The dataset of airborne imaging spectrometer (OMIS-II) mission was obtained in the Dayekou watershed flight zone on Jun. 4, 2008. Data after radiometric correction and calibration and geometric approximate correction were released. The flying time of each route was as follows: {| ! id ! flight ! file ! starttime ! lat ! long ! alt ! image linage ! endtime ! lat ! long ! alt |- | 1 || 4-13 || 2008-06-04_13-19-02_DATA.BSQ || 13:23:45 || 38.542 || 100.382 || 4624.5 || 3125 || 13:27:13 || 38.493 || 100.230 || 4617.5 |- | 2 || 4-12 || 2008-06-04_13-30-55_DATA.BSQ || 13:31:21 || 38.494 || 100.214 || 4644.9 || 2912 || 13:34:35 || 38.543 || 100.370 || 4626.3 |- | 3 || 4-11 || 2008-06-04_13-38-17_DATA.BSQ || 13:39:14 || 38.551|| 100.381 || 4616.2 || 3051 || 13:42:38 || 38.500 || 100.221 || 4656.5 |- | 4 || 4-10 || 2008-06-04_13-46-20_DATA.BSQ || 13:47:09 || 38.502 || 100.212 || 4640.3 || 2866 || 13:50:20 || 38.550 || 100.365 || 4633.4 |- | 5 || 4-9 || 2008-06-04_13-54-02_DATA.BSQ || 13:55:01 || 38.558 || 100.374 || 4644.3 || 2897 || 13:58:14 || 38.511 || 100.223 || 4628.4 |- | 6 || 4-8 || 2008-06-04_14-01-56_DATA.BSQ || 14:01:51 || 38.511 || 100.209 || 4644.6 || 2751 || 14:04:54 || 38.558 || 100.359 || 4655.7 |- | 7 || 4-7 || 2008-06-04_14-08-36_DATA.BSQ || 14:09:28 || 38.568 || 100.373 || 4630.5 || 2995 || 14:12:48 || 38.519 || 100.218 || 4642.8 |- | 8 || 4-6 || 2008-06-04_14-16-30_DATA.BSQ || 14:16:38 || 38.521 || 100.209 || 4650.1 || 2705 || 14:19:38 || 38.568 || 100.357 || 4652.9 |- | 9 || 4-5 || 2008-06-04_14-23-20_DATA.BSQ || 14:24:25 || 38.576 || 100.367 || 4649.0 || 2958 || 14:27:42 || 38.526 || 100.210 || 4673.5 |- | 10 || 4-4 || 2008-06-04_14-31-24_DATA.BSQ || 14:31:09 || 38.527 || 100.199 || 4631.3 || 2817 || 14:34:17 || 38.576 || 100.353 || 4641.7 |- | 11 || 4-3 || 2008-06-04_14-37-59_DATA.BSQ || 14:39:55 || 38.579 || 100.346 || 4599.6 || 2555 || 14:42:46 || 38.536 || 100.210 || 4612.0 |- | 12 || 4-2 || 2008-06-04_14-46-28_DATA.BSQ || 14:46:20 || 38.535 || 100.194 || 4620.5 || 2869 || 14:49:31 || 38.583 || 100.345 || 4639.2 |- | 13 || 4-1 || 2008-06-04_14-53-13_DATA.BSQ || 14:55:36 || 38.594 || 100.364 || 4621.2 || 3018 || 14:58:58 || 38.544 || 100.206 || 4606.9 |}
Liu Liangyun, LI Xin, MA Mingguo
The dateset of the ground-based RPG-8CH-DP microwave radiometer observations was obtained in the Biandukou foci experimental area from Mar. 14 to 17, 2008. Observation items included the brightness temperature by the ground-based microwave radiometer (18.7GHz and 36.5GHz), the soil temperature by the thermal resistor, the gravimetric soil moisture by the microwave drying method, and the surface roughness by the grid board. The wheat stubble land (38°15'44.13"N, 100°55'35.34"E) was chosen for continuous observations from 11:00 to 24:00 on Mar. 14, with the incidence 20°-70° and the step length 5°. The rape stubble land (38°15'23.17"N, 100°58'37.84"E) was chosen for continuous observations from 10:00 to 21:30 on Mar. 16, with the incidence 20°-70° and the step length 5°. The deep plowed land (38°18'8.28"N, 101° 3'27.22"E) was chosen for short time observations from 17:26 to 19:20 on Mar. 17, with the azimuth angle 240°-300° and the step length 10°, the incidence 40°-70° and the step length 5°. The brightness temperature was archived as .BRT and .txt files (the ASCII format). Each row in .txt was listed by year, month, date, hour, minute, second, 6.925GHz (h), 6.925GHz (v), 10.65GHz (h), 10.65GHz (v) , 18.7GHz (h), 18.7GHz (v), 36.5GHz (h), 36.5GHz (v), the elevation angle, and the azimuth angle. Values for 6.925GHz