Based on the data of GF-1 and GF-2 in China, the freeze-thaw disaster distribution data of Qinghai Tibet project corridor is produced by using the deep learning classification method and manual visual interpretation and correction. The geographical range of the data is 40km along the Xidatan Anduo section of Qinghai Tibet highway. The data include the distribution data of thermokast lakes and the distribution data of thermal melting landslides. The dataset can provide data basis for the research of freeze-thaw disaster and engineering disaster prevention and reduction in Qinghai Tibet engineering corridor. The spatial distribution of freezing and thawing disasters within 40km along the Xidatan-Anduo section of Qinghai Tibet highway is self-made based on the domestic GF-2 image data. Firstly, the deep learning method is used to extract the mud flow terrace block from GF-2 data; Then, ArcGIS is used for manual editing.
NIU Fujun, LUO Jing LUO Jing
Fractional Vegetation Cover (FVC) refers to the percentage of the vertical projected area of vegetation to the total area of the study area. It is an important indicator to measure the effectiveness of ecological protection and ecological restoration. It is widely used in the fields of climate, ecology, soil erosion and so on. FVC is not only an ideal parameter to reflect the productivity of vegetation, but also can play a good role in evaluating topographic differences, climate change and regional ecological environment quality. This research work is mainly to post process two sets of glass FVC data, and give a more reliable vegetation coverage of the circumpolar Arctic Circle (north of 66 ° n) and the Qinghai Tibet Plateau (north of 26 ° n to 39.85 °, east longitude 73.45 ° to 104.65 °) in 2013 and 2018 through data fusion, elimination of outliers and clipping.
YE Aizhong
NDVI reflects the background effects of plant canopy, such as soil, wet ground, snow, dead leaves, roughness, etc., and is related to vegetation cover. It is one of the important parameters to reflect the crop growth and nutrient information. According to this parameter, the N demand of crops in different seasons can be known, which is an important guide to the reasonable application of N fertilizer. Correct NDVI (C-NDVI) is the value of NDVI after excluding the influence of climate elements (temperature, precipitation, etc.) on NDVI. Taking precipitation as an example, studies on the lag effect of precipitation on vegetation growth show that the lag time of precipitation effects varies in different regions due to differences in vegetation composition and soil types. In this study, we post-processed the MODIS NDVI data and firstly correlated the NDVI value of the current month with the precipitation of the current month, the average value of the precipitation of the current month with that of the previous month, and the average value of the precipitation of the current month with that of the previous two months to determine the optimal lag time. The NDVI was regressed on precipitation and air temperature to obtain the correlation coefficients, and then the corrected NDVI values were calculated by the difference between the MODIS NDVI and the NDVI regressed on climate factors. We corrected NDVI using climate data to give reliable vegetation correction indices for the circum-Arctic Circle (range north of 66°N) and the Tibetan Plateau (range 26°N to 39.85°N and 73.45°E to 104.65°E) for 2013 and 2018. The spatial resolution of the data is 0.5 degrees and the temporal resolution is monthly values.
YE Aizhong
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
Photosynthetically active radiation (PAR) is fundamental physiological variable driving the process of material and energy exchange, and is indispensable for researches in ecological and agricultural fields. In this study, we produced a 35-year (1984-2018) high-resolution (3 h, 10 km) global grided PAR dataset with an effective physical-based PAR model. The main inputs were cloud optical depth from the latest International Satellite Cloud Climatology Project (ISCCP) H-series cloud products, the routine variables (water vapor, surface pressure and ozone) from the ERA5 reanalysis data, aerosol from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) products and albedo from Moderate Resolution Imaging Spectroradiometer (MODIS) product after 2000 and CLARRA-2 product before 2000. The grided PAR products were evaluated against surface observations measured at seven experimental stations of the SURFace RADiation budget network (SURFRAD), 42 experimental stations of the National Ecological Observatory Network (NEON), and 38 experimental stations of the Chinese Ecosystem Research Network (CERN). The instantaneous PAR was validated at the SURFRAD and NEON, and the mean bias errors (MBEs) and root mean square errors (RMSEs) are 5.6 W m-2 and 44.3 W m-2, and 5.9 W m-2 and 45.5 W m-2, respectively, and correlation coefficients (R) are both 0.94 at 10 km scale. When averaged to 30 km, the errors were obviously reduced with RMSEs decreasing to 36.3 W m-2 and 36.3 W m-2 and R both increasing to 0.96. The daily PAR was validated at the SURFRAD, NEON and CERN, and the RMSEs were 13.2 W m-2, 13.1 W m-2 and 19.6 W m-2, respectively at 10 km scale. The RMSEs were slightly reduced to 11.2 W m-2, 11.6 W m-2, and 18.6 W m-2 when upscaled to 30 km. Comparison with the other well-known global satellite-based PAR product of the Earth's Radiant Energy System (CERES) reveals that our PAR product was a more accurate dataset with higher resolution than the CRERS. Our grided PAR dataset would contribute to the ecological simulation and food yield assessment in the future.
