1、 Data overview: use solinst leveloger automatic water level gauge to observe river water level, calculate flow data through water level flow curve, and manually observe the flow through self-made flow weir (see thumbnail). Due to the limited amount of manual observation data, further supplementary observation is needed to improve the water level discharge curve. 2、 Data content: we manually observe the water level and flow data of the two sections. The first section: the exit of area III divided by Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, the boundary point between cold desert zone and cold meadow zone, where the valley is deep and the bedrock is exposed. Coordinates of observation points (99 ° 53 ′ 37 ″ e, 38 ° 13 ′ 34 ″ n). The observation period is from July 21, 2012 to May 6, 2013. The observation frequency of automatic observation data is 1 time / 30 minutes from July 21 to July 25, 2012. 1 time / 15 minutes from July 25, 2012 to May 6, 2013. After September 15, 2012, there was an error in the automatic monitoring data of the observation point. The reason may be that the flow of the river channel became smaller, the probe was exposed to the air, and the water level gauge could not correctly reflect the change of the flow of the river channel. At the same time, the temperature decreased after September, and the river channel froze in winter. There was no automatic monitoring flow data during this period. The second section: the exit of No.2 area divided by Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, with flat terrain, is located at the catchment of the outlet of the alluvial delta Valley, and the south side is the shrub area. A small flow weir is built. The observation point coordinates (99 ° 52 ′ 58 ″ e, 38 ° 14 ′ 36 ″ n), and the observation frequency of automatic observation data is 1 time / 15 minutes. The observation period is from July 21, 2012 to May 6, 2013. After the observation point entered September, the river flow gradually decreased and there was no water in the river. At this time, the reading of water level gauge can not correctly reflect the change of river discharge. At the same time, our field experience shows that from September to May of the next year, the observation point is basically in a state of no water.
SUN Ziyong, YU Linan
On 25 July 2012, a Leica ALS70 airborne laser scanner boarded on the Y-12 aircraft was used to obtain the point cloud data. Leica ALS70 airborne laser scanner has unlimited numbers of returns intensities measurements including the first, second, third return intensities. The wavelength of laser light is 1064 nm. The absolute flight altitude is 5500 m with the point cloud density 1 points per square meter. Aerial LiDAR- DSM was obtained through parameter calibration, automatic classification of point cloud density and manual editing.
XIAO Qing, Wen Jianguang
Soil survey data corresponding to the ejin delta and the ecological vegetation sample during the project implementation period. Soil profile sampling corresponding to the ecological vegetation survey in ejin delta (5), 20 cm stratified sampling.Investigation items included: soil salinity, soil organic matter, C, N, P, etc., time: August 2011.
YU Jingjie
On 25 August 2012, Leica ALS70 airborne laser scanner boarded on the Y-12 aircraft was utilized to obtain point cloud data. Leica ALS70 airborne laser scanner has unlimited numbers of returns intensities measurements including the first, second, third return intensities. The wavelength of laser light is 1064 nm. The absolute flight altitude is 5200 m with the point cloud density 1 point per square meter. Aerial LiDAR-DEM was obtained through parameter calibration, automatic classification of point cloud density and manual editing.
XIAO Qing, Wen Jianguang
Soil water content is the key factor affecting the transpiration water consumption of plants in desert riparian forest. In this project, the typical plant communities in the lower reaches of Heihe River are selected, with coordinates of 42 ° 02 ′ 00.07 ″ N and 101 ° 02 ′ 59.41 ″ E. through continuous measurement of soil water data in 2010-2012, the observation instrument is environscan (Australia, ICT), with observation depth of 10, 30, 50, 80 and 140cm, and observation frequency of 0.5h Understanding the mechanism of environmental regulation of transpiration water consumption of desert riparian forest in the lower reaches of Heihe River provides basic data support.
SI Jianhua
1. Data overview: This data set is the groundwater level data of qilian station from January 1, 2012 to December 31, 2012.Well no. 1 is located at the side of the general controlled hydrologic section of the cucurbitou basin, with a depth of 12.8m and an aperture of 12cm.The second well is located to the east of the delta about 100m away from the river. The depth of the well is 14.7m and the aperture is 12cm. 2. Data content: U20-hobo water level sensor is installed in the underground well, which is mainly used to monitor the groundwater level changes in the small gourgou watershed. The data are daily scale data. 3. Space and time range: Geographical coordinates of well no. 1: longitude: longitude: 99° 53’e;Latitude: 38°16 'N;Elevation: 2974m (near the hydrological section at the outlet of the basin). Geographical coordinates of well no. 2: longitude: 99° 52’e;Latitude: 38°15 'N;Altitude: 3204.1m (east of the eastern branch of the delta).
