The data came from the badain jilin 1:500,000 wind-sand landform data set compiled by the desert research institute of the Chinese academy of sciences (now the institute of cold and drought of the Chinese academy of sciences. The dataset mainly includes :dimao(landform),height(dune height),lake(lake),lvzhou(oasis), river(river), road (road).
ZHU Zhenda, WANG Yimou, D Jeremy kyle, J Hofer
Glaciers are sensitive to climate change and are important indicators and amplifiers of global change. In inland river regions, river runoff mainly comes from mountain ice and snow melt. Glaciers are very important "solid reservoirs" in these regions, and glacial melt water is an important source of supply for the tributaries of the Heihe River. The inventory of glaciers in the Heihe River Basin was completed from 1979 to 1980. For related information, please refer to "Chinese Glacier Inventory-Qilian Mountains" edited by Wang Zongtai and others. In 2004, the relevant results of the "China Glacier Inventory" were systematically digitized and a database was established. The final results were released through the "China Glacier Information System". However, in the process of coordinate restoration, the accuracy of the reference data was poor, and the glaciers in the Heihe River Basin had obvious position shifts. Therefore, we used the Landsat remote sensing image corrected by ortho-geometric correction. The processed Heihe Glacier distribution data is highly consistent with the existing basic geographic information in China in terms of geometric accuracy, and consistent with the first glacier inventory in terms of attributes.
WANG Zongtai
Data Overview: The spatial distribution data of mining wells in Zhangye City are provided by Zhangye Municipal Water Affairs Bureau, including 6,228 mechanized wells in agriculture, industry, forestry, life, scientific research and other 6 types. Data acquisition process: Zhangye Municipal Water Affairs Bureau entrusts the Hydrogeological Engineering Geological Survey Institute of Gansu Provincial Bureau of Geology and Mineral Resources to be responsible for special investigation of the data of mining wells in Zhangye City. The special survey of mining wells takes the irrigation area as a unit, uses hand-held GPS to locate the coordinates of the wells, and establishes the information card of mining wells through investigation and visit. A total of 7,429 eyes of various wells were surveyed. Among them, 6228 mining wells are still in use; 1201 wells were abandoned at the time of investigation. Description of data content: The attribute table contains information of mining well number, coordinates, location, water intake purpose, mining well type, well depth at the time of investigation, pumping flow, annual mining volume, rated flow, quality evaluation, matching quality evaluation and comprehensive quality evaluation fields.
MA Mingguo
Railway distribution map is the basic data in the mapping process. In order to facilitate the use of users, we compiled the railway data set of Heihe River basin according to the railway data set distributed by the National Basic Geographic Information Center, the atlas of Gansu Province compiled by the Gansu Provincial map Geographic Information Center, the sky map and Guge map published by the China Surveying and Mapping Bureau. This data basically reflects the distribution of Railways around the Heihe River basin around 2010. The national standard of data classification and coding of national basic geographic information system - Classification and code of basic land information data (GB / T 13923-92) is adopted for railway coding, and the code is five digit code (National Basic Geographic Information Center 2010).
National Basic Geographic Information Center
The vegetation sensor, sponsored by the European Commission, was launched by SPOT-4 in March 1998. It has received the spotvgt data for global vegetation cover monitoring since April 1998. The data is received by Kiruna ground station in Sweden, and the image quality monitoring center in Toulouse in France is responsible for image quality and provides relevant parameters (such as calibration coefficient). Finally, Belgium is responsible for image quality monitoring The Flemish Institute for technical research (Vito) vegetation processing center (ctiv) is responsible for preprocessing the data into 1km global data day by day. Preprocessing includes atmospheric correction, radiometric correction, geometric correction, and 10 day production to maximize the synthesized NDVI data, and set the value of - 1 to - 0.1 to - 0.1, and then convert to the DN value of 0-250 through the formula DN = (NDVI + 0.1) / 0.004. The dataset is a subset of China, which contains four bands of spectra synthesized every 10 days. Spot measurement (VGT) data is downloaded from the vegetation data website of Vito Institute in Belgium (http://free.vgt.vito.be), which includes the following: Spot vegation NDVI data and four band data, 10 days maximum synthesis, spatial resolution of 1km, effective time of 1998-2008, data naming specification is coverage + product type + year + month + day. Spot vector BRDF data, 10 days maximum synthesis, spatial resolution of 8km, effective time of 2001-2008, data naming specification is coverage + product type + year + month + day. Spot vectorization NPP data, 10 day maximum synthesis, spatial resolution of 8km, effective time of 1998-2006, data naming standard of "Heihe ﹣ NPP ﹣ VGT" + [1 or 2] + [year + month + day].
