BJ-1 dataset includes 11 scenes, covering the upper and middle reaches of the Heihe river basin, which were acquired on 10-21-2007, 11-19-2007, 01-09-2008, 03-03-2008, 04-04-2008, 04-16-2008, 05-01-2008, 05-16-2008, 07-01-2008, 07-06-2008 and 07-08-2008. The sensor was MSI, substar resolution was 32m, fov was 22.06°, the orbit was 686km high and the dip angle was 98.1725°, the focal distance was 150mm, CCD pixel was 7μm, the near infrared band was 760nm-900nm, red wave band was 630nm-690nm and green wave band was 520nm-620nm. The data version is Level 2, which was released after geometric correction. BJ-1 dataset was acquired from "Dragon Programme" (grant number: 5322).
LI Xin
The data set records the statistical data of capital construction investment in Qinghai province according to the composition and construction nature, and the data is divided by industry, region, affiliation and registration type. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set consists of four tables: capital investment 1978-2001.xls by composition and nature of construction, capital investment 1978-2002.xls by composition and nature of construction, capital investment 1978-2003.xls by composition and nature of construction, and capital investment 2004.xls by composition and nature of construction. The data table structure is the same. For example, the data table from 1978 to 2001 has three fields: Field 1: year Field 2: building installation Field 3: equipment purchase
Qinghai Provincial Bureau of Statistics
This data set includes the observation data of the automatic meteorological station from January 2008 to September 2009 in Linze Inland River Basin Comprehensive station. The station is located in Linze County, Zhangye City, Gansu Province, with longitude and latitude of 100 ° 08 ′ e, 39 ° 21 ′ N and altitude of 1382m. The observation items include: atmospheric temperature and humidity gradient observation (1.5m and 3.0m), wind speed (2.2m and 3.7m), wind direction, air pressure, precipitation, net radiation and total radiation, carbon dioxide (2.8m and 3.5m), soil tension, multi-layer soil temperature (20cm, 40cm, 60cm, 80cm, 120cm and 160cm) and soil heat flux (5cm, 10cm and 15cm). Please refer to the instruction document published with the data for specific header and other information.
ZHANG Zhihui, ZHAO Wenzhi, MA Mingguo
This dataset contains monthly 0.05°×0.05° (1982, 1985, 1990, 1995, and 2000) and 0.01°×0.01° (2005, 2010, 2015 and 2017) LST products in Qilian Mountain Area. The dataset was produced based on SW algorithm by AVHRR BT from thermal infrared channels (CH4: 10.5µm to 11.3µm; CH5: 11.5µm to 12.5µm) at a resolution of 0.05°, MYD21A1 LST products at a resolution of 0.01° along with some auxiliary datasets. The auxiliary datasets include IGBP land cover type, AVHRR NDVI products, Modern Era Retrospective-Analysis for Research and Applications-2 (MERRA-2) reanalysis data, ASTER GED, Lat/Lon and the Julian Day information.
WANG Junbo, SHAO Xuemei
Soil heat flux is an important part of surface energy balance, and it is the basis of energy balance analysis. In 2011-2013, hfp01 was installed at 5cm and 10cm of Tamarix community in the lower reaches of Heihe River to measure soil heat flux, with the frequency of 0.5h.
SI Jianhua
This dataset includes one scene acquired on (yy-mm-dd) 2012-09-06, covering the natural oasis eco-hydrology experimental area in the lower reaches of the Heihe River Basin. This datum contains panchromatic and multi-spectral bands, with spatial resolution of 2.5 m and 10 m, respectively. The data product level of this image is Level 1. QuickBird dataset was acquired through purchase.