HAN Chuntan
Leaf water potential is an important indicator of plant growth. In this project, Populus euphratica and Tamarix were selected in the lower reaches of Heihe River. Wp4c was used for 15 days to measure leaf water potential data before dawn, noon and sunset, which can provide basic data for understanding the growth conditions of desert plants.
SI Jianhua
On 25 July 2012, a Leica ALS70 airborne laser scanner boarded on the Y-12 aircraft was used to obtain the point cloud data. Leica ALS70 airborne laser scanner has unlimited numbers of returns intensities measurements including the first, second, third return intensities. The wavelength of laser light is 1064 nm. The absolute flight altitude is 4800 m with the point cloud density 1 points per square meter. Aerial LiDAR- DSM was obtained through parameter calibration, automatic classification of point cloud density and manual editing.
XIAO Qing, Wen Jianguang
The accurate estimation of sapwood area and heartwood area is the main means to convert the transpiration water consumption scale. In October 2011, this project investigated the sapwood and heartwood of 98 Populus euphratica in Ejin Oasis and measured the width of sapwood and heartwood. The relation curve of sapwood area with DBH and height was established. Please refer to LI Wei, SI Jianhua,FENG Qi, YU Teng fei. Response of Transpiration to Water Vapour Pressure Defferential of Populus euphratica. Journal of Desert Research, 2013, 33(5): 1377-1384. for details.
SI Jianhua
On 25 July 2012, a Leica ALS70 airborne laser scanner boarded on the Y-12 aircraft was used to obtain the point cloud data. Leica ALS70 airborne laser scanner has unlimited numbers of returns intensities measurements including the first, second, third return intensities. The wavelength of laser light is 1064 nm. The absolute flight altitude is 4800 m with the point cloud density 1 points per square meter. Aerial LiDAR-DEM was obtained through parameter calibration, automatic classification of point cloud density and manual editing.
XIAO Qing, Wen Jianguang
On 25 July 2012, a Leica ALS70 airborne laser scanner boarded on the Y-12 aircraft was used to obtain the point cloud data. Leica ALS70 airborne laser scanner has unlimited numbers of returns intensities measurements including the first, second, third return intensities. The wavelength of laser light is 1064 nm. The absolute flight altitude is 5500 m with the point cloud density 1 points per square meter. Aerial LiDAR-DEM was obtained through parameter calibration, automatic classification of point cloud density and manual editing.
XIAO Qing, Wen Jianguang
1. Data overview The data set of the base camp integrated environmental observation system is a set of ENVIS (IMKO, Germany) which was installed at the base camp observation point by qilian station.It is stored automatically by ENVIS data mining system. 2. Data content This data set is the scale data from January 1, 2012 to December 31, 2012.Including air temperature 1.5m, humidity 1.5m, air temperature 2.5m, humidity 2.5m, soil moisture 0cm, precipitation, wind speed 1.5m, wind speed 2.5m, wind direction 1.5m, geothermal flux 5cm, total radiation, surface temperature, ground temperature 20cm, ground temperature 40cm, ground temperature 60cm, ground temperature 80cm, ground temperature 120cm, ground temperature 160cm, CO2, air pressure. 3. Space and time scope Geographical coordinates: longitude: 99° 53’e;Latitude: 38°16 'N;Height: 2980.2 m.
CHEN Rensheng, HAN Chuntan
The NDVI data of GIMMS (glaobal modelling and mapping studies) is the latest global vegetation index change data released by NASA c-j-tucker et al in November 2003. This data set includes the changes in the vegetation index of the long time series of the qaidam basin from 1981 to 2006. The format is the standard ENVI format, and the projection is ALBERS. The temporal resolution is 15 days and the spatial resolution is 8km.GIMMS NDVI data recorded the vegetation changes in 22a region in the format of satellite data. 1. File format: The gimms-ndvi data set contains all the.rar compressed files with a 15-day interval from July 1981 to 2006, including one XML document, one.hdr header file, one.img file, and one.jpg image file after unzipped. 2. File name: The naming rule for compressed files in NOAA/ avhrr-ndvi data set is: YYMMM15a(b). N ** -vig_data_envi.After unzipping, there are four files with the same file name and attributes: XML document, header file (suffix:.hdf), remote sensing image file (suffix:.img) and JPEG image file. Remote sensing image files with suffixes.img and.hdf, which are used by users to analyze vegetation index, can be opened in ENVI and ERDAS software.