HU Ningke, Greet Janssens, MA Mingguo
This data is produced using knowledge rule-based land cover classification methods. It is a set of USGS global land cover classification standards that can be used in atmospheric models and land surface process models of land cover types in the Heihe River Basin. The data covers the upper, middle, and lower reaches of the Heihe River Basin. The data uses Albers Conical Equal Area projection with a spatial resolution of 1 km. It is an ASCII file containing the land cover classification code and named: Rule_Based_Lulc_of_HRB2009.asc. You can directly use a text program (such as Notepad) to open and view the file, you can also input it in ArcGIS for other operations. The NOAH land surface process parameter table and parameter table description matched with the data are provided. Users can refer to this parameter table to apply the data to the land surface process model. The two files are USGS_LULC_NOAHVEGPARM.TBL and NOAHVEGPARM_documentation.txt, both can be opened by the text program (such as Notepad).
NAN Zhuotong
Terra (EOS am-1), the flagship of the EOS earth observation series, was the first satellite to be launched on December 18, 1999.ASTER is primarily used for high-resolution observations of surface radiation balance. Compared with Landsat series satellites, ASTER has improved spectral and spatial resolution, and significantly increased short-wave infrared and thermal infrared bands.ASTER has a total of 14 wavebands, including 3 visible and near-infrared wavebands, 5 short-wave infrared wavebands and 5 thermal infrared wavebands. The resolution is 15m, 30m and 90m respectively, and the scanning width is 60km, 30m and 90m respectively.Heihe river basin ASTER remote sensing image data set through the international cooperation data from NASA's web site (https://wist.echo.nasa.gov/). Data naming rules as follows: assuming that the name of the ASTER image for "ASTL1B0103190215190103290064", then ASTL1B said ASTER L1B products, 003 on behalf of the version number namely VersionID, (010319) represents the next 6 digits observation date will be March 19, 2001, followed by six digits (021519) represents the observation time (02:15:19), followed by the last six digits (010329) representing the processing date is March 29, 2001, the last four digits (0064) representing the four-digit sequence code. At present, there are 258 scents of ASTER data in heihe river basin.The acquisition time is:2000-04-25, 2000-04-27 (2 scenes), 2000-05-04, 2000-05-15 (4 scenes), 2000-05-20 (9 scenes), 2000-05-29 (3 scenes), 2000-05-31 (2 scenes), 2000-06-12, 2000-06-14 (5 scenes), 2000-06-21 (3 scenes), 2000-06-30 (8 scenes), 2000-07-18, 2000-07-23 (3 scenes), 2000-08-03 (4 scenes),2000-08-08 (9 scenes), 2000-08-17 (7 scenes), 2000-08-19 (4 scenes), 2000-08-26 (3 scenes), 2000-09-02 (4 scenes), 2000-10-02 (7 scenes), 2000-10-04 (6 scenes), 2000-10-29 (3 scenes), 2000-11-21, 2001-02-18 (2 scenes), 2001-02-25, 2001-03-11 (5 scenes), 2001-03-22 (4 scenes),2001-03-27 (4 scenes), 2001-03-29 (9 scenes), 2001-04-07 (2 scenes), 2001-04-12 (2 scenes), 2001-04-14 (6 scenes), 2001-07-10, 2001-07-12 (8 scenes), 2001-07-21 (8 scenes), 2001-08-13 (8 scenes), 2001-08-20 (7 scenes), 2001-08-22, 2001-08-27 (2 scenes), 2001-08-29,2001-09-03 (2 scenes), 2001-11-15 (7 scenes), 2002-02-01, 2002-03-30 (2 scenes), 2002-04-17 (2 scenes), 2002-05-24, 2002-06-04 (6 scenes), 2002-06-09, 2002-06-13, 2002-06-25, 2002-08-14 (3 scenes), 2002-09-29, 2002-10-19 (2 scenes), 2002-11-11 (2 scenes),2002-12-29 (4 scenes), 2003-04-18, 2003-05-24 (2 scenes), 2003-07-25, 2003-07-30, 2003-8-10 (5 scenes), 2003-08-12, 2003-08-17, 2003-09-09 (11 scenes), 2003-09-13 (4 scenes), 2003-10-15, 2003-10-18, 2003-10-29 (9 scenes), 2003-11-30, 2004-03-14, 2005-03-20,2005-06-05, 2005-08-11, 2007-10-22, 2007-11-14, 2007-11-23, 2007-12-04, 2008-01-28, 2008-02-13, 2008-05-03 (4 scenes), 2008-05-05, 2008-05-17, 2008-06-04 (2 scenes), 2008-06-13.