TANG Wenjun
The dataset include ground-based passive microwave brightness temperature, multi-angle brightness temperature, ten-minute 4-component radiation and snow temperature, daily snow pit data and hourly meteorological data observed at Altay base station（lon：88.07、lat: 44.73）from November 27, 2015 to March 26, 2016. Daily snow pit parameters include: snow stratification, stratification thickness, density, particle size, temperature. These data are stored in five NetCDF files: TBdata. nc, TBdata-multiangle. nc, ten-minute 4 component radiation and snow temperature. nc, hourly meteorological and soil data. nc and daily snow pit data.nc. TBdata. nc is brightness temperature at 3 channels for both polarizations automatically collected by a six-channel dual polarized microwave radiometer RPG-6CH-DP. The contents include Year, month, day, hour, minute, second, Tb1h, Tb1v, Tb18h, Tb18v, Tb36h, Tb36v, incidence angle, azimuth angle. TBdata-multiangle.nc is 7 groups of multi-angle brightness temperatures at 3 channels for both polarizations. The contents include Year, month, day, hour, minute, second, Tb1h, Tb1v, Tb18h, Tb18v, Tb36h, Tb36v, incidence angle, azimuth angle. The ten-minute 4 component radiation and snow temperature.nc contains 4 component radiation and layered snow temperatures. The contents include Year, month, day, hour, minute, SR_DOWN, SR_UP, LR_DOWN, LR_UP, T_Sensor, ST_0cm, ST_5cm, ST_15cm, ST_25cm, ST_35cm, ST_45cm, ST_55cm. The hourly meteorological and soil data.nc contains hourly weather data and layered soil data. The contents include Year, month, day, hour, Tair, Wair, Pair, Win, SM_10cm, SM_20cm, Tsoil_5cm, Tsoil_10cm, Tsoil_15 cm, Tsoil_20cm. The daily snow pit data.nc. is manual snow pit data. The observation time was 8:00-10:100 am local time. The contents include Year, month, day, snow depth, thickness_layer1, thickness_layer2, thickness_layer3, thickness_layer4, thickness_layer5, thickness_layer6, Long_layer1, Short_layer1, Long_layer2, Short_layer2, Long_layer3, Short_layer3, Long_layer 4, Short_layer4, Long_layer5, Short_layer5, Long_layer6, Short_layer 6, Stube, Snow shovel_0-10, Snow shovel _10-20, Snow shovel _20-30, Snow shovel _30-40, Snow shovel _40-50, Snow fork_5, Snow fork _10, Snow fork _15, Snow fork_20, Snow fork_25, Snow fork_30, Snow fork_35, Snow fork_40, Snow fork_45, Snow fork_50, shape1, shape2, shape3, shape4, shape5,
DAI Liyun
This dataset includes component temperatures measured by the thermal imager at the Mixed Forest and Sidaoqiao stations between 23 July and 18 August, 2014. The Mixed Forest (101.1335 °E, 41.9903 °N, 874 m.a.s.l.) and Sidaoqiao (101.1374 °E, 42.0012 °N, 873 m.a.s.l.) stations were located in the downstream of the Heihe River basin, Dalaihubu Town, Ejin Banner, Inner Mongolia. At the Mixed Forest station, a Testo 890-2 thermal imager (Testo Inc., Germany) with a resolution of 640 × 480 pixels was employed to acquire brightness temperature images. The imager was manually operated from a 10-m height platform of the tower between 10:00-16:00 (China Standard Time, CST) with an observation interval of 1-h on cloudless days. On August 4th observations were acquired between 11:00 and 17:00 at an interval of 10-min to match observations acquired with an airborne TIR imager. The ground based imager was pointed to five viewing directions (southeast-SE, east-E, northeast-NE, northwest-NW, and southwest-SW) and was inclined 25°–45° below the horizon depending on viewing direction. At Sidaoqiao station, a Testo 875-2i imager (Testo Inc., Germany) with a resolution of 160 × 120 pixels was manually operated from a 10-m high platform to acquire brightness temperature images in directions SW, SE, NE, and NW. Depending on the targets in each viewing direction, the imager was inclined to 30°–45° below the horizon. Observations at Sidaoqiao and Mixed Forest stations were almost synchronous. Furthermore, visible images were taken simultaneously with the aforementioned two TIR imagers (2048 × 1536 pixels for Testo 890-2 and 640 × 480 pixels for Testo 875-2i).
