, Li－Cor 1800-12s (BNU), ASD and FieldSpec Pro were carried out on Jun. 5, 0 and 10, 2008. They were mainly for trees of different ages, reflectance of Qinghai spruce bark, and reflectance and transmission. The data can only be opened by ASD ViewSpecPro; the processed spreadsheet file can be opened by Microsoft Excel. (3) Vertical ground object (scrub, meadow, moss, the shaded moss, litter, the bare land, Qinghai spruce of different ages) spectrum was measured by ASD and FieldSpec Pro on Jun. 4, 2008. Optical fibres of 1m and 10m were used as required.
SONG Jinling, FU Zhuo, GUO Xinping, WANG Xinyun, WANG Qiang, WANG Bengyu
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
On June 15, 2012, the satellite transit ground synchronous observation was carried out in the TerraSAR-X sample near the super station in the dense observation area of Daman. TerraSAR-X satellite carries X-band synthetic aperture radar (SAR). The daily transit image is HH / VV polarized, with a nominal resolution of 3 m, an incidence angle of 22-24 ° and a transit time of 19:03 (Beijing time), which mainly covers the ecological and hydrological experimental area of the middle reaches artificial oasis. The local synchronous data set can provide the basic ground data set for the development and verification of active microwave remote sensing soil moisture retrieval algorithm. Quadrat and sampling strategy: Six natural blocks are selected in the southeast of the super station, with an area of about 100 m × 100 m. One plot in the northwest corner of the sample plot is watermelon field, others are corn. The basis of sample selection is: (1) considering different vegetation types, i.e. watermelon and corn; (2) considering the visible light pixel, the sample size of 100m square can guarantee at least 4 30 M-pixel is located in the sample; (3) the location of the sample is near the super station, with convenient transportation. The observation of the super station is in the north, and there is a water net node on both sides of the East and the west, which makes it possible to integrate these observations in the future; (4) in addition, there are some obvious points around the sample, which can ensure that the geometric correction of the SAR image is more accurate in the future. Considering the resolution of the image, 21 splines (distributed from east to West) are collected at 5 m intervals. Each line has 23 points (north-south direction) at 5 m intervals. Four hydroprobe data acquisition systems (HDAS, reference 2) are used to measure at the same time. The sampling interval is controlled by the scale and moving splines on the measuring line to make up for the lack of using hand-held GPS. Measurement content: About 500 points on the quadrat were obtained, and each point was observed twice, i.e. in each sampling point, once in the film (marked a in the data record) and once out of the film (marked b in the data record); although the watermelon land was also covered with film, considering that it was not laid horizontally, only the soil moisture at the non covered position was measured (marked b in both data records). As the HDAS system uses pogo portable soil sensor, the soil temperature, soil moisture (volume moisture content), loss tangent, soil conductivity, real part and imaginary part of soil complex dielectric are observed. The vegetation team completed the measurement of biomass, Lai, vegetation water content, plant height, row ridge distance, chlorophyll, etc. Data: This data set includes two parts: soil moisture observation and vegetation observation. The former saves the data format as a vector file, the spatial location is the location of each sampling point (WGS84 + UTM 47N), and the measurement information of soil moisture is recorded in the attribute file; the vegetation sampling information is recorded in the excel table.
WANG Shuguo, MA Mingguo, LI Xin
The dataset of ground truth measurements synchronizing with MODIS, ALOS PALSAR and AMSR-E was obtained in the Biandukou foci experimental area on May 24, 2008. Observation items included: (1) the surface temperature in No. 1 (grassland), No. 2 (the rape land), No. 3 (the rape land), No. 4 (the wheat land) and No. 5 quadrate (wheat and rape); (2) the soil moisture by WET in No. 2 quadrate; (3) GPR and WET; (4) The spectrum by ASD Fieldspec FRTM (Boulder, Co, USA), 350nm-2500nm, 3nm for the visible near-infrared band and 10nm for the shortwave infrared band). The spectrum data were archived in the ASCII format, with the first five rows as the file header and the following two columns as wavelength (nm) and reflectance (percentage) respectively, and can be opened by .txt or wordpad. The .txt file was not reflectance but intermediate file for further calculation. Raw data were binary files direct from ASD (by ViewSpecPro). The surface radiative temperature and the physical temperature were measured by the handheld infrared thermometer. Besides, the cover type was also recorded. The data can be opened by Microsoft Office. Soil moisture was acquired by WET and the cutting ring. The data can be opened by Microsoft Office. Six data files were included, soil moisture, the surface temperature, GPR, coverage photos and preprocessed data, ground objects spectrum and satellite images.
BAI Yunjie, CAO Yongpan, CHE Tao, DU Ziqiang, HAO Xiaohua, WANG Zhixia, WU Yueru, CHAI Yuan, CHANG Sheng, QIAN Yonggang, SUN Xiaoqing, WANG Jindi, YAO Dongping, ZHAO Shaojie, ZHENG Yue, ZHAO Yingshi, LI Xiaoyu, PATRICK Klenk, HUANG Bo, LI Shihua, LUO Zhen
The dataset of ground truth measurements synchronizing with ASTER was obtained in the Yingke oasis and Huazhaizi desert steppe foci experimental areas on May 28, 2008. Observation items included: (1) 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. (2) Photosynthesis by LI-6400. Raw data were archived in the user-defined format (by notepat.exe) and processed data were in Excel format. (3) 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. (4) Coverage fraction of maize and wheat by the self-made instrument and the camera (2.5m-3.5m above the ground) in Yingke oasis maize field. 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 the surrounding environment was also recorded. Data included the primarily measured image and final fraction of vegetation coverage. (5) the radiative temperature of maize, wheat and the bare land in Yingke oasis maize field by ThermaCAM SC2000 using 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). (6) the radiative temperature by the automatic thermometer (FOV: 10°; emissivity: 0.95), 3 for maize canopy, the bare land and wheat canopy in Yingke oasis maize field, one for maize canopy in Huazhaizi desert maize field, and 2 for vegetation and the desert bare land in Huazhaizi desert No. 2 plot,at nadir at a time interval of one second. Raw data, blackbody calibrated data and processed data were all archived in Excel format. (7) 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. (8) LAI in Yingke oasis maize field. The maximum leaf length and width of each maize and wheat were measured. Data were archived in Excel format. (9) 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 the table format of Word. (10) The radiative temperature in Yingke oasis maize field (the transect observation), Yingke oasis wheat field (the transect observation), Huazhaizi desert maize field (the transect observation) and Huazhaizi desert No. 2 plot (the diagonal observation) by the handheld infrared thermometer (BNU and Institute of Remote Sensing Applications). Raw data (in Word format), blackbody calibrated data and processed data (in Excel format) were all archived.
CHAI Yuan, CHEN Ling, KANG Guoting, QIAN Yonggang, REN Huazhong, WANG Haoxing, WANG Jianhua, SHU Lele, LI Li, LIU Sihan, XIN Xiaozhou, ZHANG Yang, ZHOU Chunyan, ZHOU Mengwei, TAO Xin, WANG Dacheng, LI Xiaoyu, CHENG Zhanhui, YANG Tianfu, HUANG Bo, LI Shihua, LUO Zhen
The global monthly all-sky land surface temperature (2000-2020) is produced by the method from Chen et al. 2017 JHM.
CHEN Xuelong, BOB Su, MA Yaoming
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
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