National Aeronautics and Space Administration
The sampling and distribution of plant materials in the arid regions of the middle and lower reaches of Heihe River Basin. The plants are mainly shrubs and a few herbs. The numbering of plant materials is consistent with the morphological structural characteristics analysis table and is used in correspondence with each other.
LIU Yubing
This data set contains the observation data of Zhangye National Climate Observatory from 2008 to 2009. The station is located in Zhangye, Gansu Province, with longitude and latitude of 100 ° 17 ′ e, 39 ° 05 ′ N and altitude of 1456m. The observation items include: atmospheric wind temperature and humidity gradient observation (2cm, 4cm, 10cm, 20m and 30m), wind direction, air pressure, photosynthesis effective radiation, precipitation, radiation four components, surface temperature, multi-layer soil temperature (5cm, 10cm, 15cm, 20cm and 40cm), soil moisture (10cm, 20cm, 50cm, 100cm and 180cm) and soil heat flux (5cm, 10cm and 15cm). Please refer to the instruction document published with the data for specific header and other information.
Zhangye city meteorological bureau
The survey area is 101 ° 3 ′ 13.265 ″ longitude, 42 ° 1 ′ 53.660 ″ latitude and 883.54m altitude. The sample area is 100 × 100m, and the sample area is 20 × 20m. The crown width, height and DBH of Populus euphratica were investigated.
SI Jianhua
Trunk sap flow is an effective tool for measuring transpiration of a single plant. In this project, the trunk sap flow data of Populus euphratica in the lower reaches of Heihe River was measured by HRM (ICT, Australia) with a frequency of 0.5h. In the growth season of 2012-2013, the installation location is the north and lateral roots (50cm underground depth, 30cm away from the trunk) at the DBH (1.3m).
SI Jianhua
On 25 August 2012, a Leica ALS70 airborne laser scanner boarded on the Y-12 aircraft was used to obtain LiDAR DSM point cloud data. Leica ALS70 airborne laser scanner has unlimited numbers of returns intensities measurements including the first, second, third return intensities. The wavelength of laser light is 1064 nm. The absolute flight altitude is 5200 m with the point cloud density 1 point per square meter. Aerial LiDAR-DSM was obtained through parameter calibration, automatic classification of point cloud density and manual editing.
XIAO Qing, Wen Jianguang
This data set is the multispectral data used to retrieve 30 meter Lai and fAPAR products in 2012. It is obtained by the environmental satellite CCD sensor with a resolution of 30 m and four bands. This data set has been geometric corrected, radiometric corrected and converted into reflectivity image.
FAN Wenjie
Lysimeter is the most effective tool for measuring water consumption per plant, which can provide daily, monthly and seasonal changes of transpiration water consumption per plant. In this project, a lysimeter measurement system for Populus euphratica seedlings is established in the lower reaches of Heihe River, with the observation frequency of 0.5h, mainly including water content changes, infiltration, evapotranspiration, etc.
SI Jianhua
This dataset include soil moisture and soil temperature observations of 50 SoilNET Nodes during June 2012~March 2013 (UTC+8), which located in a MODIS pixel in the observation matrix of the HiWATER artificial oasis eco-hydrology experimental area, and aim to capture the spatial-temporal variance at the ~100 m scale. Each SoilNET node observe the soil moisture and soil temperature at 4 cm, 10 cm, 20 cm and 40 cm depth using the SPADE sensor with 10 minutes interval. This dataset can be used in the estimation of surface hydrothermal variables and their validation, eco-hydrological research, irrigation management and so on. The detail description please refers to "SoilNET_data_document.docx".
WANG Xufeng, KANG Jian, Li Dazhi, Wang Zuocheng, Dong Cunhui, LI Xin, MA Mingguo
Based on MODIS Lai products (mcd15a2 and mod15a2), the daily and 1km resolution Lai datasets of 2001-2011 are obtained by using the improved hats algorithm to remove the cloud and reconstruct. The product coordinate system is longitude and latitude projection, and the spatial range is 96.5e-102.5e, 37.5n-43n. Every day's data is stored as a geotif file. The name is Heihe YYY ɇ Lai ɇ recon.ddd.tif, where yyyy is the year and DDD represents a certain day in a specific year. There are 365 days of output data by default every year. The data type is single precision floating-point type, the pixel filling value of invalid value is 255, the valid data range is 0-100, and the scaling factor is 0.1.