China Centre for Resources Satellite Data and Application
This data set records the statistical data of the utilization of foreign capital in Qinghai Province from 1958 to 2018, which is divided by industry, region, affiliation and registration type. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set consists of 23 tables Foreign capital utilization in Main Years 1958-2016.xls Foreign capital utilization in Main Years 1985-2004.xls Foreign capital utilization in Main Years 1985-2008.xls Foreign capital utilization in Main Years 1985-2009.xls Foreign capital utilization in Main Years 1985-2010.xls Foreign capital utilization in Main Years 1985-2011.xls Foreign capital utilization in Main Years 1985-2013.xls Foreign capital utilization in Main Years 1985-2014.xls Foreign capital utilization in Main Years 1985-2015.xls Foreign capital utilization in Main Years 1985-2017.xls Foreign capital utilization in Main Years 1985-2018.xls Foreign capital utilization in Main Years 1985-2006.xls Foreign capital utilization in Main Years 1991-2007.xls Foreign capital utilization in Main Years 2000-2005.xls Foreign capital utilization in Main Years 1985-2012.xls Utilization of foreign capital 2001.xls Utilization of foreign capital 2002.xls Utilization of foreign capital, 2000.xls Utilization of foreign capital 2004.xls Utilization of foreign capital 2003.xls A survey of foreign capital utilization 1985-2001.xls A survey of the utilization of foreign capital 1985-2002.xls A survey of utilizing foreign capital 1985-2003.xls The data table structure is the same. For example, there are two fields in the 1985-2001 data sheet of the utilization of foreign capital Field 1: year Field 2: Foreign Direct Investment
Qinghai Provincial Bureau of Statistics
This data was derived from "1: 100,000 Land Use Data of China". Based on Landsat MSS, TM and ETM remote sensing data, 1: 100,000 Land Use Data of China was compiled within three years by a remote sensing scientific and technological team of 19 research institutes affiliated to the Chinese Academy of Sciences, which was organized by the “Remote Sensing Macroinvestigation and Dynamic Research on the National Resources and Environment", one of the major application programs in Chinese Academy of Sciences during the "Eighth Five-year Plan". 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. This is the most accurate land use data product in our country at present. It has already played an important role in national land resources survey, hydrology and ecological research.
LIU Jiyuan, ZHUANG Dafang, WANG Jianhua, ZHOU Wancun, WU Shixin
Sketch map of 1:50000 geological map of hulugou small watershed in 2012, hulugou watershed is composed of Quaternary loose stratum and pre Cenozoic bedrock stratum. The pores of the bedrock stratum are mainly fissures and covered with thin residual slope deposits. The Pleistocene alluvial proluvial sand gravel layer (q3al + PL) above the piedmont plain is dominant. The loose formation in the front of the glacier is Holocene moraine gravel layer (q4gl), which is distributed under the modern cirque and forms lateral moraine and final moraine dike (ridge).
SUN Ziyong, CHANG Qixin
The integration of geomorphological information in western China was completed by a team led by Dr. Xie Chuanjie, Institute of Geography, Resources and Environment, Chinese Academy of Sciences. These include the national geomorphological database of 1: 4 million and the western geomorphological database of 1: 1 million. The geomorphological data of 1: 4 million are tracked, collected and collated by the Geography Department of the National Planning Commission of the Chinese Academy of Sciences, "China Geomorphological Map (1: 4 million)" edited by Li Bingyuan and "Geomorphological Map of China and Its Adjacent Areas (1: 4 million)" edited by Chen Zhiming. Scan and register the data, vectorize all registered maps by ArcMap software, and establish their own classification and code systems. Geomorphological types are divided into basic geomorphological types and morphological structure types (point, line and surface representation) according to map spots (common staining) and symbols. Data are divided into structural geomorphology and morphological geomorphology. Projection information: Projection: Albers False_Easting: 0.000000 False_Northing: 0.000000 Central_Meridian: 105.000000 Standard_Parallel_1: 25.000000 Standard_Parallel_2: 47.000000 Latitude_Of_Origin: 0.000000 Linear Unit: Meter (1.000000) Geographic Coordinate System: datumg Angular Unit: Degree (0.017453292519943299) Prime Meridian: <custom> (0.000000000000000000) Datum: D_Krasovsky_1940 Spheroid: Krasovsky_1940 Semimajor Axis: 6378245.000000000000000000 Semiminor Axis: 6356863.018773047300000000 Inverse Flattening: 298.300000000000010000
CHENG Weiming, ZHOU Chenghu
This data set records the statistical data of the output value and area of the construction industry in various regions of the country and their ranking (2001-2010). The data are divided by year. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set contains 10 data tables with the same structure. For example, the data table in 2010 has four fields: Field 1: Province (city, district) Field 2: gross output value of construction industry Field 3: construction area Field 4: as built area
Qinghai Provincial Bureau of Statistics
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.