and 10.65GHz were zero due to malfunction. The roughness data were obtained by the grid board and the camera and the RMS height (cm) and correlation length (cm) were also calculated and archived, which could be opened by Notepad or Microsoft Office Word. Those provide reliable reference for the roughness of the same land cover type. The gravimetric soil moisture (soil samples from 0-1cm, 1-3cm and 3-5cm) was measured by the microwave drying method. The file can be opened by Microsoft Office Word. The shallow layer soil moisture was measured by hydra prob from 12:00 to 17:00 on 14 and by the Hydra probe (straight downward for 0-5cm) and HH2 (level into the soil surface) on 16. The surface temperature was measured by the thermal resistor. The file can be opened by Microsoft Office Word. Four data files were included, the brightness temperature, the surface temperature, the soil moisture and the surface roughness.
CHANG Sheng, LIANG Xingtao, PAN Jinmei, PENG Danqing, ZHANG Yongpan, ZHANG Zhiyu, ZHAO Shaojie, Zhao Tianjie, ZHENG Yue, YIN Xiaojun, ZHANG Zhiyu
The dataset of airborne L-band microwave radiometer and thermal imager mission was obtained in the Binggou-A'rou flight zone in the afternoon of Apr. 1, 2008. The frequency of L bands was 1.4 GHz with back sight of 35 degree and dual polarization (H&V) was acquired. The plane took off at Zhangye airport at 12:48 (BJT) and landed at 16:35 along the scheduled lines at the altitude about 5000m and speed about 260km/hr.. The raw data include microwave radiometer (L) data, thermal imager data (7.5-13 um; FOV: 24×18º) and GPS data; the first were instantaneous non-imaging observation recorded in text, which could be converted into brightness temperatures according to the caliberation coefficients (filed with raw data together), and the third are aircraft longitude, latitude and attitude. Moreover, based on the respective real-time clock log, observations by the microwave radiometer and GPS can be integrated to offer coordinates matching for the former. Yaw, flip, and pitch motions of aircraft were ignored due to the low resolution of microwave radiometer observations. Observation information can also be rasterized, as required, after calibration and coordinates matching. L band resolution (x) and footprint can be approximately estimated as x=0.3H (H is relative flight height). The thermal imager was 320*240 pixels and with FOV of 24×18º. The thermal imager data were stored in binary format with a text header file. The recorded value was brightness temperature at sensor with scale and gain parameter recorded in the header file. And the thermal images were not geometrically corrected because there were gaps between sequential images.
WANG Shuguo, WANG Xufeng, CHE Tao, ZHAO Kai, JIN Jinan, XIAO Qing, Liu Qiang
The global typhoon path data set contains the data of 29 typhoon path points in the Northwest Pacific in 2018, including time, longitude and latitude, central air pressure, wind speed and wind force, future direction, future speed, wind force level and other indicators; the data comes from the typhoon network of the Central Meteorological Station (http://typhone.nmc.cn/web.html), using Python to grab the typhoon path data published on the web page, In addition, the captured Excel data table is sorted into ShapeFile form, and each path point is given wind power level according to the wind power rating standard of typhoon; It can be applied to the analysis of the characteristics and influence of the movement of typhoon path points, wind speed and wind force.