JIA Li
1. Data overview The data set of the base camp integrated environmental observation system is a set of ENVIS (IMKO, Germany) which was installed at the base camp observation point by qilian station.It is stored automatically by ENVIS data mining system. 2. Data content This data set is the scale data from January 1, 2012 to December 31, 2012.Including air temperature 1.5m, humidity 1.5m, air temperature 2.5m, humidity 2.5m, soil moisture 0cm, precipitation, wind speed 1.5m, wind speed 2.5m, wind direction 1.5m, geothermal flux 5cm, total radiation, surface temperature, ground temperature 20cm, ground temperature 40cm, ground temperature 60cm, ground temperature 80cm, ground temperature 120cm, ground temperature 160cm, CO2, air pressure. 3. Space and time scope Geographical coordinates: longitude: 99° 53’e;Latitude: 38°16 'N;Height: 2980.2 m
JIA Li
NDVI products based on MODIS (myd13a2 and mod13a2) use the improved hats algorithm to remove the cloud and reconstruct the daily and 1km resolution NDVI data set in 2001-2011. The product coordinate system is longitude and latitude projection, and the spatial range is 96.5e-102.5e, 37.5n-43n. Every day's data is stored as a geotif file. The name is Heihe ﹣ YYY ﹣ NDVI ﹣ recon.ddd.tif, where yyyy is the year and DDD represents a certain day in a specific year. There are 365 days of output data by default every year. The data type is 16bit shaping, the pixel filling value of invalid value is - 3000, the effective data range is - 2000-10000, and the scaling factor is 0.0001.
JIA Li
Meteorological elements are indicators of atmospheric variables or phenomena indicating weather conditions at a given place and at a given time. We used automatic forest weather station to monitor the meteorological elements data of Pailugou Watershed at 2800m above sea level. The main meteorological elements monitored include total radiation, net radiation, temperature, relative humidity, wind speed, and wind direction, which basically reflect the changes in meteorological elements in the Qinghai spruce forest.
CHANG Xuexiang
Soil moisture, also known as soil humidity. It is the moisture that remains in the pore space of the soil. The main source of soil moisture in Qinghai spruce forest is atmospheric precipitation, which is the only source of water absorption of Qinghai spruce to survive. The data is the soil moisture of Qinghai spruce forest in Pailugou of Heihe River Basin measured by the EM50 soil moisture meter produced in the United States.
CHANG Xuexiang
Forest survey is the application of measurement, tree measurement, remote sensing and other professional techniques and methods, survey, sampling and computer technology and other means to understand the quantity, quality, distribution and growth of forests within a specific range, so as to provide basic data for the formulation of forestry policies and scientific management of forests, as well as for scientific research. In the drainage ditch watershed of Qilian Mountain, there are three plots of Picea crassifolia forest in Qinghai Province, each of which is 2800m, 2900m and 3000m above sea level. Plot 01 is 20 * 30m and plot 02-09 is 20 * 35m. The traditional methods were used to investigate the tree height, DBH, base diameter and crown diameter of Picea crassifolia, providing basic data for the study of ecological hydrology of Picea crassifolia forest in the upper reaches of Heihe River.
CHANG Xuexiang
Soil evaporation in forest land is a process in which water in soil enters the atmosphere from the soil surface through rising and vaporizing. Soil evaporation affects the change of soil water content, which is an important part of hydrological cycle. The data were observed by the mini lysmeter evaporation tube, which was designed to provide data support for the study of water vertical exchange rule of Picea crassifolia forest.
CHANG Xuexiang
Forest canopy interception refers to the hydrological process in which part of water is intercepted and received by forest canopy and redistributed to precipitation in the process of precipitation. The data include precipitation, throughfall, canopy interception and interception rate, which are mainly used to provide data support for understanding the eco hydrological process of Picea crassifolia forest.
CHANG Xuexiang
Canopy conductance (mm s-1) is a sensitive index of forest transpiration response to environmental factors, and is a key parameter in water and carbon exchange model. The data is obtained by expanding the water consumption scale measured by stem sap flow technology to the stand scale to obtain the water consumption of the stand, and then using penman equation to calculate. This data mainly provides basic data for some eco hydrological models.
