Based on 11 well-acknowledged global-scale microwave remote sensing-based surface soil moisture products, and with 9 main quality impact factors of microwave-based soil moisture retrieval incorporated, we developed the Remote Sensing-based global Surface Soil Moisture dataset (RSSSM, 2003~2020) through a complicated neural network approach. The spatial resolution of RSSSM is 0.1°, while the temporal resolution is approximately 10 days. The original dataset covered 2003~2018, but now it has been updated to 2020. RSSSM dataset is outstanding in terms of temporal continuity, and has full spatial coverage except for snow, ice and water bodies. The comparison against the global-scale in-situ soil moisture measurements indicates that RSSSM has a higher spatial and temporal accuracy than most of the frequently-used global/regional long-term surface soil moisture datasets. In addition, although RSSSM is remote sensing based, without the incorporation of any precipitation data or records, its interannual variation generally conforms with that of precipitation (e.g., the GPM IMERG precipitation data) and Standardized Precipitation Evapotranspiration Index (SPEI). Moreover, RSSSM can also reflect the impact of human activities, e.g., urbanization, cropland irrigation and afforestation on soil moisture changes to some degree. The data is in ‘Tiff’ format, and the size after compression is 2.48 GB. The relevant data describing paper has been published in the Journal ‘Earth System Science Data’ in 2021.
CHEN Yongzhe, FENG Xiaoming, FU Bojie
Surface soil moisture (SSM) is a crucial parameter for understanding the hydrological process of our earth surface. Passive microwave (PM) technique has long been the primary choice for estimating SSM at satellite remote sensing scales, while on the other hand, the coarse resolution (usually >~10 km) of PM observations hampers its applications at finer scales. Although quantitative studies have been proposed for downscaling satellite PM-based SSM, very few products have been available to public that meet the qualification of 1-km resolution and daily revisit cycles under all-weather conditions. In this study, therefore, we have developed one such SSM product in China with all these characteristics. The product was generated through downscaling of AMSR-E and AMSR-2 based SSM at 36-km, covering all on-orbit time of the two radiometers during 2003-2019. MODIS optical reflectance data and daily thermal infrared land surface temperature (LST) that have been gap-filled for cloudy conditions were the primary data inputs of the downscaling model, in order to achieve the “all-weather” quality for the SSM downscaling outcome. Daily images from this developed SSM product have achieved quasi-complete coverage over the country during April-September. For other months, the national coverage percentage of the developed product is also greatly improved against the original daily PM observations. We evaluated the product against in situ soil moisture measurements from over 2000 professional meteorological and soil moisture observation stations, and found the accuracy of the product is stable for all weathers from clear sky to cloudy conditions, with station averages of the unbiased RMSE ranging from 0.053 vol to 0.056 vol. Moreover, the evaluation results also show that the developed product distinctly outperforms the widely known SMAP-Sentinel (Active-Passive microwave) combined SSM product at 1-km resolution. This indicates potential important benefits that can be brought by our developed product, on improvement of futural investigations related to hydrological processes, agricultural industry, water resource and environment management.
SONG Peilin, ZHANG Yongqiang
This biophysical permafrost zonation map was produced using a rule-based GIS model that integrated a new permafrost extent, climate conditions, vegetation structure, soil and topographic conditions, as well as a yedoma map. Different from the previous maps, permafrost in this map is classified into five types: climate-driven, climate-driven/ecosystem-modified, climate-driven/ecosystem protected, ecosystem-driven, and ecosystem-protected. Excluding glaciers and lakes, the areas of these five types in the Northern Hemisphere are 3.66×106 km2, 8.06×106 km2, 0.62×106 km2, 5.79×106 km2, and 1.63×106 km2, respectively. 81% of the permafrost regions in the Northern Hemisphere are modified, driven, or protected by ecosystems, indicating the dominant role of ecosystems in permafrost stability in the Northern Hemisphere. Permafrost driven solely by climate occupies 19% of permafrost regions, mainly in High Arctic and high mountains areas, such as the Qinghai-Tibet Plateau.