National Aeronautics and Space Administration
On July 23, 1972, the United States launched the world's first resource satellite "Landsat 1" , and Landsat 2 and Landsat 3 were launched in the following 10 years. These three satellites were the first generation of resource satellites. They were equipped withreturn-beam vidicon cameras and multi-spectral scanners (MSS) with 3 and 4 spectral segments respectively, a resolution of 79m and a width of 185Km. There are 28 scenes of MSS data in Heihe River Basin currently which were obtained on the following dates: 1972-10-14, 1972-10-30, 1973-01-10, 1973-01-31, 1973-02-16, 1973-06-04, 1973. -10-07, 1973-10-28 (2 scenes), 1973-12-22, 1974-01-05, 1975-10-07, 1975-10-09, 1976-07-04, 1976-10-18 , 1976-11-07, 1976-11-27, 1976-12-30, 1977-01-19, 1977-02-07, 1977-04-20, 1977-05-06 (2 scenes), 1977-05 -08, 1977-06-10, 1977-06-29, 1977-07-18, 1978-10-09. Ortho rectification was performed on the images.
LP DAAC User Services
QuickBird satellite was launched by Digital Globe corporation on October 18, 2001. It has 4 multi-spectral bands and 1 panchromatic band, with a spatial resolution of 0.61m for panchromatic bands and a spatial resolution of 2.5m for multi-spectral bands and a width of 16.5 * 16.5 km. There are two QuickBird remote sensing images in heihe river basin.The acquisition time and coverage were: 2004-03-23, covering zhangye area;2004-08-08, covering danokou and drainage ditch drainage basin. The product level is level L2 and has been geometrically corrected by the system.
LI Xin, GUO Jianwen
This data set is a subset of 1:100000 desert spatial data in China. The 1:100000 desert spatial data set in China reflects the geographical distribution, area size, mobility and fixation degree of deserts in China. Taking the TM image of 2000 as the information source, on the basis of the coverage of the national land use map and the TM digital image information of 2000, this paper interprets, extracts, revises, and maps the sand, sand and Gravel Gobi in China by using remote sensing and geographic information system technology combined with the mapping requirements of 1:100000 scale thematic map.
WANG Jianhua
Landsat 5 was launched in March 1984 and has been in orbit for 16 years. The thematic mapper (TM) sensor on Landsat 5 consists of seven bands, all of which have a resolution of 30m except for band 6, which has a resolution of 120m. Currently, there are 23 TM data sets in heihe river basin.The obtained time was 1987-08-15, 1987-09-14, 1987-10-09, 1988-06-28, 1989-05-09, 1990-07-30, 1990-08-21 (2 scenes), 1990-08-28, 1990-08-30, 1990-09-15 (2 scenes), 1991-09-02, 1995-08-19, 1995-08-21, 2002-06-13,2003-09-12, 2007-09-23, 2008-03-17, 2008-07-07, 2008-07-23. The product is class L1 and has been geometrically corrected.
LP DAAC User Services
The Landsat TM Mosaic Image of the Heihe River Basin can be effectively applied to monitoring land-use change of the basin, which reflects the current situation of the Heihe River Basin in 2010, and provides a reliable basis for ecological planning and restoration. This mosaic image collected the TM images released by the USGS for free in 2010 (data from July to September 2010, totally 21 scenes, the maximum cloud amount is less than 10%), and the preprocessed images were geometrically registered by topographic maps(polynomial geometry correction method), then a geometrically-corrected digital mosaic map was generated, which was of high quality after a certain accuracy evaluation. The images were stored in ERDAS IMG format, and the most abundant bands 5, 4 and 3 combination, with three colors: red, green, and blue were selected to generate a color composite image. The combined composite image not only is similar to natural color, which is more in accordance with people's visual habits, but also can fully display the differences in image features because of the rich amount of information.
LP DAAC User Services
Data overview: This set of data mainly includes six prefecture level cities and 16 counties (Ganzhou District, Gaotai County, Shandan County, Minle County, Linze County, Sunan Yugu Autonomous County, Jinta County, Subei Mongolian Autonomous County, Suzhou District, Yumen City, Jiayuguan City, Yongchang County, Qilian County, Alxa Left Banner, Ejina Banner, Alxa Right Banner) in Heihe River Basin ）The 12 social and economic data are: GDP, output value of primary industry, output value of secondary industry, output value of tertiary industry, per capita GDP, per capita disposable income of urban residents, per capita net income of rural residents, fixed asset investment, total retail sales of social consumer goods, fiscal revenue, fiscal expenditure, and total grain output (including all kinds of work) Output of the product). It is divided into county level and township level. The data period is 2000-2009.