GE Chunmei, GU Juan, JIN Rui, MA Mingguo, WANG Jianhua, WANG Xufeng,
The data set contains nearly 15 years of eddy covariance data from an alpine steppe ecosystem on the central Tibetan Plateau.The data was processed following standardized quality control methods to allow for comparability between the different years of our record and with other data sets. To ensure meaningful estimates of ecosystem atmosphere exchange, careful application of the following correction procedures and analyses was necessary: (1) Due to the remote location, continuous maintenance of the eddy covariance (EC) system was not always possible, so that cleaning and calibration of the sensors was performed irregularly. Furthermore, the high proportion of bare soil and high wind speeds led to accumulation of dirt in the measurement path of the infrared gas analyzer (IRGA). The installation of the sensor in such a challenging environment resulted in a considerable drift in CO2 and H2O gas density measurements. If not accounted for, this concentration bias may distort the estimation of the carbon uptake. We applied a modified drift correction procedure following Fratini et al. (2014) which, instead of a linear interpolation between calibration dates, uses the CO2 concentration measurements from the Mt. Waliguan atmospheric observatory as reference time series. (2) We applied rigorous quality filtering of the calculated fluxes to retain only fluxes which represent actual physical processes. (3) During the long measurement period, there were several buildings constructed in the near vicinity of the EC system. We investigated the influence of these obstacles on the turbulent flow regime to identify fluxes with uncertain land cover contribution and exclude them from subsequent computations. (4) We calculated the de-facto standard correction for instrument surface heating during cold conditions (hereafter called sensor self heating correction) following Burba et al. (2008) and a revision of the original method following Frank and Massman (2020). (5)Subsequently, we applied the traditional and widely used gap filling procedure following Reichstein et al. (2005) to provide a more complete overview of the annual net ecosystem CO2 exchange.(6) We estimated the flux uncertainty by calculating the random flux error (RE) following Finkelstein and Sims (2001) and by using the standard deviation of the fluxes used for gap filling(NEE_fsd) as a measure for spatial and temporal variation.
Felix Nieberding, MA Yaoming, Cristian Wille, Gerardo Fratini, Magnus Ole Asmussen, Yuyang Wang*, MA Weiqiang*, Torsten Sachs
The data set is MODIS vegetation index data (MOD13Q1). The source areas of the three rivers are extracted to carry out the research and analysis of the source areas of the three rivers separately. MOD13Q1 is a 16-day composite vegetation index, including normalized vegetation index (NDVI) and enhanced vegetation index (EVI). The spatial scope of Sanjiang Source covers two MODIS files (h25v05 and h26v05). Data storage format is hdf. Each file contains 12 bands: Normalized Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Data Quality (VI Quality), Red Reflectance, Near Infrared Reflectance (NIR Reflectance), Blue Reflectance, Mid Infrared Reflectance, Observation. Viewzenith angle, sun zenith angle, relative azimuth angle, composite day of the year and pixel reliability. The data format of this data set is hdf, spatial resolution is 250m, temporal resolution is 16 days, time range: February 2000 to October 2018.
Kamel Didan*, Armando Barreto Munoz, Ramon Solano, Alfredo Huete
The data set records the precipitation statistics of the main areas in Qinghai Province, and the data are divided by region. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set contains 18 data tables with the same structure. For example, the data table in 2001 has nine fields: Field 1: month Field 2: Xining Field 3: Ping An Field 4: source Field 5: chabcha Field 6: colleagues Field 7: Dawu Field 8: Jiegu Field 9: Delingha
Qinghai Provincial Bureau of Statistics
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.
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.