CHANG Xuexiang
The data set is the HWSD soil texture dataset of the Shulehe River Basin. The data comes from the Harmonized World Soil Database (HWSD) constructed by the Food and Agriculture Organization of the United Nations (FAO) and the Vienna International Institute for Applied Systems (IIASA). Version 1.1 was released on March 26, 2009. The data resolution is 1km. The soil classification system used is mainly FAO-90. The main fields of the soil attribute table include: SU_SYM90 (soil name in FAO90 soil classification system) SU_SYM85 (FAO85 classification) T_TEXTURE (top soil texture) DRAINAGE (19.5); ROOTS: String (depth classification of obstacles to the bottom of the soil); SWR: String (soil moisture characteristics); ADD_PROP: Real (a specific soil type related to agricultural use in the soil unit); T_GRAVEL: Real (gravel volume percentage); T_SAND: Real (sand content); T_SILT: Real (silt content); T_CLAY: Real (clay content); T_USDA_TEX: Real (USDA soil texture classification); T_REF_BULK: Real (soil bulk density); T_OC: Real (organic carbon content); T_PH_H2O: Real (pH) T_CEC_CLAY: Real (cation exchange capacity of cohesive layer soil); T_CEC_SOIL: Real (cation exchange capacity of soil) T_BS: Real (basic saturation); T_TEB: Real (exchangeable base); T_CACO3: Real (carbonate or lime content) T_CASO4: Real (sulfate content); T_ESP: Real (exchangeable sodium salt); T_ECE: Real (conductivity). The attribute field beginning with T_ indicates the upper soil attribute (0-30cm), and the attribute field beginning with S_ indicates the lower soil attribute (30-100cm) (FAO 2009). The data can provide model input parameters for modelers of the Earth system, and the agricultural perspective can be used to study eco-agricultural zoning, food security, and climate change.
Food and Agriculture Organization of the United Nations（FAO）
The dataset is a vector map of the administrative boundary of Qinghai Lake Basin, with a scale of 250,000 and projection: latitude and longitude. The data includes spatial data and attribute data, mainly including the name and administrative code of the county boundary of Qinghai Lake Basin.
National Basic Geographic Information Center
The data is the Shule River Basin land cover dataset, which is derived from "China's 1: 100,000 Land Use Data Set" in 2000. It is based on Landsat MSS, TM and ETM remote sensing data within three years by satellite remote sensing. This data adopts a hierarchical land cover classification system, which divides the country into 6 first-class categories (cultivated land, forest land, grassland, water area, urban and rural areas, industrial and mining areas, residential land and unused land) and 31 second-class categories. The attribute fields include: Area, Perimeter, Code(Land code), Name (land type).
LIU Jiyuan, ZHUANG Dafang, WANG Jianhua, ZHOU Wancun, WU Shixin
The VEGETATION sensor sponsored by the European Commission was launched by SPOT-4 in March 1998. Since April 1998, SPOTVGT data for global vegetation coverage observation has been received by Kiruna ground station in Sweden. The image quality monitoring center in Toulouse, France is responsible for image quality and provides relevant parameters (such as calibration coefficient number). Finally, the Belgian flemish institute for technological research (Vito)VEGETATION processing Centre (CTIV) is responsible for preprocessing into global data of 1km per day. Pretreatment includes atmospheric correction, radiation correction, geometric correction, production of 10 days to maximize the synthesized NDVI data, setting the value of -1 to -0.1 to -0.1, and then converting to the DN value of 0-250 through the formula DN= (NDVI+0.1)/0.004. The data set is the Shule River long-time series vegetation index data set, which is mainly aimed at normalized difference vegetation index (NDVI). It includes spectral reflectance of four bands synthesized every 10 days and maximum NDVI for 10 days from 1998 to 2008. The spatial resolution is 1km and the temporal resolution is ten days.
Greet Janssens
The data is the distribution map of 100,000 deserts in Qinghai Lake Basin. This data uses 2000 TM image as the data source for interpretation, extraction and revision. Remote sensing and geographic information system technology are combined with the mapping requirements of a scale of 1: 100,000 to carry out thematic mapping of deserts, sands and gravelly Gobi. Data attribute table: area (area), perimeter (perimeter), ashm_ (sequence code), class (desert code) and ashm_id (desert code), of which the desert code is as follows: mobile sand 2341010, semi-mobile sand 2341020, semi-fixed sand 2341030, Gobi desert 2342000 and saline-alkali land 2343000.