RAN Youhua, M. Torre Jorgenson, LI Xin, JIN Huijun, Wu Tonghua, Li Ren, CHENG Guodong
Agricultural irrigation consumes a large amount of available freshwater resources and is the most immediate human disturbance to the natural water cycle process, with accelerated regional water cycles accompanied by cooling effects. Therefore, estimating irrigation water use (IWU) is important for exploring the impact of human activities on the natural water cycle, quantifying water resources budget, and optimizing agricultural water management. However, the current irrigation data are mainly based on the survey statistics, which is scattered and lacks uniformity, and cannot meet the demand for estimating the spatial and temporal changes of IWU. The Global Irrigation Water Use Estimation Dataset (2011-2018) is calculated by the satellite soil moisture, precipitation, vegetation index, and meteorological data (such as incoming radiation and temperature) based on the principle of soil water balance. The framework of IWU estimation in this study coupled the remotely sensed evapotranspiration process module and the data-model fusion algorithm based on differential evolution. The IWU estimates provided from this dataset have small bias at different spatial scales (e.g., regional, state/province and national) compared to traditional discrete survey statistics, such as at Chinese provinces for 2015 (bias = −3.10 km^3), at U.S. states for 2013 (bias = −0.42 km^3), and at various FAO countries (bias = −10.84 km^3). Also, the ensemble IWU estimates show lower uncertainty compared to the results derived from individual precipitation and soil moisture satellite products. The dataset is unified using a global geographic latitude and longitude grid, with associated metadata stored in corresponding NetCDF file. The spatial resolution is about 25 km, the time resolution is monthly, and the time span is 2011-2018. This dataset will help to quantitatively assess the spatial and temporal patterns of agricultural irrigation water use during the historical period and support scientific agricultural water management.
ZHANG Kun, LI Xin, ZHENG Donghai, ZHANG Ling, ZHU Gaofeng
The long-term evolution of lakes on the Tibetan Plateau (TP) could be observed from Landsat series of satellite data since the 1970s. However, the seasonal cycles of lakes on the TP have received little attention due to high cloud contamination of the commonly-used optical images. In this study, for the first time, the seasonal cycle of lakes on the TP were detected using Sentinel-1 Synthetic Aperture Radar (SAR) data with a high repeat cycle. A total of approximately 6000 Level-1 scenes were obtained that covered all large lakes (> 50 km2) in the study area. The images were extracted from stripmap (SM) and interferometric wide swath (IW) modes that had a pixel spacing of 40 m in the range and azimuth directions. The lake boundaries extracted from Sentinel-1 data using the algorithm developed in this study were in good agreement with in-situ measurements of lake shoreline, lake outlines delineated from the corresponding Landsat images in 2015 and lake levels for Qinghai Lake. Upon analysis, it was found that the seasonal cycles of lakes exhibited drastically different patterns across the TP. For example, large size lakes (> 100 km2) reached their peaks in August−September while lakes with areas of 50−100 km2 reached their peaks in early June−July. The peaks of seasonal cycles for endorheic lakes were more pronounced than those for exorheic lakes with flat peaks, and glacier-fed lakes with additional supplies of water exhibited delayed peaks in their seasonal cycles relative to those of non-glacier-fed lakes. Large-scale atmospheric circulation systems, such as the westerlies, Indian summer monsoon, transition in between, and East Asian summer monsoon, were also found to affect the seasonal cycles of lakes. The results of this study suggest that Sentinel-1 SAR data are a powerful tool that can be used to fill gaps in intra-annual lake observations.
ZHANG Yu, ZHANG Guoqing
The Antarctic ice sheet elevation data were generated from radar altimeter data (Envisat RA-2) and lidar data (ICESat/GLAS). To improve the accuracy of the ICESat/GLAS data, five different quality control indicators were used to process the GLAS data, filtering out 8.36% unqualified data. These five quality control indicators were used to eliminate satellite location error, atmospheric forward scattering, saturation and cloud effects. At the same time, dry and wet tropospheric, correction, solid tide and extreme tide corrections were performed on the Envisat RA-2 data. For the two different elevation data, an elevation relative correction method based on the geometric intersection of Envisat RA-2 and GLAS data spot footprints was proposed, which was used to analyze the point pairs of GLAS footprints and Envisat RA-2 data center points, establish the correlation between the height difference of these intersection points (GLAS-RA-2) and the roughness of the terrain relief, and perform the relative correction of the Envisat RA-2 data to the point pairs with stable correlation. By analyzing the altimetry density in different areas of the Antarctic ice sheet, the final DEM resolution was determined to be 1000 meters. Considering the differences between the Prydz Bay and the inland regions of the Antarctic, the Antarctic ice sheet was divided into 16 sections. The best interpolation model and parameters were determined by semivariogram analysis, and the Antarctic ice sheet elevation data with a resolution of 1000 meters were generated by the Kriging interpolation method. The new Antarctic DEM was verified by two kinds of airborne lidar data and GPS data measured by multiple Antarctic expeditions of China. The results showed that the differences between the new DEM and the measured data ranged from 3.21 to 27.84 meters, and the error distribution was closely related to the slope.