LI Mingsong , MA Jin
This dataset includes component temperatures measured by the thermal infrared (TIR) radiometers at the Mixed Forest and Sidaoqiao stations between 22 July, 2014 and 19 July, 2016. The Mixed Forest (101.1335 °E, 41.9903 °N, 874 m.a.s.l.) and Sidaoqiao (101.1374 °E, 42.0012 °N, 873 m.a.s.l.) stations were located in the downstream of the Heihe River basin, Dalaihubu Town, Ejin Banner, Inner Mongolia. At the Mixed Forest station, two TIR radiometers (SI-111, Apogee Instruments Inc., USA) connected to a data logger (CR800, Campbell Scientific Inc., USA) measured component temperatures of the sunlit canopy and shaded canopy. TIR radiometers were mounted horizontally at 5 m height on iron rods just south and north of a tree and pointed to its canopy. The distance from the sensor to the canopy was ~1 m. At the Sidaoqiao station, two SI-111 TIR radiometers connected to a CR800 data logger measured component temperatures of the soil and shrub. The first sensor pointed from 2 m height under a viewing zenith angle of 45° to bare soil; the second sensor was mounted at 1-m height and pointed horizontally into the shrub canopy.
ZHOU Ji, LI Mingsong , MA Jin
This is the vegetation index (NDVI) for Maduo County in July, August and September of 2016. It is obtained through calculation based on the multispectral data of GF-1. The spatial resolution is 16 m. The GF-1 data are processed by mosaicking, projection coordinating, data subsetting and other methods. The maximum synthesis is then conducted every month in July, August, and September.
LI Fei, Fei Li, Zhijun Zhang
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 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
During lidar and widas flight in summer 2012, the ground synchronously carried out the continuous observation of differential GPS of ground base station, and obtained the synchronous GPS static observation data, which is used to support the synchronous solution of aviation flight data. Measuring instrument: Two sets of triple R8 GNSS system. Zgp8001 sets Time and place of measurement: On July 19, 2012, EC matrix lidar flew and observed at mjwxb (northwest of Maojiawan) and sbmz (shibamin) two base stations at the same time On July 25, 2012, lidar of hulugou small watershed and tianmuchi small watershed in the upper reaches flew, observed in XT Xiatang, lidar of Zhangye City calibration field in the middle reaches, and observed in mjwxb (northwest of Maojiawan) On July 26, 2012, lidar flight of hulugou small watershed and tianmuchi small watershed in the upper reaches was observed in XT Xiatang, lidar flight of Zhangye City calibration field in the middle reaches was observed in HCZ (railway station) On August 1, 2012, the upper east and West branches of widas flew and observed in yng (yeniugou) On August 2, 2012, the midstream EC matrix test area widas flew and observed in HCZ (railway station) On August 3, 2012, the midstream EC matrix test area widas flew and observed in mjwxb (northwest Maojiawan) Data format: Original data format before differential preprocessing.