WANG Jianhua, YAN Changzhen
The dataset is the HWSD soil texture dataset of the Qinghai Lake Basin. The data comes from the Harmonized World Soil Database (HWSD) constructed by the Food and Agriculture Organization of the United Nations (FAO) and the Vienna International Institute for Applied Systems (IIASA). Version 1.1 was released on March 26, The data resolution is 1km. The soil classification system used is mainly FAO-90. The main fields of the soil attribute table include: SU_SYM90 (soil name in FAO90 soil classification system) SU_SYM85 (FAO85 classification) T_TEXTURE (top soil texture) DRAINAGE (19.5); ROOTS: String (depth classification of obstacles to the bottom of the soil); SWR: String (soil moisture characteristics); ADD_PROP: Real (a specific soil type related to agricultural use in the soil unit); T_GRAVEL: Real (gravel volume percentage); T_SAND: Real (sand content); T_SILT: Real (silt content); T_CLAY: Real (clay content); T_USDA_TEX: Real (USDA soil texture classification); T_REF_BULK: Real (soil bulk density); T_OC: Real (organic carbon content); T_PH_H2O: Real (pH) T_CEC_CLAY: Real (cation exchange capacity of cohesive layer soil); T_CEC_SOIL: Real (cation exchange capacity of soil) T_BS: Real (basic saturation); T_TEB: Real (exchangeable base); T_CACO3: Real (carbonate or lime content) T_CASO4: Real (sulfate content); T_ESP: Real (exchangeable sodium salt); T_ECE: Real (conductivity). The attribute field beginning with T_ indicates the upper soil attribute (0-30cm), and the attribute field beginning with S_ indicates the lower soil attribute (30-100cm) (FAO 2009). The data can provide model input parameters for modelers of the Earth system, and the agricultural perspective can be used to study eco-agricultural zoning, food security, and climate change.
Food and Agriculture Organization of the United Nations（FAO）
The data is a land cover dataset of the Qinghai Lake Basin, which was derived from the "China 1: 100,000 Land Use Dataset" in 2000. It was constructed based on Landsat MSS, TM and ETM remote sensing data within three years using satellite remote sensing. This data uses a hierarchical land cover classification system, which divides the country into 6 first-class categories (arable land, forest land, grassland, waters, urban and rural areas, industrial and mining, residential land and unused land), and 31 second-class categories. The attribute fields include: Area, Perimeter, Code (Land Code), Name (Land Type).
LIU Jiyuan, ZHUANG Dafang, WANG Jianhua, ZHOU Wancun, WU Shixin
The data is a dataset of road distribution in Qinghai Lake basin, scale1: 250,000, projection: latitude and longitude, mainly including the spatial distribution and attribute data of main roads in Qinghai Lake basin, attribute fields: code (road code), name (road classification).
National Basic Geographic Information Center
The dataset is the distribution map of lakes in Qinghai Lake Basin. The projection is latitude and longitude. The data includes the spatial distribution data and attribute data of the lake. The attribute fields of the lake are: NAME (lake name), CODE (lake code).
WU Lizong
The dataset of ground truth measurement synchronizing with PROBA CHRIS was obtained in the Yingke oasis and Huazhaizi desert steppe foci experimental areas on Jun. 22, 2008. Observation items included: (1) Albedo by the shortwave radiometer in Huazhaizi desert No. 2 plot. R =10H (R for FOV radius; H for the probe height). Data were archived in Excel format. (2) BRDF of maize in Yingke oasis maize field by ASD (350-2 500 nm) from Beijing University and the observation platform of BNU make. The maximum height of the platform was 5m above the ground with the azimuth 0~360° and the zenith angle -60°~60°; BRDF in Huazhaizi desert No. 2 plot by ASD from Institute of Remote Sensing Applications (CAS) and the observation platform of its own make, whose maximum height was 2m above the ground with the zenith angle -70°~70°. Raw data were binary files direct from ASD (by ViewSpecPro), and pre-processed data on reflectance were in Excel format. (3) Atmospheric parameters in Huazhaizi desert No. 2 plot by CE318 (produced by CIMEL in France). The total optical depth, aerosol optical depth, Rayleigh scattering coefficient, column water vapor in 936 nm, particle size spectrum and phase function were then retrieved from these observations. The optical depth in 1020nm, 936nm, 870nm, 670nm and 440nm were all acquired by CE318. Those data include the raw data in .k7 format and can be opened by ASTPWin. ReadMe.txt is attached for detail. Processed data (after retrieval of the raw data) in Excel format are on optical depth, rayleigh scattering, aerosol optical depth, the horizontal visibility, the near surface air temperature, the solar azimuth, zenith, solar distance correlation factors, and air column mass number.