HUANG Huabin
The proportion data set of daily cloudless MODIS snow cover area in babaohe river basin (2008.1.1-2014.6.1) was obtained after cloud removal processing using a cloud removal algorithm based on cubic spline function interpolation on the basis of daily cloudless MODIS snow cover product-mod10a1 (tang zhiguang, 2013). This data set adopts the projection method of UTM (horizontal axis isometric cutting cylinder), with a spatial resolution of 500m, and provides Daily Snow Albedo daily-sad results for the babao river basin.The data set is a daily file from January 1, 2008 to June 1, 2014.Each file is the snow albedo result of the day, with a value of 0-100 (%), is the ENVI standard file, and the naming rule is: mod10a1.ayyyyddd_h25v05_snow_sad_grid_2d_reproj_babaohe_nocloud.img, where YYYY represents the year, DDD stands for Julian day (001-365/366).The file can be opened directly with ENVI or ARCMAP software. The original MODIS snow cover data products processed by declouding are derived from MOD10A1 products processed by the us national snow and ice data center (NSIDC). This data set is in HDF format and USES sinusoidal projection. The attributes of the cloud-free MODIS albedo data set (2008.1.1-2014.1.1) in babaohe river basin are composed of the spatial and temporal resolution, projection information and data format of the dataset.
WANG Jian, PAN Haizhu
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 measurements synchronizing with Envisat ASAR was obtained in No. 1 and 2 quadrates of the Biandukou foci experimental area on Oct. 17, 2007 during the pre-observation period. The ASAR 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: the soil temperature , volumetric soil moisture (cm^3/cm^3), soil salinity (s/m), soil conductivity (s/m) by the Hydra probe, the surface radiative temperature by the handheld infrared thermometer, gravimetric soil moisture, volumetric soil moisture, and soil bulk density by drying soil samples from the cutting ring (100cm^3). Meanwhile, vegetation parameters as height, coverage and water content were also observed. Those provide reliable ground data for the development and validation of soil moisture, soil freeze/thaw algorithms and the forward model from active remote sensing approaches.
BAI Yunjie, CAO Yongpan, LI Xin, Wang Weizhen, WANG Xufeng
The dataset of ground truth measurement synchronizing with EO-1 Hyperion was obtained in the Yingke oasis and Huazhaizi desert steppe foci experimental areas on May 25, 2008. Observation items included: (1) Atmospheric parameters on the ICBC resort office roof by CE318 (produced by CIMEL in France). The total optical depth, aerosol optical depth, Rayleigh scattering coefficient, column water vapor in 936 nm, particle size spectrum and phase function were then retrieved from these observations. The optical depth in 1020nm, 936nm, 870nm, 670nm and 440nm were all acquired by CE318. Those data include the raw data in k7 format and can be opened by ASTPWin. ReadMe.txt is attached for detail. Processed data (after retrieval of the raw data) in Excel format are on optical depth, rayleigh scattering, aerosol optical depth, the horizontal visibility, the near surface air temperature, the solar azimuth, zenith, solar distance correlation factors, and air column mass number. (2) Ground object reflectance spectra f new-born rape and the bare land in Biandukou foci experimental area by ASD FieldSpec (350~2500 nm) from BNU. Raw data were binary files direct from ASD (by ViewSpecPro), and pre-processed data on reflectance were in Excel format. (3) Soil moisture (0-40cm) by the cutting ring and the soil temperature (0-40cm) by the thermocouple in Huazhaizi desert No. 1 plot and the windbreak forest; and soil moisture and the soil temperature (0-100cm) in Yingke oasis maize field. Data were archived in Excel format. (4) LAI. The maximum leaf length and width of each alfalfa and barley were measured. Data were archived in Excel format. (5) Coverage of maize and wheat in Yingke oasis maize field, of vegetation (Reaumuria soongorica) in Huazhaizi desert No. 1 and 2 plots by the self-made coverage instrument and the camera (2.5m-3.5m above the ground). Based on the length of the measuring tape and the bamboo pole, the size of the photo can be decided GPS date were also collected and the technology LAB was applied to retrieve the coverage of the green vegetation. Besides, such related information as surroundings environment was also recorded. Data included the primarily measured image and final fraction of vegetation coverage.