LIU Xiangfeng, MA Mingguo
The aim of the simultaneous observation of land surface temperature is obtaining the land surface temperature of different kinds of underlying surface, including greenhouse film, the roof, road, ditch, concrete floor and so on, while the sensor of thermal infrared go into the experimental areas of artificial oases eco-hydrology on the middle stream. All the land surface temperature data will be used for validation of the retrieved land surface temperature from thermal infrared sensor and the analysis of the scale effect of the land surface temperature, and finally serve for the validation of the plausibility checks of the surface temperature product from remote sensing. 1. Observation time and other details On 25 June, 2012, ditch and asphalt road surface temperatures were observed once every five minutes using handheld infrared thermometers recorded. On 26 June, 2012, ditch and asphalt road surface temperatures were observed once every five minutes using handheld infrared thermometers while greenhouse film and concrete floor surface temperatures were observed once every one second using self-recording point thermometer. On 29 June, 2012, concrete floor surface temperatures were observed continuously using handheld infrared thermometers during the sensor of TASI go into the region. At the same time, greenhouse film and concrete floor surface temperatures were observed once every one second using self-recording point thermometer. On 30 June, 2012, asphalt road, ditch, bare soil, melonry and ridge of field surface temperatures were observed continuously using handheld infrared thermometers during the sensor of TASI go into the region. At the same time, greenhouse film and concrete floor surface temperatures were observed once every one second using self-recording point thermometer. On 10 July, 2012, asphalt road, ditch, bare soil, melonry and ridge of field surface temperatures were observed once every one minute using handheld infrared thermometers during the sensor of TASI go into the region. At the same time, concrete floor surface temperatures were observed once every six second using self-recording point thermometer. On 26 July, 2012, asphalt road, concrete floor, bare soil and melonry surface temperatures were observed once every one minute using handheld infrared thermometers during the sensor of WiDAS go into the region. At the same time, greenhouse film and concrete floor surface temperatures were observed once every six second using self-recording point thermometer. On 2 August, 2012, corn field and concrete floor surface temperatures were observed using handheld infrared thermometers. At the same time, greenhouse film and concrete floor surface temperatures were observed once every six second using self-recording point thermometer. For corn field, twelve sites were selected according to the flight strip of the WiDAS sensor, and for each site one plot surface temperatures were recorded continuously during the sensor of WiDAS go into the region. On 3 August, 2012, corn field and concrete floor surface temperatures were observed using handheld infrared thermometers. At the same time, greenhouse film and concrete floor surface temperatures were observed once every six second using self-recording point thermometer. For corn field, fourteen sites were selected according to the flight strip of the WiDAS sensor, and for each site three plots surface temperatures were recorded continuously during the sensor of WiDAS go into the region. 2. Instrument parameters and calibration The field of view of the self-recording point thermometer and the handheld infrared thermometer are 10 and 1 degree, respectively. The emissivity of the latter was assumed to be 0.95. The observation heights of the self-recording point thermometer for the greenhouse film and the concrete floor were 0.5 m and 1 m, respectively. All instruments were calibrated three times (on 6 July, 5 August and 20 September, 2012) using black body during observation. 3. Data storage All the observation data were stored in excel.
GENG Liying, Jia Shuzhen, WANG Haibo, PENG Li, Dong Cunhui
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. 1, 2008. WiDAS, composed of four CCD cameras, one mid-infrared thermal imager (AGEMA 550), and one infrared thermal imager (S60), can acquire CCD, MIR and TIR band data. The simultaneous ground data included: (1) The radiative temperature of maize, wheat and the bare land in Yingke oasis maize field and Huazhaizi desert No. 1 plot 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). (2) The radiative temperature by the automatic thermometer (FOV: 10°; emissivity: 1.0; from Institute of Remote Sensing Applications), observing straight downwards at intervals of 1s in Yingke oasis maize field. Raw data, blackbody calibrated data and processed data were all archived in Excel format. (3) 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 Excel format. (4) The reflectance spectra by ASD in Yingke oasis maize field (350-2500nm , from BNU, the vertical canopy observation and the transect observation), and Huazhaizi desert No. 1 plot (350-2500nm , from Cold and Arid Regions Environmental and Engineering Research Institute, CAS, the NE-SW diagonal observation at intervals of 30m). The data included raw data (in .doc format), recorded data and the blackbody calibrated data (in Excel format). (5) 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. (6) The radiative temperature by the handheld radiometer in Yingke oasis maize field (from BNU, the vertical canopy observation, the transect observation and the diagonal observation), Yingke oasis wheat field (only for the transect temperature), and Huazhaizi desert No. 1 plot (the NE-SW diagonal observation). Besides, the maize radiative temperature and the physical temperature were also measured both by the handheld radiometer and the probe thermometer in the maize plot of 30m near the resort. The data included raw data (in .doc format), recorded data and the blackbody calibrated data (in Excel format). (7) Atmospheric parameters on the playroom roof at the resort by CE318 (produced by CIMEL in France). The underlying surface was mainly composed of crops and the forest (1526m high). 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) Narrow channel emissivity of the bare land and vegetation by the W-shaped determinator in Huazhaizi desert No. 1 plot. Four circumstances should be considered for emissivity, with the lid plus the au-plating board, the au-plating board only, the lid only and without both. Data were archived in Word.