CHEN Yiting, YANG Hua, WU Jianjun, ZHOU Hongmin
The MODIS land cover type product is a data classification product (MOD12Q1) with different classification schemes for land cover features extracted from Terra data each year. These data are generated by reprojecting the standard MODIS land cover product MOD12Q1 to geographic coordinates with a spatial resolution of one-half degree. The basic land cover classification comprises the 17 types defined by the International Geosphere Biosphere Programme (IGBP): 11 types of natural vegetation classification, 3 types of land use and land inlays, and 3 types of nonvegetation land classification. It covers a longitude range of -180-180 degrees and a latitude range of -64-84 degrees. The data are in GeoTIFF format. This data are free to use, and the copyright belongs to the University of Maryland Department of Geography and NASA.
Channan, S, Channan, XU Xiyan
The dataset of surface roughness was obtained at the super site (100m×100m, pure Qinghai spruce) around the Dayekou Guantan forest station. 25 corner points and 16 center points were collected and each point was measured twice and photos were taken. With the roughness plate 110cm long and the measuring points distance 1cm, the samples were collected along the strip from south to north and from east to west, respectively. The photos were processed using ArcView software; and after geometric correction, surface height standard deviation (cm) and correlation length (cm) could be acquired based on the formula listed on pages 234-236, Microwave Remote Sensing, Vol. II. The roughness data were initialized by the sample name, which was followed by the serial number, the name of the file, standard deviation and correlation length. Each .txt file is matched with one sample photo and standard deviation and correlation length represent the roughness. In addition, the length of 101 radius is also included for further checking. Those provide reliable ground data for improving and verifying the remote sensing algorithms.
BAI Yunjie, CAO Yongpan, CHE Tao, CHEN Ling, Qu Yonghua, ZHOU Hongmin
This dataset contains Doppler Weather Radar data from the Zhangye National Climate Observatory during the Watershed Allied Telemetry Experimental Research from 2008-03-08 to 2008-06-30. The latitude and longitude of the observation point are 100°16.8'E, 39°05.094'N; the altitude is 1378m. The main observation items are: rainfall, cloud physics, weather radar, etc.
Zhangye National Climate Observatory
In the mid-latitude region of Asia, the southeastern region is humid and affected by monsoon circulation (thus, it is referred to as the monsoon region), and the inland region is arid and controlled by the other circulation patterns (these areas include the cold and arid regions in the northern Tibetan Plateau, referred to as the westerly region). Based on the generalization of the climate change records published in recent years, the westerly region was humid in the mid-late Holocene, which was significantly different from the pattern of the Asian monsoon in the early-middle Holocene. In the past few millennia, the westerly region was arid during the Medieval Warm Period but relatively humid during the Little Ice Age. In contrast, the oxygen isotope records derived from a stalagmite in the Wanxiang Karst Cave showed that the monsoon precipitation was high in the Medieval Warm Period and low during the Little Ice Age. In the last century, especially in the last 50 years, the humidity of the arid regions in the northwest has increased, while the eastern areas of northwestern and northern China affected by the monsoon have become more arid. Moreover, in the northern and southern parts of the Tibetan Plateau, which are affected by the westerlies and the monsoon, respectively, the precipitation changes on the interdecadal and century scales have also shown an inverse phase. Based on these findings, we propose that the control zone of the westerly belt in central Asia has different humidity (precipitation) variation patterns than the monsoon region on every time scale (from millennial to interdecadal) in the modern interglacial period. The integrated research project on Holocene climate change in the arid and semi-arid regions of western China was a major research component of the project Environmental and Ecological Science for West China, which was funded by the National Natural Science Foundation of China. The leading executive of the project was Professor Fahu Chen from Lanzhou University. The project ran from January 2006 to December 2009. The data collected by the project include the following: 1. The integrate humidity data over the Holocene in the arid regions of Central-East Asia and 12 lakes (11000-0 cal yr BP): including Lake Van, Aral Sea, Issyk-Kul, Ulunguhai Lake, Bosten Lake, Barkol Lake, Bayan Nuur, Telmen Lake, Hovsgol Nuur, Juyan Lake, Gun Nuur and Hulun Nuur. 2. The integrated humidity data over the past millennium in the arid regions of Central-East Asia and at five research sites (1000-2000): including Aral Sea, Guliya, Bosten Lake, Sugan Lake, and the Badain Juran desert. Data format: excel table.