CHEN Ling, QIAN Yonggang, REN Huazhong, WANG Haoxing, YAN Guangkuo, GE Yingchun, SHU Lele, WANG Jianhua, XU Zhen, GUANG Jie, LI Li, XIN Xiaozhou, ZHANG Yang, ZHOU Chunyan, TAO Xin, YAN Binyan, YAO Yanjuan
The dataset of ground truth measurement synchronizing with Envisat ASAR was obtained in No. 1, 2 and 3 quadrates of the A'rou foci experimental area on Jun. 19, 2008. GPR observations were also carried out in one sampling strip. The Envisat ASAR data were in AP mode and VV/VH polarization combinations, and the overpass time was approximately at 11:17 BJT. Simultaneous with the satellite overpass, numerous ground data were collected, the soil temperature, soil volumetric moisture, the loss tangent, soil conductivity, and the real part and the imaginary part of soil complex permittivity were acquired by the POGO soil sensor, and the mean soil temperature from 0-5cm by the probe thermometer. Those provide reliable ground data for retrieval and validation of the surface temperature and evapotranspiration from remote sensing approaches. Four files were included, ASAR data, No. 1, 2 and 3 quadrates data.
CAO Yongpan, GE Chunmei, HAN Xujun,
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 Envisat ASAR was obtained in in No. 2 and 3 quadrates of the A'rou foci experimental areas on Mar. 15, 2008. The Envisat ASAR data were in AP mode and VV/VH polarization combinations, and the overpass time was approximately at 11:35 BJT. The quadrates were divided into 4×4 subsites, with each one spanning a 30×30 m2 plot. Only corner points of each subsite were chosen for observations. In No. 2 quadrate, simultaneous with the satellite overpass, numerous ground data were collected, the soil temperature, soil volumetric moisture, the loss tangent, soil conductivity, and the real part and the imaginary part of soil complex permittivity by the POGO soil sensor, the mean soil temperature from 0-5cm by the probe thermometer, the surface radiative temperature measured three times by the hand-held infrared thermometer, soil gravimetric moisture, volumetric moisture, and soil bulk density after drying by the cutting ring (100cm^3). In No. 3 quadrate, simultaneous with the satellite overpass, numerous ground data were collected, the soil temperature, soil volumetric moisture, the loss tangent, soil conductivity, and the real part and the imaginary part of soil complex permittivity by the POGO soil sensor, soil volumetric moisture by ML2X, the mean soil temperature from 0-5cm by the probe thermometer, the surface radiative temperature measured three times by the hand-held infrared thermometer, soil gravimetric moisture, volumetric moisture, and soil bulk density after drying by the cutting ring (100cm^3). Surface roughness was detailed in the "WATER: Surface roughness dataset in the A'rou foci experimental area". Besides, GPR (Ground Penetration Radar) observations were also carried out in No. 1 quadrate of A'rou. Those provide reliable ground data for retrieval and validation of soil moisture and freeze/thaw status from active remote sensing approaches.
CAO Yongpan, GU Juan, HAN Xujun, LI Zhe, Wang Weizhen, WU Yueru, LI Hua, YU Meiyan, ZHAO Jin, PATRICK Klenk, YUAN Xiaolong
The dataset of ground truth measurements synchronizing with Envisat ASAR was obtained in No. 1 and 2 quadrates of the Biandukou foci experimental area on Oct. 18, 2007, during the pre-observation period. The ASAR data were in AP mode and VV/VH polarization combinations, and the overpass time was approximately at 11:17 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: the soil temperature , volumetric soil moisture (cm^3/cm^3), soil salinity (s/m), soil conductivity (s/m) by the Hydra probe, the surface radiative temperature by the handheld infrared thermometer, gravimetric soil moisture, volumetric soil moisture, and soil bulk density by drying soil samples from the cutting ring (100cm^3). Meanwhile, vegetation parameters as height, coverage and water content were also observed. Those provide reliable ground data for the development and validation of soil moisture, soil freeze/thaw algorithms and the forward model from active remote sensing approaches.