CHEN Ling, GUO Xinping, REN Huazhong, ZOU Jie, LIU Sihan, ZHOU Chunyan, FAN Wenjie, TAO Xin
The dataset of ground truth measurements for snow synchronizing with the airborne microwave radiometers (K&Ka bands) mission was obtained in the Binggou watershed foci experimental area on Mar. 30, 2008. Those provide reliable data for retrieval of snow parameters and properties, especially for dry and wet snow identification. Observation items included: (1) Snow density, snow complex permittivity, snow volumetric moisture and snow gravimetric moisture by the snowfork in BG-A; (2) Snow parameters including snow depth, the snow surface temperature synchronizing with the airborne microwave radiometers (K&Ka bands), the snow layer temperature, the snow grain size and snow density in BG-A (10 points), BG-B (6 points), BG-F (12 points), BG-H (21 points) and BG-I (20 points); For each snow pit, the snowpack was divided into several layers with 10-cm intervals of snow depth. The layer depth (by the ruler), the snow grain size (by the handheld microscope), snow density (by the cutting ring) and the snow temperature (by the probe thermometer) were obtained at each snow pit. Two files including raw data and the preprocessed data were archived.
BAI Yanfen, BAI Yunjie, GE Chunmei, GU Juan, HAO Xiaohua, LI Hongyi, LI Zhe, LIANG Ji, MA Mingguo, SHU Lele, WANG Jianhua, WANG Xufeng, WU Yueru, XU Zhen, ZHU Shijie, LI Hua, CHANG Cun, MA Zhongguo, JIANG Tenglong, XIAO Pengfeng , LIU Yan, ZHANG Pu, CHE Tao
The dataset of airborne imaging spectrometer (OMIS-II) mission was obtained in the Linze station-Linze grassland flight zone on Jun. 15, 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 liange ! endtime ! lat ! long ! lat |- | 1 || reservoir 1 || 2008-06-15_11-55-28_DATA.BSQ || 12:12:48 || 39.013 || 100.236 || -1.0 || 2540 || 12:15:37 || 39.085 || 100.150 || -1.0 |- | 2 || 1-13 || 2008-06-15_12-15-51_DATA.BSQ || 12:20:47 || 39.172 || 100.048 || 2867.7 || 5572 || 12:26:58 || 39.359 || 100.190 || 2867.8 |- | 3 || 1-12 || 2008-06-15_12-27-13_DATA.BSQ || 12:31:59 || 39.366 || 100.188 || 2846.6 || 5067 || 12:37:37 || 39.185 || 100.051 || 2867.8 |- | 4 || 1-11 || 2008-06-15_12-37-51_DATA.BSQ || 12:42:52 || 39.179 || 100.039 || 2878.8 || 5542 || 12:49:02 || 39.363 || 100.179 || 2884.8 |- | 5 || 1-10 || 2008-06-15_12-49-16_DATA.BSQ || 12:54:29 || 39.373 || 100.179 || 2909.9 || 5116 || 13:00:10 || 39.187 || 100.039 || 2897.3 |- | 6 || 1-9 || 2008-06-15_13-00-24_DATA.BSQ || 13:05:30 || 39.182 || 100.028 || 2864.2 || 5498 || 13:11:37 || 39.366 || 100.167 || 2859.7 |- | 7 || 1-8 || 2008-06-15_13-11-51_DATA.BSQ || 13:17:22 || 39.377 || 100.169 || 2846.8 || 5114 || 13:23:02 || 39.191 || 100.029 || 2862.3 |- | 8 || 1-7 || 2008-06-15_13-23-17_DATA.BSQ || 13:28:06 || 39.187 || 100.0187 || 2857.1 || 5497 || 13:34:13 || 39.372 || 100.158 || 2842.5 |- | 9 || 1-6 || 2008-06-15_13-34-27_DATA.BSQ || 13:39:10 || 39.380 || 100.158 || 2909.7 || 5184 || 13:44:55 || 39.197 || 100.019 || 2861.8 |- | 10 || 1-5 || 2008-06-15_13-45-10_DATA.BSQ || 13:50:09 || -1.000 || -1.000 || -1.0 || 5488 || 13:56:09 || -1.000 || -1.000 || -1.0 |- | 11 || 1-4 || 2008-06-15_13-56-23_DATA.BSQ || 14:01:20 || -1.000 || -1.000 || -1.0 || 5353 || 14:07:18 || -1.000 || -1.000 || -1.0 |- | 12 || 1-3 || 2008-06-15_14-07-32_DATA.BSQ || 14:12:36 || -1.000 || -1.000 || -1.0 || 5350 || 14:18:30 || -1.000 || -1.000 || -1.0 |- | 13 || 1-2 || 2008-06-15_14-18-46_DATA.BSQ || 14:22:48 || -1.000 || -1.000 || -1.0 || 5236 || 14:28:31 || -1.000 || -1.000 || -1.0 |- | 14 || 1-1 || 2008-06-15_14-28-49_DATA.BSQ || 14:34:02 || -1.000 || -1.000 || -1.0 || 5964 || 14:40:11 || -1.000 || -1.000 || -1.0 |- | 15 || reservoir 2 || 2008-06-15_14-40-51_DATA.BSQ || 14:51:05 || -1.000 || -1.000 || -1.0 || 6846 || 14:58:35 || -1.000 || -1.000 || -1.0 |}