CHEN Fahu
The dataset of BRDF observations was obtained in the Yingke oasis and Huazhaizi desert steppe foci experimental areas. Reflectance could be got based on R = (DN1/DN0)×R0, DN1 indicating DN of the item, R0 and DN0 the reflectance and DN of the grey board. Synchronizing with WiDAS and OMIS-II, the ground observations on reflectance (-60°~60° at intervals of 10°) of maize and wheat were carried out with ASD (FOV: 25°) and the self-made observation platform (maximum height: 5m) on May 30, Jun. 9, 14, 20, 22, 26 and 30, and Jul. 1, 2008. Raw data, recorded data and processed BRDF were archived in Excel format.
CHEN Ling, REN Huazhong, WANG Haoxing, YAN Guangkuo, ZHANG Wuming, XIN Xiaozhou, ZHANG Yang, FAN Wenjie, TAO Xin
The dataset of Land Surface Temperature (LST) observations was obtained in the Yingke oasis and Huazhaizi desert steppe foci experimental areas. (1) The time-continuous surface radiative temperature by the automatic thermometer (FOV: 10°; six from BNU with emissivity 0.95; two from Institute of Remote Sensing Applications with emissivity 1.00, observing at nadir at an intervals of one second. The maize canopy, the bare land and the wheat canopy in Yingke oasis maize field, the wheat canopy in Yingke oasis wheat field, the maize canopy in Huazhaizi desert maize field, vegetation and the bare land in Huazhaizi desert No. 1 and 2 plots and three intensive plots (Huazhaizi desert No. 3 plot, the barley field and the maize field near the resort) were measured on May 20, 24, 28, 30 and 31, Jun. 1, 3, 4, 16, 29 and 30, Jul. 1, 7, 9 and 11, 2008. The dataset of ground truth measurement was synchronizing with WiDAS (Wide-angle Infrared Dual-mode line/area Array Scanner), OMIS-II, TM, ASTER, MODIS, Hyperion and CHRIS. Diurnal variation in the radiative temperature was recorded as well. Raw data, blackbody calibrated data and processed data were archived in Excel format. (2) the surface radiative temperature by the handheld infrared thermometer (FOV:1°; accuracy: 0.1°C) in Yingke oasis maize field and wheat field, Huazhaizi desert maize field, No. 1 and 2 plots, and the maize field at the resort on May 20, 28, 30 and 31, Jun. 1, 4, 16 and 29, Jul. 4, 7 and 11, 2008. Besides, the four component temperature was also measured in Yingke oasis maize field and wheat field, Huazhaizi desert maize field. Raw data and processed data on the surface radiative temperature were archived.
CHAI Yuan, CHEN Ling, KANG Guoting, QIAN Yonggang, REN Huazhong, REN Zhixing, WANG Haoxing, WANG Tianxing, YAN Guangkuo, SHU Lele, Liu Qiang, XIA Chuanfu, XIN Xiaozhou, ZHOU Chunyan, SHEN Xinyi, LI Xinhui, YANG Guijun, LI Xiaoyu, HUANG Bo
This data set contains meteorological element observation data from January 1, 2015 to April 17, 2015 from huangcaogou station, upstream of heihe hydrometeorological observation network.The station is located in huangcaogou village, ebao town, qilian county, qinghai province.The latitude and longitude of the observation point is 100.7312e, 38.0033n and 3137m above sea level.The air temperature and relative humidity sensors are located at 5m, facing due north.The barometer is installed in the anti-skid box on the ground;The tilting bucket rain gauge is installed at 10m;The wind speed and direction sensor is set at 10m, facing due north;The four-component radiometer is installed at 6m, facing due south;Two infrared thermometers are installed at 6m, facing due south, and the probe facing vertically downward;The soil temperature probe is buried at 0cm on the surface and 4cm underground, 10cm, 20cm, 40cm, 80cm, 120cm, 160cm, 2m to the south of the meteorological tower.The soil water probe is buried at 4cm, 10cm, 20cm, 40cm, 80cm, 120cm and 160cm underground, 2m to the south of the meteorological tower.The soil heat flow plates (3 pieces) are buried in the ground 6cm underground, 2m to the south of the