ZHAO Jun
Based on the geostationary satellites and reanalysis data, the China Regional Atmospheric Driving Dataset is a set of atmospheric driving data sets with high spatiotemporal resolution prepared by the China Meteorological Administration, with a spatial resolution of 0.1 ° × 0.1 ° and a temporal resolution of 1 Hours, covering a range of 75 ° -135 ° east longitude and 15 ° -55 ° north latitude, include 6 elements of near-surface temperature, relative humidity, ground pressure, near-surface wind speed, incident solar radiation on the ground, and ground precipitation rate. The preparation process of precipitation products is as follows: The 6-hour cumulative precipitation estimated from the multi-channel data of the China Fengyun-2 geostationary satellite is integrated with the 6-hour cumulative precipitation from conventional ground observations to obtain 6-hour cumulative precipitation spatial distribution data, and then use the high-resolution cloud classification information retrieved from the multi-channel inversion of the geostationary satellites determines the interpolation time weight of the cumulative precipitation and obtains an estimated one-hour cumulative precipitation. The preparation process of the radiation data is as follows: The surface incident solar radiation based on FY-2C, uses the radiation transmission model DISORT (Discrete Ordinates Radiative Transfer Program for a Multi-Layered Plane-parallel Medium) to calculate the radiation transmission and obtains the data of surface incident solar radiation in China. Preparation process of other elements: The space and time interpolation method is used for the NCEP reanalysis data of 1.0 ° × 1.0 ° to obtain driving factors such as near-surface air temperature, relative humidity, ground pressure, and near-surface wind speed of 0.1 ° × 0.1 ° per hour. Physical meaning of each variable: Meteorological Elements || Variable Name || Unit || Physical Meaning | Surface temperature || TBOT || K || Surface temperature (2m) | Surface pressure || PSRF || Pa || Surface pressure | Relative humidity on the ground || RH || kg / kg || Relative humidity near the ground (2m) | Wind speed on the ground || WIND || m / s || Wind speed near the ground (anemometer height) | Surface incident solar radiation || FSDS || W / m2 || Surface incident solar radiation | Precipitation Rate || PRECTmms || mm / hr || Precipitation Rate For more information, see the data documentation published with the data.
SHI Chunxiang
Desertification is a kind of land degradation with aeolian sands as the main symbol caused by the uncoordinated human-land relationship in arid, semi-arid and some semi-humid regions of northern China. Data source: edited by the China Institute of Glacial and Frozen Desert and coordinated by the Institute of Geography of the Chinese Academy of Sciences. Based on aerial photographs from the 1970s and field research, a 1: 2 million desert map was drawn. Mapping of the 14 million "Map of the People's Republic of China" published in 1971. First, the data set content 1.Desert_Ch_2009 (desert distribution) 2.Dune_hight_Ch_200 (dune height) 3.Gobi_Ch_200 (Gobi) 4.Wind_eroded_land_Ch_200 (wind erosion data) The fields of the desertification attribute table are as follows: (1) Semifixed (semi-fixed dunes): undulating sandy land (2-1), thicket dunes (2-2), parabolic dunes (2-3), beam nest dunes (2-4), sand ridges And dendritic sand ridge (2-5), honeycomb sand dune (2-6), honeycomb sand ridge (2-7), composite sand ridge (2-8) (2) Fixation (fixed dune): flat sandy land (3-1), grassland bush (3-2), sand ridge (3-3), honeycomb sand dune (3-4) (3) Migratory: Crescent sand dunes and dune chains (1-1), Crescent sand ridges and dunes (1-2), Lattice dunes and Lattice dune chains (1-3), Fish scales Sand dunes (1-4), feathery dunes (1-5), pyramid dunes (1-6), composite dunes and dune chains (1-7), composite dunes (1-8), composite Dome-shaped dunes (1-9), chain-shaped sand hills (sand dunes) (1-10), stacked chain-shaped sand hills (1-11), compound ridge-shaped sand hills (1-12), composite chain-shaped Sand Mountain (1-13), Pyramid Sand Mountain (1-14) (4) class_id: encoding of desertification attributes Projection information PROJCS ["Albers", GEOGCS ["GCS_Beijing_1954", DATUM ["Beijing_1954", SPHEROID ["Krasovsky_1940", 6378245.0,298.3]], PRIMEM ["Greenwich", 0.0], UNIT ["Degree", 0.0174532925199433]], PROJECTION ["Albers_Conic_Equal_Area"], PARAMETER ["False_Easting", 0.0], PARAMETER ["False_Northing", 0.0], PARAMETER ["longitude_of_center", 105.0], PARAMETER ["Standard_Parallel_1", 25.0], PARAMETER ["Standard_Parallel_2", 47.0], PARAMETER ["latitude_of_center", 0.0], UNIT ["Meter", 1.0]]