Liu Liangyun, LI Xin, MA Mingguo
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 PR2 soil moisture profile observations (10cm, 20cm, 30cm, 40cm, 60cm and 100cm) was obtained in the Linze grassland foci experimental area. The sample points, with various underlying surface and depth were measured by PR2 probe in PR2 quadrate (3Grid×3Grid, 90m×90m) and PR2 line. Observations were carried out from May 31 to Jul. 13, 2008 with exceptions on Jun. 6, 8, 10, 13, 21, 27, 28, 29, Jul. 3 and 12. Data were archived in Excel and Word file. See WATER: Dataset of setting of the sampling plots and stripes in the foci experimental area of Linze station for more information.
CAO Yongpan, CHAO Zhenhua, GE Chunmei, HAN Xujun, HU Xiaoli, HUANG Chunlin, JIANG Xi, LI Hongxing, LIANG Ji, LIU Chao, NIAN Yanyun, WANG Shuguo, WANG Xufeng, WU Yueru, ZHU Shijie, FENG Lei, YU Fan, WANG Jing, LI Xiaoyu
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 snow spectral reflectance observations was obtained in the Binggou watershed foci experimental area on Mar. 23, 2008. Flat open space was chosen for the observations and observation items included: (1) Multi-angle snow spectrum by the observation platform made by BNU for snow bidirectional reflectance properties from 10:50-13:50 BJT; (2) Snow albedo by the total radiometer for its relationship with the solar altitude from 10:00-14:36 BJT; (3) The snow spectrum by the portable ASD (Xinjiang Meteorological Administration). Two files including raw data and the preprocessed data were archived.
BAI Yunjie, HAO Xiaohua, MA Mingguo, SHU Lele, WANG Xufeng, ZHU Shijie, QU Wei, REN Jie, CHANG Cun, MA Zhongguo, JIANG Tenglong, XIAO Pengfeng , ZHANG Pu
The dateset of soil texture measurements was obtained by the pipette method in the Biandukou and A'rou foci experimental area. Observation items were mainly the soil texture and the soil temperature. Data were archived as Excel files. Sampling locations were not recorded.
PAN Jinmei, ZHAO Shaojie
The dataset of the truck-mounted dual polarized doppler radar observations (time-continuous 10-minute on the 250m×250m horizontal grid) was obtained in the arid region hydrology experiment area from May 20 to Jul. 5, 2008. The observation site (38.73°N, 100.45°E, 1668m) was typical of complex underlying surface and transit zone landscapes. The aim was to explore and retrieve precipitation type and intensity by radar in cold regions, with the precipitation particle drop size analyzer and ground intensive measurements occurring simultaneously, thus making it possible to produce a high resolution precipitation dataset. The 714XDP X-band dual-linear polarization Doppler weather radar was with a horizontal resolution of 150 m, an azimuth resolution of 1, VCP from 10-22 layers and the scanning cycle 10 minutes. ZH, ZDR and KDP could be acquired together. For more details, please refer to Readme file.
CHU Rongzhong, ZHAO Guo, HU Zeyong, ZHANG Tong, JIA Wei
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