meteorological tower. Observation projects are: air temperature and humidity (Ta_5m, RH_5m) (unit: c, percentage), pressure (Press) (unit: hundred mpa), precipitation (Rain) (unit: mm), wind speed (WS_10m) (unit: m/s), wind (WD_10m) (unit: degrees), the radiation of four component (DR, UR, DLR_Cor, ULR_Cor, Rn) (unit: watts per square meter), the surface radiation temperature (IRT_1, IRT_2) (unit:Soil heat flux (Gs_1, Gs_2, Gs_3) (in watts/m2), soil temperature (Ts_0cm, Ts_4cm, Ts_10cm, Ts_20cm, Ts_80cm, Ts_120cm, Ts_160cm) (in Celsius), soil moisture (Ms_4cm, Ms_10cm, Ms_20cm, Ms_40cm, Ms_80cm, Ms_120cm, Ms_160cm) (unit: percentage). Processing and quality control of observed data :(1) ensure 144 pieces of data every day (every 10min), and mark by -6999 in case of data missing;(2) excluding the time with duplicate records;(3) data that obviously exceeds the physical significance or the range of the instrument is deleted;(4) the part marked with red letter in the data is the data in question, and there are many questions about the measured wind direction of the station;(5) date and time have the same format, and date and time are in the same column.For example, the time is: September 10, 2015, 10:30;(6) the naming rule is: AWS+ site name.The station was demolished after April 17. For information of hydrometeorological network or station, please refer to Li et al. (2013), and for observation data processing, please refer to Liu et al. (2011).
LIU Shaomin, LI Xin, CHE Tao, XU Ziwei, ZHANG Yang, TAN Junlei
This data set is the acquisition of the super-site forest 3D structure of the scanning point cloud data and other ancillary data based on the ground-based lidar (LiDAR) . Data acquisition time is from June 4, 2008 to June 12, 2008. Riegl LMS-Z360i ground-based LiDAR was used. The super site is divided into 16 sub-samples of 25m×25m, LiDAR base station points are set in each sub-sample, and LiDAR acquisition 3D full coverage LiDAR point metadata is set at each base station point. The content of the data set: total station measurement coordinates (x, y, z) for each LiDAR data acquisition base station point, the instrument attitude measured by a digital slope meter and an angle meter when each station collects data, and the laser radar scanning point cloud data at each station. This data set can provide realistic 3D forest scenes, provide detailed ground observation data for the development and correction of various 3D forest remote sensing models, and provide ground verification data for airborne and spaceborne remote sensing data.
BAO Yunfei, GUO Zhifeng, GUO Zhifeng, NI Wenjian, WANG Qiang, ZHANG Zhiyu
The Landuse/Landcover data of the Heihe River Basin in 2000 ( newly compiled in 2012), was finished by the Remote Sensing Laboratory of Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, using satellite remote sensing, based on the LandsaTM and ETM remote sensing data around 2000, combing field investigation and verification, thus leading to the establishment of the Heihe River Basin 1:10. 10,000 land use/land cover imagery and vector database. The main contents are: 1:100,000 land use graphic data and attribute data in the Heihe River Basin. The Heihe River Basin 1:100,000 (2011) land cover data and the previous land cover data use the same layered land cover classification system, the whole basin is divided into six first-class categories (cultivated land, woodland, grassland, waters, urban and rural residents, industrial and mining land and unused land), 25 secondary classes; data types are vector polygons, stored as Shape format. Land cover classification attributes: Primary type, secondary type, attribute coding, spatial distribution position Cultivated land: Plain dry land, 123, is mainly distributed in basin, Piedmont zone, river alluvial, diluvial plain or lacustrine plain (lack of water, irrigation condition is