Near-surface atmospheric driving data prepared by ETMonitor and WRF models based on remote sensing surface evapotranspiration model were used to estimate the average surface evapotranspiration of the heihe river basin with a resolution of 250m in 8 days from may to September 2012.The coordinate system is the projection of equal latitude and longitude, and the spatial range is 96.5e -- 102.5e, 37.5n -- 43N.8 days data using synthetic way of storage, the data format for GEOTIFF, naming: 2012 ddd_evapotranspiration. Tif, including a DDD, ordinal number, for example 2012121 _evapotranspiration. Tif said 2012 day ordinal number is 121-128 days, the average surface evaporation unit is mm/d.The data type is single-precision floating point with an invalid value of -9.
JIA Li
Near-surface atmospheric driving data prepared by ETMonitor and WRF models based on remote sensing surface evapotranspiration model were used to estimate the daily surface evapotranspiration of the heihe river basin at 1km from 2009 to 2011.The coordinate system is the longitude and latitude projection, and the spatial range is 96.5e -- 102.5e, 37.5n -- 43N.Using daily data storage, data format for GEOTIFF, naming: yyyyddd_EvapoTranspiration. tif, including yyyy for years, DDD for ordinal.The data type is single-precision floating point in mm/d and the invalid value is -9.
JIA Li
Water scarcity，food crises and ecological deterioration caused by drought disasters are a direct threat to food security and socio-economic development. Improvement of drought disaster risk assessment and emergency management is now urgently required. This article describes major scientific and technological progress in the field of drought disaster risk assessment. Drought is a worldwide natural disaster that has long affected agricultural production as well as social and economic activities. Frequent droughts have been observed in the Belt and Road area, in which much of the agricultural land is concentrated in fragile ecological environment. Soil relative humidity index is one of the indicators to characterize soil drought and can directly reflect the status of crops' available water.
FAN Wenjie
Firstly, the canopy reflectance is expressed as a function of a series of parameters, such as Lai / fAPAR, wavelength, soil and leaf reflectance, aggregation index, incidence and observation angle. For several key parameters, the parameter table is established as the input of inversion. Then input the surface reflectance data and land cover data after preprocessing, and use the LUT method to retrieve the fAPAR products. See the reference for detailed algorithm. Image format: TIF Image size: about 1m per scene Time frame: 2012 Time resolution: month by month Spatial resolution: 1km
FAN Wenjie
This dataset contains three basic remote sensing data of digital topography (DEM), TM remote sensing image and NDVI vegetation index of badan jilin desert. 1. DEM, digital terrain data, from the SRTM1 data set released by NASA in the United States, was cropped in the desert area.The resolution is 30 m.The data is stored in the DEM folder, and the dm.ovr file can be opened by ArcGIS. 2. TM image data.The composite data of Landsat TM/ETM + 543 band released by NASA were cropped in the desert lake group distribution area.The resolution is 30 m.From 1990 to 2010, one scene was selected in summer and one scene in autumn every five years to analyze the long-term changes of the lake.In 2002, there was a scene for each quarter to analyze the changes of the lake during the year.The data is stored in TM folder, TIFF format, can be opened by ArcGIS or ENVI software.The file naming rule is yyyymm.tif, where yyyy refers to the year and mm to the month. For example, 199009 refers to the time corresponding to the impact data of September 1990. 3. NDVI, vegetation index.The modis-ndvi product MOD13Q1, released by NASA, was cropped in desert areas.The NDVI data of every ten days of the growing season (June, July, August and September) from 2000 to 2012 are included. The spatial resolution is 250 m and the temporal resolution is 16 days.Stored in NDVI folder, TIFF format, can be opened by ArcGIS or ENVI software.Mosaic_tmp_yyyyddd.hdfout.250m_16_days_ndvi_roi.tif, Where yyyy represents the year and DDD represents the day of DDD of the year.
JIN Xiaomei, HU Xiaonong
On 25 July 2012, a Leica ALS70 airborne laser scanner boarded on the Y-12 aircraft was used to obtain the point cloud data. Leica ALS70 airborne laser scanner has unlimited numbers of returns intensities measurements including the first, second, third return intensities. The wavelength of laser light is 1064 nm. The absolute flight altitude is 5500 m with the point cloud density 1 points per square meter. Aerial LiDAR- DSM was obtained through parameter calibration, automatic classification of point cloud density and manual editing.
XIAO Qing, Wen Jianguang
On 25 August 2012, Leica ALS70 airborne laser scanner boarded on the Y-12 aircraft was utilized to obtain point cloud data. Leica ALS70 airborne laser scanner has unlimited numbers of returns intensities measurements including the first, second, third return intensities. The wavelength of laser light is 1064 nm. The absolute flight altitude is 5200 m with the point cloud density 1 point per square meter. Aerial LiDAR-DEM was obtained through parameter calibration, automatic classification of point cloud density and manual editing.
XIAO Qing, Wen Jianguang
On 25 July 2012, a Leica ALS70 airborne laser scanner boarded on the Y-12 aircraft was used to obtain the point cloud data. Leica ALS70 airborne laser scanner has unlimited numbers of returns intensities measurements including the first, second, third return intensities. The wavelength of laser light is 1064 nm. The absolute flight altitude is 4800 m with the point cloud density 1 points per square meter. Aerial LiDAR- DSM was obtained through parameter calibration, automatic classification of point cloud density and manual editing.