BAI Yunjie, CAO Yongpan, WANG Jian, Wang Weizhen, WANG Xufeng, JIN Rui, Qu Yonghua, ZHOU Hongmin
The dataset of ground truth measurements synchronizing with Envisat ASAR and ALOS PALSAR was obtained in the Linze station foci experimental area on May 24, 2008. The data were in AP mode and VV/VH polarization combinations, and the overpass time was approximately at 11:34 BJT. Observation items included: (1) soil moisture (0-5cm) measured once by cutting ring method at corner points of the 40 subplots of the west-east desert transit zone strip, one time by cutting ring method in nine subplots of the north-south desert transit zone, strip and once by the cutting ring and three times by ML2X Soil Moisture Tachometer in the center points of nine subplots of Wulidun farmland quadrates . The preprocessed soil volumetric moisture data were archived as Excel files. (2) surface radiative temperature by measured two handheld infrared thermometer (5# and 6# from Cold and Arid Regions Environmental and Engineering Research Institute which were both calibrated) in 40 subplots of the west-east desert transit zone strip (repeated 14-30 times each), and nine subplots of the north-south desert transit zone strip (repeated 12-30 times). There are 34 sample points in total and each was repeated three times synchronizing with the airplane. Photos were taken. Data were archived as Excel files. (3) LAI, the plant height and the spacing measured by the ruler and the set square in Wulidun farmland quadrates and Linze station quadrates. Part of the samples were also measured by LI-3100. Data were archived as Excel files. See the metadata record “WATER: Dataset of setting of the sampling plots and stripes in the Linze station foci experimental area” for more information of the quadrate locations.
BAI Yanfen, DING Songchuang, PAN Xiaoduo, WANG Yang, ZHU Shijie, LI Jing, XIAO Zhiqiang, SUN Jinxia
The dataset of ground truth measurements synchronizing with Envisat ASAR was obtained in the saline plot B, the alfalfa plot D and the barley plot E of the Linze grassland foci experimental area on May 24, 2008. The data were in AP mode and VV/VH polarization combinations, and the overpass time was approximately at 11:34 BJT. The quadrate was divided into 6×6 subsites, with each one spanning a 120×120 m2 plot. Corner points were chosen. Simultaneous with the satellite overpass, numerous ground data were collected, soil gravimetric moisture, volumetric moisture, and soil bulk density after drying by the cutting ring (100cm^3), the mean soil temperature from 0-5cm by the probe thermometer, and the land surface radiative temperature measured three times by the hand-held infrared thermometer in plot B; soil moisture, soil conductivity, the soil temperature, and the real part of soil complex permittivity by WET, the mean soil temperature from 0-5cm by the probe thermometer, and the land surface radiative temperature measured three times by the hand-held infrared thermometer in plot D; the soil temperature, soil moisture, the loss tangent, soil conductivity, the real part and the imaginary part of soil complex permittivity by the POGO soil sensor, the mean soil temperature from 0-5cm by the probe thermometer, and the land surface radiative temperature measured three times by the hand-held infrared thermometer in plot E. Data were archived in Excel file. Those provide reliable ground data for retrieval and validation of soil moisture and alinity content with active microwave remote sensing approaches. See WATER: Dataset of setting of the sampling plots and stripes in the Linze station foci experimental area for more information.