poor). Hilly dry land, 122, is mainly distributed in Hilly areas. Generally speaking, land blocks distribute on gentle slopes, ridges and mats of hills. Mountainous dry land, 121, is mainly distributed in mountainous areas, with the elevation below 4000 meters (gentle slope, mountainside, steep slope platform, etc.) and the Piedmont zones. Woodland: There is woodland (arbor), 21, is mainly distributed in the mountains (below 4000 meters ) or on the slopes of the mountains, valleys, hills, plains and so on. Shrub land, 22, is mainly distributed in higher mountain areas (below 4500 meters), most of which distribute in hillsides, valleys and sandy land. Sparse forest land, 23, is mainly distributed in the mountains, hills, plains and sandy land, and on the edge of the Gobi (loam, gravel). Other woodlands, 24, are mainly distributed in the oasis field, around rivers, roadsides and rural settlements. Grassland: Highly covered grassland, 31, is mainly distributed in mountainous areas (slow slopes), hills (steep slopes) and inter-river beaches, Gobi, sand dunes, etc. Mid-covered grassland, 32, is mainly distributed in relatively dry areas (Gobi, low-lying land and sandy land,sand dunes, etc.). The low-cover grassland, 33, grows mainly in drier areas (on the loess hills and on the edge of the sand). Waters: Channel, 41 is mainly distributed in plains, inter-river cultivated land and inter-mountain valleys. Lake, 42, is mainly distributed in low-lying areas. Reservoir pit, 43, is mainly distributed in plains and valleys between rivers, surrounded by residential areas and cultivated land. Glacier and permanent snow cover, 44, mainly distribute at the top of (over 4000) alpine regions. Flood land, 46, is mainly distributed in the high and low hillside gullies, the piedmont, the plain lowlands, and the edge of the river and lake basins. Residents land: Urban land, 51, is mainly distributed in plains, mountain basins, slopes and valleys. Rural residential land, 52, are mainly distributed in oases, cultivated land and roadsides, on the tablelands and the slopes. Industrial land and traffic land, 53, are generally distributed in the periphery of towns, areas with fairly developed transportation and industrial mining areas. Unutilized land: Sandy land, 61, is mostly distributed in the basin, on both sides of the river, in the river bay and on the periphery of the Piedmont and Gobi. Gobi, 62, is mainly distributed in the Piedmont belt with strong wind erosion and sediment transport. Saline and alkaline land, 63, is mainly distributed in dry lakes, lakeside and areas relatively low with easy water accumulation. Swamp, 64, is mainly distributed in relatively low areas with easy water accumulation. Bare soil, 65, is mainly distributed in arid areas (steep hillsides, hills and gobi), with vegetation coverage less than 5%. Bare rock, 66, is mainly distributed in extremely arid rocky mountainous areas (windy and rainless). The other, 67 mainly distributes in bare rocks formed by freezing and thawing above 4000 meters, also known as alpine tundra.
WANG Jianhua
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 evaportranspiration measured by micro-lysimeter was obtained at the super site (100m×100m, pure Qinghai spruce) around the Dayekou Guantan forest station. Observation items included the ground-based lidar scanning, the total station measuring, DGPS, tally investigation, LAI, canopy spectrum, camera observations of the canopy, soil evapotranspiration, the soil frozen tube observations, surface roughness, precipitation interception, soil moisture and dry-wet weight of the forest component. Observation time was 18:00 every day from Jun. 1 to Dec. 31, 2008. 20 rain gauges, 4 self-made Lysimeter (diameter: 20cm) and the electronic balance were used. Those provide reliable data for retrieval of evapotranspiration from remote sensing data.