CHEN Ling, HE Tao, REN Huazhong, REN Zhixing, YAN Guangkuo, ZHANG Wuming, XU Zhen, LI Xin, GE Yingchun, SHU Lele, JIANG Xi, HUANG Chunlin, GUANG Jie, LI Li, LIU Sihan, WANG Ying, XIN Xiaozhou, ZHANG Yang, ZHOU Chunyan, LIU Xiaocheng, TAO Xin, CHEN Shaohui, LIANG Wenguang, LI Xiaoyu, CHENG Zhanhui, Liu Liangyun, YANG Tianfu
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 May 30, 2008. WiDAS, composed of four CCD cameras, one mid-infrared thermal imager (AGEMA 550), and one infrared thermal imager (S60), can acquire CCD, MIR and TIR band data. The simultaneous ground data included: (1) The radiative temperature by the handheld radiometer (BNU) 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 diagonal observation). The data included raw data (in .doc format), recorded data and the blackbody calibrated data (in Excel format). (2) The component temperature of maize and wheat by the handheld radiometer in Yingke oasis maize field, Yingke 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 .doc format), recorded data and the blackbody calibrated data (in Excel format). (3) The radiative temperature of maize, wheat and the bare land in 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). (4) The radiative temperature and the canopy multi-angle radiative temperature by the fixed automatic thermometer (FOV: 10°; emissivity: 1.0), observing straight downwards at intervals of 1s in Yingke oasis maize field (2 instruments for maize canopy), Huazhaizi desert maize field (only one for maize canopy) and Huazhaizi desert No. 2 plot (two for reaumuria soongorica canopy and the bare land). The thermal infrared remote sensing calibration was carried out in the resort plot. Raw data, blackbody calibrated data and processed data were all archived in Excel format. (5) 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. (6) Reflectance spectra of Yingke oasis maize field (350-2500nm, from Institute of Remote Sensing Applications) and resort calibration site (350-2500nm, from Beijing Univeristy) by ASD (Analytical Sepctral Devices); BRDF by the self-made observation platform. Raw data were binary files direct from ASD (by ViewSpecPro), and pre-processed data on reflectance were in Excel format. (7) Atmospheric parameters at the resort calibration site 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) Soil moisture (0-40cm) by the cutting ring, the soil temperature by the thermocouple thermometer, roughness by the self-made roughness board and the camera in Huazhaizi desert No. 1 plot. Sample points were selected every 30m along the diagonals. Data were all archived in Excel format. (9) 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. (10) FPAR (Fraction of Photosynthetically Active Radiation) 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 Word. 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 of May 31.