Gai Yingchun, WANG Jianhua, GUANG Jie, XIN Xiaozhou, ZHANG Yang,
The dataset of ground truth measurement synchronizing with Landsat TM was obtained in the Yingke oasis and Huazhaizi desert steppe foci experimental areas on May 20, 2008. Observation items included: (1) LAI in Yingke oasis maize field. The maximum leaf length and width of each alfalfa and barley were measured. Data were archived in Excel format. (2) Reflectance spectra in Yingke oasis maize field by ASD FieldSpec (350-2500nm, the vertical canopy observation and the transect observation) from Institute of Remote Sensing Applications (CAS), and in Huazhaizi desert No. 2 plot by ASD FieldSpec (350-1603nm, the vertical observation and the transect observation for reaumuria soongorica and the bare land) from Beijing Academy of Agriculture and Forestry Sciences. The grey board and the black and white cloth were also used for calibration spectrum. Raw data were binary files direct from ASD (by ViewSpecPro), and pre-processed data on reflectance were in Excel format. (3) the radiative temperature by 3 handheld radiometers in Yingke oasis maize field (Institute of Remote Sensing Applications, BNU and Institute of Geographic Sciences and Natural Resources respectively, the vertical canopy observation and the transect observation), and by 3 handheld infrared thermometers in Huazhaizi desert No. 2 plot (the vertical vegetation and bare land observation). The data included raw data (in Word format), recorded data and the blackbody calibrated data (in Excel format). (4) the radiative temperature of maize, wheat and the bare land of Yingke oasis maize field by ThermaCAM SC2000 (1.2m above the ground, FOV = 24°×18°). The data included raw data (read by ThermaCAM Researcher 2001), recorded data and the blackbody calibrated data (archived in Excel format). (5) Photosynthesis of maize, wheat and the bare land of Yingke oasis maize field by LI6400, carried out according to WATER specifications. Raw data were archived in the user-defined format (by notepat.exe) and processed data were in Excel format. (6) Maize albedo by the shortwave radiometer in Yingke oasis maize field. R =10H (R for FOV radius; H for the probe height). Data were archived in Excel format. (7) 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. (8) Coverage fraction of Reaumuria soongorica by the self-made coverage instrument and the camera (2.5m-3.5m above the ground) in Huazhaizi desert No. 2 plot. Based on the length of the measuring tape and the bamboo pole, the size of the photo can be decided. GPS data was used for the location and the technology LAB was used to retieve the coverage fractionof the green vegetation. Besides, such related information as the surrounding environment was also recorded. Data included the vegetation iamge and coverage (by .exe). (9) The radiative temperature of Reaumuria soongorica canopy and the bare land by 2 fixed automatic thermometers (FOV: 10°; emissivity: 0.95) in Huazhaizi desert No. 2 plot, observing straight downwards at intervals of 1s. Raw data, blackbody calibrated data and processed data were all archived in Excel format.
LI Jing, GUANG Jie, LIU Qiang, XIN Xiaozhou, ZHANG Hao, TIAN Jing,
The dataset of automatic meteorological observations was obtained at the Dayekou Maliantan grassland station (E100°18′/N38°33′, 2817m) from Nov. 2, 2007 to Dec. 31, 2009. The experimental area with a flat and open terrain was slightly sloping from southeast to northwest. The landscape was mainly grassland, with vegetation 0.2-0.5m high. Observation items were multilayer gradient (2m and 10m) of the wind speed, the air temperature and air humidity, the air pressure, precipitation, four components of radiation, the multilayer soil temperature (5cm, 10cm, 20cm, 40cm, 80cm, and 120cm), soil moisture (5cm, 10cm, 20cm, 40cm, 80cm, and 120cm), and soil heat flux (5cm & 15cm). The raw data were level0 and the data after basic processes were level1, in which ambiguous ones were marked; the data after strict quality control were defined as Level2. The data files were named as follows: station+datalevel+AMS+datadate. Level2 or above were strongly recommended to domestic users. As for detailed information, please refer to Meteorological and Hydrological Flux Data Guide.
MA Mingguo, Wang Weizhen, TAN Junlei, HUANG Guanghui, ZHANG Zhihui
This data is based on the 1:50,000 and 1:100,000 base maps of hexi and ejin by lanzhou institute of desert research, Chinese academy of sciences, and compiled by supplementary investigation.(1) land type map of zhangye region of gansu province and alashan right banner of Inner Mongolia (Chen longheng, 1:250,000);(2) soil map of beidahe river basin (li fuxing, Yang constituent system, 1:100,000);(3) land type map of ejin banner delta in Inner Mongolia (ejin banner delta research team, lanzhou desert research institute, Chinese academy of sciences, 1:250,000).The drawing USES the basic map data, the field route investigation mainly, the aerial photograph, the guardian photograph interpretation combination method.This chart by li fuxing, qiu baoming compilation, zhang ziyu participated in the work;Drawing for peng shilong, wang xizhang, guo yingsheng.The soil classification research group of nanjing institute of soil research, Chinese academy of sciences and li jin provided the classification and mapping specifications.According to the Chinese soil classification system and the field conditions, the soil in heihe river basin is divided into 8 soil classes, 12 subclasses, 23 soil classes and 60 subclasses.Its purpose is to reflect the main soil types, combinations and distribution rules of the region, and reflect the regional characteristics of the soil, comprehensively demonstrate the generalization of soil resources, and provide the basic scientific basis for the estimation and evaluation of the quantity and quality of land resources, the rational utilization of land resources and the rational redistribution of water resources basins.See attachment for soil data type attributes.
LI Fuxing, LIU Chao