BAI Yunjie, CHE Tao, LI Jiancheng, TAN Junlei
The source data for this dataset is derived from world soil maps and multiple regional and national soil databases, including soil attributes and soil maps. We have adopted a unified data structure and data processing process to fuse diverse data. We then used the soil type connection method and the soil variable line connection method to obtain the spatial distribution of soil properties. To aggregate these data, we currently use the area weighting method. The raw data has a resolution of 30 seconds, and aggregated data with a 5-minute resolution (about 10km) is provided here. There are eight vertical layers with a maximum depth of 2.3 meters (ie 0- 0.045, 0.045- 0.091, 0.091- 0.166, 0.166- 0.289, 0.289- 0.493, 0.493- 0.829, 0.829- 1.383 and 1.383- 2.296 m). 1. Data characteristics: Projection: WGS_1984 Coverage: Global Resolution: 0.083333 degrees (about 10 kilometers) Data format: netCDF 2. The data set contains 11 items of general soil information and 34 properties of soil. (1) The general information of the soil is as follows, the file general.zip: No. Description Units 1 additional property 2 available water capacity 3 drainage class 4 impermeable layer 5 nonsoil class 6 phase1 7 phase2 8 reference soil depth cm 9 obstacle to roots 10 soil water regime 11 topsoil texture (2) The 34 soil properties are as follows, files 1-9.zip, 10-18.zip, 19-26.zip, 27-34.zip Soil organic carbon density: SOCD5min.zip: No. Attrubute units Scale factor 1 total carbon% of weight 0.01 2 organic carbon% of weight 0.01 3 total N% of weight 0.01 4 total S% of weight 0.01 5 CaCO3% of weight 0.01 6 gypsum% of weight 0.01 7 pH (H2O) 0.1 8 pH (KCl) 0.1 9 pH (CaCl2) 0.1 10 Electrical conductivity ds / m 0.01 11 Exchangeable calcium cmol / kg 0.01 12 Exchangeable magnesium cmol / kg 0.01 13 Exchangeable sodium cmol / kg 0.01 14 Exchangeable potassium cmol / kg 0.01 15 Exchangeable aluminum cmol / kg 0.01 16 Exchangeable acidity cmol / kg 0.01 17 Cation exchange capacity cmol / kg 0.01 18 Base saturation% 19 Sand content% of weight 20 Silt content% of weight 21 Clay content% of weight 22 Gravel content% of volume 23 Bulk density g / cm3 0.01 24 Volumetric water content at -10 kPa% of volume 25 Volumetric water content at -33 kPa% of volume 26 Volumetric water content at -1500 kPa% of volume 27 The amount of phosphorous using the Bray1 method ppm of weight 0.01 28 The amount of phosphorous by Olsen method ppm of weight 0.01 29 Phosphorous retention by New Zealand method% of weight 0.01 30 The amount of water soluble phosphorous ppm of weight 0.0001 31 The amount of phosphorous by Mehlich method ppm of weight 0.01 32 exchangeable sodium percentage% of weight 0.01 33 Total phosphorus% of weight 0.0001 34 Total potassium% of weight 0.01
SHANGGUAN Wei, DAI Yongjiu
This dataset contains the spectra of white cloth and black cloth obtained in the simultaneous time during the airborn remote sensing which supports the airboren data preprocessing as CASI, SASI and TASI , and the spetra of the typical targets in the middle reaches of the Heihe River Basin. Instruments: SVC-HR1024 from IRSA, ASD Field Spec 3 from CEODE, Reference board Measurement method: the spectra radiance of the targets are vertically measured by the SVC or ASD; before and after the target, the spectra radiance of the reference board is measured as the reference. This dataset contains the spectra recorded by the SVC-HR1024 ( in the format of .sig which can be opened by the SVC-HR1024 software or by the notepad ) and the ASD (in the format of .asd), the observation log (in the format of word or excel), and the photos of the measured targets. Observation time: 15-6-2012, the spectra of typical targets in the EC matrix using SVC 16-6-2012, the spectra of typical targets in the wetland by SVC 29-6-2012, the spectra of typical vegetation and soil in Daman site and Gobi site by ASD 29-6-2012, the spectra of white cloth and black cloth by ASD which is simultaneous with the airborne CASI data 30-6-2012, the spectra of vegetation and soil in the desert by ASD 5-7-2012, the spectra of white cloth and black cloth by ASD which is simultaneous with the airborne CASI data 7-7-2012, the spectra of corn in the Daman site for the research of daily speral variation. 8-7-2012, the spectra of white cloth and black cloth by ASD which is simultaneous with the airborne CASI data 8-7-2012, the spectra of corn in the Daman site by ASD for the research of daily speral variation 9-7-2012, the spectra of corn in the Daman site by ASD for the research of daily speral variation 10-7-2012, the spectra of corn in the Daman site by ASD for the research of daily speral variation 11-7-2012, the spectra of corn in the Daman site by ASD for the research of daily speral variation. The time used in this dataset is in UTC+8 Time.