CHAI Yuan, CHEN Ling, HE Tao, KANG Guoting, QIAN Yonggang, REN Huazhong, REN Zhixing, WANG Haoxing, ZHANG Wuming, ZOU Jie, GE Yingchun, SHU Lele, WANG Jianhua, XU Zhen, GUANG Jie, LIU Sihan, XIN Xiaozhou, ZHANG Yang, ZHOU Chunyan, LIU Xiaocheng, TAO Xin, LIANG Wenguang, WANG Dacheng, LI Xiaoyu, CHENG Zhanhui, YANG Tianfu, HUANG Bo, LI Shihua, LUO Zhen
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 Jul. 11, 2008. WiDAS, composed of four CCD cameras, one mid-infrared thermal imager (AGEMA 550), and one infrared thermal imager (S60), can acquire CCD, 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 details. 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) Radiative temperature of maize, wheat and the bare land (in Yingke oasis maize field), vegetation and the bare land (Huazhaizi desert No. 2 plot) by the thermal cameras at a height of 1.2m above the ground. Optical photos of the scene were also taken. Raw data (read by ThermaCAM Researcher 2001) was archived in IMG format and radiative files are stored in Excel format. . (3) Photosynthesis by LI6400 in Yingke oasis maize field, 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. (4) Ground object reflectance spectra in Yingke oasis maize field, Huazhaizi maize field, Huazhaizi desert No. 1 and 2 plots, by ASD FieldSpec (350～2500 nm) from Institute of Remote Sensing Applications (IRSA), CAS. Raw data were binary files direct from ASD (by ViewSpecPro), which were recorded daily in detail, and pre-processed data on reflectance were in .txt format. (5) The radiative temperature in Huazhaizi desert No. 2 plot by the handheld infrared thermometer (BNU and IRSA). Raw data, blackbody calibrated data and processed data (in Excel format) were all archived. (6) FPAR (Fraction of Photosynthetically Active Radiation) 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 Excel format. (7) The radiative temperature of the maize canopy by the automatic thermometer (FOV: 10°; emissivity: 0.95) mearsued at nadir with an time intervals of 1s in Huazhaizi desert maize field. Raw data, blackbody calibrated data and processed data were all archived as Excel files. (8) Maize albedo from two shortwave radiometer in Yingke oasis maize field. R =10H (R for FOV radius; H for the probe height). Data were archived in Excel format.
REN Huazhong, WANG Tianxing, YAN Guangkuo, LI Li, LI Hua, LIU Sihan, XIA Chuanfu, XIN Xiaozhou, ZHOU Chunyan, ZHOU Mengwei, YANG Guijun, LI Xiaoyu, CHENG Zhanhui, Liu Liangyun
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 dataset of the ground-based microwave radiometers and ground truth observations (multi-frequency, multi-polar multi-angle) for soil freeze/thaw cycle in the A'rou foci experimental area from Oct. 19 to 25, 2007, during the pre-observation period, X-band from Oct. 20 to 25, S-band from Oct. 20 to 25, K-band from Oct. 19 to 24, and Ka-band from Oct. 20 to 24, to be specific. The aims of the measurements were the effects of the soil freeze/thaw status on the microwave brightness temperatures. Those provide reliable ground data for improving and verifying microwave radiative transfer models and parameters retrieval of soil freeze/thaw status. Time-continuous ground observations synchronizing with the ground-based microwave radiometers including self-recording and manual measurements, were carried out in No. 1 quadrate of A'rou with dry natural grassland as the landscape. (1) self-recording observations: the soil temperatures at 0cm, 5cm, 10cm, 15cm and 20cm by the temperature probe from Oct. 21 to 25, 2007, and shallow layer soil moisture at 0-5cm, 5cm, 10cm, 15cm and 20cm by TDR from Oct. 19 to 21 2007. Both time interval of the observations were 5 minutes. (2) manual observations: the surface radiative temperature by the handheld infrared thermometer, the soil temperature at 0cm, 5cm, 10cm, 15cm and 20cm by the glass geothermometer, and the mean soil temperature from 0-5cm by the probe thermometer. The time interval of observations was 30 minutes from Oct. 19-21, 2007.