WANG Jianhua
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
In 2007 and 2008, Landsat data set 49 scenes, covering the entire black river basin. The acquisition time is:2007-08-12, 2007-09-23, 2008-01-05, 2008-02-06, 2008-03-17, 2008-03-25, 2008-05-10, 2008-05-19, 2008-05-28, 2008-06-04, 2008-07-07, 2008-07-15, 2008-07-22, 2008-07-23, 2008-08-16, 2008-08-30,2008-09-08, 2008-09-15, 2008-09-17, 2008-10-01, 2008-10-10, 2008-10-19, 2008-10-26, 2008-11-02, 2008-11-04, 2008-11-18, 2008-11-20, 2008-11-27, 2008-12-06, 2008-12-13, 2008-12-14. The product is class L1 and has been geometrically corrected.It includes 4 scenes of TM image and 45 scenes of ETM+ image. The Landsat satellite remote sensing data set of heihe integrated remote sensing joint experiment was obtained through free download.
HU Ningke
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
The medium resolution imaging spectrometer (MERIS) is a sensor mounted on the ENVISAT satellite of the European Space Agency. It has 15 spectral segments and scans the earth's surface by push sweep method. The incident angle of the point below the star is 68.5 degrees and the width is 1150km. At present, there are 56 ENVISAT MERIS data in Heihe River Basin. Acquisition time: 2008-05-01, 2008-05-02, 2008-05-03, 2008-05-05, 2008-05-07, 2008-05-08, 2008-05-11, 2008-05-14, 2008-05-17 (2 scenes), 2008-05-20 (2 scenes), 2008-05-21 (2 scenes), 2008-05-23 (2 scenes), 2008-05-24, 2008-05-30, 2008-05-31, 2008-06-01, 2008-06-02, 2008-06-05, 2008-06-06, 2008-06-09, 2008-06-12, 2008-06-15, 2008-06-18, 2008-06-21, 2008-06-22, 2008-06-24 (2 scenes), 2008-06-25, 2008-06-27, 2008-06-30, 2008-07-01, 2008-07-02, 2008-07-04, 2008-07-07, 2008-07-10, 2008-07-11, 2008-07-13 (2 scenes), 2008-07-13, 2008-07-16, 2008-07-17, 2008-07-20, 2008-07-23 (2 scenes), 2008-07-26 (2 scenes), 2008-07-27, 2008-07-29, 2008-07-30, 2008-08-01, 2008-08-02. The product level is L1B without geometric correction. The ENVISAT MERIS remote sensing data set of Heihe integrated remote sensing joint experiment was obtained through the China EU "dragon plan" project (Project No.: 5322) (see the data use statement for details).
HU Ningke
The aim of the simultaneous observation of river surface temperature is obtaining the land surface temperature in different places be of different kinds of underlying surface, while the sensor of WiDAS go into the experimental areas of the upstream of Heihe river basin. All the land surface temperature data will be used for validation of the retrieved land surface temperature from WiDAS sensor and the analysis of the scale effect of the land surface temperature, and finally serve for the validation of the authenticity of the surface temperature product from remote sensing. 1. Observation sites and other details Six places be of different kinds of underlying surface were chosen to observe surface temperature simultaneous in the upstream of Heihe river basin on 1 August. Self-recording point thermometers (observed once every 6 seconds) were used one place while handheld infrared thermometers (observed continuously during the sensor of WiDAS go into the region) were used in other five places. The main underlying surface including natural grassland, river section, river rapids, gravel. 2. Instrument parameters and calibration. The field of view of the self-recording point thermometer and the handheld infrared thermometer are 10 and 1 degree, respectively. The emissivity of the latter was assumed to be 0.95. All instruments were calibrated on 5 August, 2012 using black body during observation. 3. Data storage All the observation data were stored in excel.
GENG Liying, WANG Qingfeng, CAO Bin, WAN Xudong, PENG Li
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