XIAO Qing, MA Mingguo
The dataset of soil moisture profile observations was obtained (once every ten days) in the Pailugou watershed foci experimental area during 2007 and from May to Sep. 2008. The soil profile was the moss litter layer, 0-10cm, 10-20cm, 20-40cm, 40-60cm and 60-80cm. It was fetched by the cutting ring and was measured through oven drying. Land cover types included spruce forest located in different elevation levels of 2600m, 2700m, 2900m, 3100m and 3300m, scrub of 3300m, 3400m and 3500m, and tailo grassland of 2600m, 2700m, 2800m and 2900m. Data were archived in Excel format.
WANG Shunli, LUO Longfa, WANG Rongxin, CHE Zongxi, JING Wenmao
The dataset of ground truth measurements synchronizing with Landsat TM was obtained in the Biandukou foci experimental area from 11:10-13:30 on Mar. 17, 2008. Those provide reliable ground data for objects modelling and background modelling, remote sensing image simulation and scaling. Simultaneous with the satellite overpass, numerous ground data were collected, spectrum (ASD Fieldspec FRTM (Boulder, Co, USA), 350nm-2500nm, 3nm for the visible near-infrared band and 10nm for the shortwave infrared band), the surface temperature, atmospheric parameters, the soil profile gravimetric moisture (0-1cm, 1-3cm and 3-5cm), the shallow layer frost depth and the soil roughness in C1, G1, W1, W2, B1 and B2, mostly the grassland, the wheat stubble land, the deep plowed land and the rape stubble land. The quadrates of 90m×90m and 450m×450m were compartmentalized into 81 subgrids of 10m×10m and 50m×50m. Based on the resolution of 30m×30m and 150m×150m, the influence of adjacent eight pixels on the center pixel was studied. Section lines of each subgrid were adopted to acquire the pixel spectrum, which were measured more than once for the mean value. 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. 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. Atmospheric parameters were measured by CE318 to retrieve the total optical depth, aerosol optical depth, Rayleigh scattering coefficient, column water vapor in 936 nm, and various parameters at 550nm to obtain horizontal visibility with the help of MODTRAN or 6S. Those provide reliable data for atmosphere correction of the same period in this area. The gravimetric soil moisture (samples from 0-1cm, 1-3cm and 3-5cm) was measured by the microwave drying method. The frost depth by the chopstick and the ruler. The soil was considered frozen when it was hard and with ice crystal. The data can be opened by Microsoft Office. Nine data files were included, TM data, CE318 data, B1, B2, C1, G1, W1 and W2.
CHANG Sheng, CHANG Yan, Fang Qian, QU Ying, LIANG Xingtao, LIU Zhigang, PAN Jinmei, PENG Danqing, REN Huazhong, ZHANG Yongpan, ZHANG Zhiyu, ZHAO Shaojie, Zhao Tianjie, ZHENG Yue, Zhou Ji, LIU Chenzhou, YIN Xiaojun, ZHANG Zhiyu
The dataset of ground truth measurements synchronizing with PROBA CHRIS was obtained in the Biandukou foci experimental area on Jun. 22, 2008. Observation items included: (1) quadrates investigation including GPS by GARMIN GPS 76, species by manual cognition, the plant number by manual work, the height by the measuring tape repeated 4-5 times, the chlorophyll content by SPAD 502, the coverage by manual work and the biomass (samples from 0.5m×0.5m) by wet weight and dry weight. Data were archived as Excel files. (2) LAI of maize, desert scrub and the poplar by the fisheye camera (CANON EOS40D with a lens of EF15/28), shooting straight downwards, with exceptions of higher plants, which were shot upwards. Data included original photos (.JPG) and those processed by can_eye5.0 (as Excel files). For more details, see Readme file. (3) ground object spectrum of grassland, barley and the rape by ASD FieldSpec (350～2 500 nm) from BNU, with 20% reference board. 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. (4) BRDF of grassland, barley and the rape by ASD FieldSpec (350～2 500 nm), with 20% reference board. Raw data were binary files direct from ASD (by ViewSpecPro), which were recorded daily in detail. The processed reflectance and transmittivity were archived in .txt files. The dataset includes processed spectrum data, soil moisture, BRDF, quadrates investigation, integrating spheres data on the rape, LAI, CHRIS data and the fisheye camera data.
DING Songchuang, HAO Xiaohua, YU Yingjie
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