BAI Yunjie, CAO Yongpan, HAO Xiaohua, LI Hongyi, LI Xin, LI Zhe, QIN Chun, Wang Weizhen
The dataset of the ground-based microwave radiometers and ground truth observations for soil freeze/thaw cycle was obtained in the A'rou foci experimental area (N38º03.639'/E100º26.793'; 2998m) from May 5 to 8, 2008, S-band from Apr. 6 to 8, C-band from Apr. 7 to 8, K-band from Apr. 5 to 8, and Ka-band on Apr. 5, to be specific. The aims of the measurements were the effects of the soil freeze/thaw status on the microwave brightness temperatures. The observation site was bare land and the soil moisture was 30% after artificial irrigation. Observation items included the soil temperature at 5cm automatically (the time interval: 10m), the soil temperature at 5cm, 10cm, 20cm and 30cm by the probe thermometer (the time interval: 1h), and the soil moisture at 5cm, 10cm, 20cm and 30cm automatically (the time interval: 10m). Seven files were included, four ground-based microwave radiometers (S-band, C-band, K-band and Ka-band) observations, the automatic soil temperature, the manual soil temperature, and the automatic soil moisture, and the last three were archived in Excel format.
CAO Yongpan, CHE Tao, HAO Xiaohua, LI Zhe, Wang Weizhen, WU Yueru
The dataset of ground truth measurement synchronizing with the airborne WiDAS mission and Landsat TM was obtained in the Yingke oasis and Huazhaizi desert steppe foci experimental areas on Jul. 7, 2008. Observation items included: (1) the radiative temperature by the thermal camera (Institute of Remote Sensing Applications) of maize, wheat and the bare land of Yingke oasis maize field at a height of 1.2m above the ground. Optical photos of the scene were also taken. Raw data (read by ThermaCAM Researcher 2001) was archived in IMG format, and blackbody calibrated data and processed data were all archived as Excel files. (2) 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. (3) Reflectance spectra in Yingke oasis maize field by ASD FieldSpec (350-1603nm) from Institute of Remote Sensing Applications (CAS). The grey board and the black and white cloth were also used for calibration on the CCD camera. Raw data were binary files direct from ASD (by ViewSpecPro), and pre-processed data on reflectance were in Excel format. (4) the component temperature by the handheld radiometer in Yingke oasis maize 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 Word format), recorded data and the blackbody calibrated data (in Excel format). (5) the radiative temperature by the handheld radiometer (emissivity = 1.0) in Yingke oasis maize field (for the canopy mean temperature), Huazhaizi desert maize field (for the transect temperature), Zhangye airport (the black and white cloth for calibration) and Huazhaizi desert No. 2 plot (the diagonal radiative temperature and the radiative temperature of 30m*30m subplot). The component temperature was also measured. The data included raw data (in Word format), recorded data and the blackbody calibrated data (as Excel files). (6) The air temperature (°C) , the soy bean leaf temperature (°C) and the maize leaf temperature (°C) by SPAD (from Institute of Remote Sensing Applications (CAS)) in Yingke oasis maize field. Besides, spectrum, photosynthesis, fluorescence and chlorophyll were measured as well. (7) The leaf reflectance spectra ASD (serial number: 64831) and 50% grey board from Institute of Remote Sensing Applications (CAS). The spectral DN was changed into radiance based on the 50% grey board calibration data and calibration lamp data, which could further be transformed into Excel format. Moreover, the solar radiance=the reference board radiance/the reference reflectance. (8) The leaf fluorescence by ImagingPam from Beijing Academy of Agriculture and Forestry Sciences. YII = (Fm'-F)/Fm' was applied for caculation, F indicating fluorescence before saturating flash light, Fm' the maximum fluorescence before saturating flash light, and YII the quantum yield of photosystem II. Data were archived in pim and could be read by ImagingPam, which can be downloaded from http://www.zealquest.com. (9) The leaf photosynthesis by LI-6400. (10) The radiative temperature by the automatic thermometer (FOV: 10°; emissivity: 0.95), observing straight downwards at intervals of 1s in Yingke oasis maize field and Huazhaizi desert maize field. Raw data, blackbody calibrated data and processed data were all archived in Excel format. (11) FPAR (Fraction of Photosynthetically Active Radiation) 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. (12) Atmospheric parameters near Daman Water Management office 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, REN Huazhong, WANG Tianxing, YAN Guangkuo, HAO Xiaohua, WANG Shuguo, LI Li, LI Hua, LIU Sihan, SU Gaoli, XIA Chuanfu, XIN Xiaozhou, ZHOU Chunyan, ZHOU Mengwei, LI Xinhui, YU Fan, ZHU Xiaohua, YANG Guijun, CHENG Zhanhui, Liu Liangyun
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