XIAO Qing, Wen Jianguang
On 25 July 2012, a Leica ALS70 airborne laser scanner boarded on the Y-12 aircraft was used to obtain the point cloud data. Leica ALS70 airborne laser scanner has unlimited numbers of returns intensities measurements including the first, second, third return intensities. The wavelength of laser light is 1064 nm. The absolute flight altitude is 4800 m with the point cloud density 1 points per square meter. Aerial LiDAR-DEM was obtained through parameter calibration, automatic classification of point cloud density and manual editing.
XIAO Qing, Wen Jianguang
On 25 July 2012, a Leica ALS70 airborne laser scanner boarded on the Y-12 aircraft was used to obtain the point cloud data. Leica ALS70 airborne laser scanner has unlimited numbers of returns intensities measurements including the first, second, third return intensities. The wavelength of laser light is 1064 nm. The absolute flight altitude is 5500 m with the point cloud density 1 points per square meter. Aerial LiDAR-DEM was obtained through parameter calibration, automatic classification of point cloud density and manual editing.
XIAO Qing, Wen Jianguang
The NDVI data of GIMMS (glaobal modelling and mapping studies) is the latest global vegetation index change data released by NASA c-j-tucker et al in November 2003. This data set includes the changes in the vegetation index of the long time series of the qaidam basin from 1981 to 2006. The format is the standard ENVI format, and the projection is ALBERS. The temporal resolution is 15 days and the spatial resolution is 8km.GIMMS NDVI data recorded the vegetation changes in 22a region in the format of satellite data. 1. File format: The gimms-ndvi data set contains all the.rar compressed files with a 15-day interval from July 1981 to 2006, including one XML document, one.hdr header file, one.img file, and one.jpg image file after unzipped. 2. File name: The naming rule for compressed files in NOAA/ avhrr-ndvi data set is: YYMMM15a(b). N ** -vig_data_envi.After unzipping, there are four files with the same file name and attributes: XML document, header file (suffix:.hdf), remote sensing image file (suffix:.img) and JPEG image file. Remote sensing image files with suffixes.img and.hdf, which are used by users to analyze vegetation index, can be opened in ENVI and ERDAS software.
National Aeronautics and Space Administration
On 25 August 2012, a Leica ALS70 airborne laser scanner boarded on the Y-12 aircraft was used to obtain LiDAR DSM point cloud data. Leica ALS70 airborne laser scanner has unlimited numbers of returns intensities measurements including the first, second, third return intensities. The wavelength of laser light is 1064 nm. The absolute flight altitude is 5200 m with the point cloud density 1 point per square meter. Aerial LiDAR-DSM was obtained through parameter calibration, automatic classification of point cloud density and manual editing.
XIAO Qing, Wen Jianguang
This data set is the multispectral data used to retrieve 30 meter Lai and fAPAR products in 2012. It is obtained by the environmental satellite CCD sensor with a resolution of 30 m and four bands. This data set has been geometric corrected, radiometric corrected and converted into reflectivity image.
FAN Wenjie
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 number). 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 the Shule River long-time series vegetation index data set, which is mainly aimed at normalized difference vegetation index (NDVI). It includes spectral reflectance of four bands synthesized every 10 days and maximum NDVI for 10 days from 1998 to 2008. The spatial resolution is 1km and the temporal resolution is ten days.
Greet Janssens
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 dataset of ground truth measurements synchronizing with Envisat ASAR was obtained in No. 1 and 2 quadrates of the E'bao foci experimental area on Oct. 17, 2007 during the pre-observation period The data were in AP mode and VV/VH polarization combinations, and the overpass time was approximately at 23:04 BJT. Both the quadrates were divided into 3×3 subsites, with each one spanning a 30×30 m2 plot. 25 sampling points were chosen, including centers and corners. Simultaneous with the satellite overpass, numerous ground data were collected, soil volumetric moisture, soil conductivity, the soil temperature, and the real part of soil complex permittivity by the WET soil moisture tachometer; the surface radiative temperature by the hand-held infrared thermometer; soil gravimetric moisture, volumetric moisture, and soil bulk density by drying soil samples from the cutting ring. Meanwhile, vegetation parameters as height, coverage and water content were also observed. Meanwhile, vegetation parameters as height, coverage and water content were also observed. Those provide reliable ground data for retrieval and verification of soil moisture, soil freeze/thaw status and the microwave radiative transfer model from active remote sensing approaches.
CHAO Zhenhua, CHE Tao, QIN Chun, WU Yueru
The dataset of ground truth measurements synchronizing with Envisat ASAR was obtained in No.2 quadrate of the A'rou foci experimental area on Oct. 17, 2007 during the pre-observation period. The Envisat ASAR data were in AP mode and VV/VH polarization combinations, and the overpass time was approximately at 23:04 BJT. The quadrate was divided into 3×3 subsites, with each one spanning a 30×30 m2 plot. 25 sampling points were chosen, including centers and corners of each subsites. Simultaneous with the satellite overpass, numerous ground data were collected, soil volumetric moisture by ML2X; soil volumetric moisture, soil conductivity, soil temperature, and the real part of soil complex permittivity by WET soil moisture sensor; the surface radiative temperature by the hand-held infrared thermometer; soil gravimetric moisture, volumetric moisture, and soil bulk density after drying by the cutting ring (100cm^3). Meanwhile, vegetation parameters as height, coverage and water content were also observed. Surface roughness was detailed in the "WATER: Surface roughness dataset in the A'rou foci experimental area". Those provide reliable ground data for retrieval and validation of soil moisture and freeze/thaw status from active remote sensing approaches.
BAI Yunjie, HAO Xiaohua, LI Hongyi, LI Xin, LI Zhe
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 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 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
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