CHAO Zhenhua, HU Xiaoli, LIANG Ji, Wang Weizhen, LIU Zhaoyan, TANG Bohui, HAN Hui, WANG Xiaoping
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. 18, 2007 during the pre-observation period. The data were in AP mode and VV/VH polarization combinations, and the overpass time was approximately at 11:17 BJT (Beijing Time). 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 (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 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 measurement synchronizing with Envisat ASAR was obtained in No. 1, 2 and 3 quadrates of the A'rou foci experimental area on Jul. 5 and Jul. 6, 2008. The Envisat ASAR data were in AP mode and VV/VH polarization combinations, and the overpass time was approximately at 11:14 BJT. The quadrates were divided into 4×4 subsites, with each one spanning a 30×30 m2 plot. Observation items included: (1) the quadrate investigation in No. 2 and 3 quadrates: GPS by GARMIN GPS 76, plant species by manual cognition, the plant number by manual work, the height by the measuring tape repeated 4-5 times, phenology by manual work, the coverage by manual work (compartmentalizing 0.5m×0.5m into 100 to see the percentage the stellera takes) and the chlorophyll content by SPAD 502. (2) spectrum of stellera and pasture by ASD FieldSpec (350～2 500 nm), with 20% reference board. The preprocessed canopy spectrum was archived. (3) BRDF by ASD FieldSpec (350～2 500 nm), with 20% reference board. The processed reflectance and transmittivity were archived as .txt files. (4) photosynthesis of stellera and pasture by LI-6400. The data were archived in Excel format. (5) soil moisture by WET soil moisture tachometer. Acquisition time, soil moisture (%vol), Ecp (ms/m), Tmp Eb and Ecb (ms/m) of 25 corner points were archived. (6) the soil temperature by the handheld infrared thermometer. Acquisition time, the soil temperature measured three times and the land cover types were archived. The data included the canopy reflectance on Jul. 5 and 6, photosynthesis on Jul. 5 and 6, BRDF on Jul. 5, photos on Jul. 5, the infrared land surface temperature and soil moisture by WET on Jul. 5, biomass on Jul. 5 and the surface temperature along No. 3 flight on Jul. 6.
DING Songchuang, GE Yingchun, LI Hongyi, MA Mingguo, Qian Jinbo, WANG Yang, YU Yingjie, LIU Sihan
The dataset of ground truth measurements synchronizing with Envisat ASAR was obtained in No.1 (freeze/thaw status), No. 2 (snow parameters) and No. 3 (freeze/thaw status) quadrates of the A'rou foci experimental areas on Mar. 12, 2008. The Envisat ASAR data were in AP mode and VV/VH polarization combinations, and the overpass time was approximately at 11:29 BJT. The quadrates were divided into 4×4 subsites, with each one spanning a 30×30 m2 plot. Center and corner points of each subsite were chosen for all observations except for the cutting ring measurements which only observed the center points. In No. 1 quadrate, numerous ground data were collected, the soil temperature, soil volumetric moisture, the loss tangent, soil conductivity, and the real part and the imaginary part of soil complex permittivity by the POGO soil sensor, soil volumetric moisture by ML2X, the soil volumetric moisture profile (10cm, 20cm, 30cm, 40cm, 60cm and 100cm) by PR2, the mean soil temperature from 0-5cm by the probe thermometer, soil gravimetric moisture, volumetric moisture, and soil bulk density after drying by the cutting ring (100cm^3). In No. 2 quadrate, simultaneous with ASAR, snow parameters were measured, the snow surface temperature by the thermal infrared probe, the snow layer temperature by the probe thermometer, the snow grain size by the handheld microscope, snow density by the aluminum case, the snow surface temperature and the snow-soil interface temperature by the thermal infrared probe, snow spectrum by ASD, and snow albedo by the total radiometer. In No. 3 quadrate soil volumetric moisture, soil conductivity, the soil temperature, and the real part of soil complex permittivity were measured by WET, the mean soil temperature from 0-5cm by the probe thermometer (5# and 7#), the surface radiative temperature by the hand-held infrared thermometer (5#), and soil gravimetric moisture, volumetric moisture, and soil bulk density after drying by the cutting ring (100cm^3). Surface roughness was detailed in the "WATER: Surface roughness dataset in the A'rou foci experimental area". Besides, GPR (Ground Penetration Radar) observations were also carried out in No. 1 quadrate of A'rou. Those provide reliable ground data for retrieval and verification of soil moisture and freeze/thaw status from active remote sensing approaches.
BAI Yanfen, CAO Yongpan, GE Chunmei, GU Juan, HAN Xujun, LI Zhe, LIANG Ji, MA Mingguo, SHU Lele, WANG Jianhua, WANG Xufeng, WU Yueru, XU Zhen, QU Wei, CHANG Cun, DOU Yan, MA Zhongguo, YU Meiyan, ZHAO Jin, JIANG Tenglong, XIAO Pengfeng , LIU Yan, ZHANG Pu, PATRICK Klenk, YUAN Xiaolong
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