"Heihe River Basin Ecological hydrological comprehensive atlas" is supported by the key project of Heihe River Basin Ecological hydrological process integration research. It aims at data arrangement and service of Heihe River Basin Ecological hydrological process integration research. The atlas will provide researchers with a comprehensive and detailed background introduction and basic data set of Heihe River Basin. The boundary map of Heihe River Basin in 2005 is one of the basic geographic part of atlas, with scale of 1:2500000, positive axis and equal product conic projection, and standard latitude of 25 47。 Data sources: 2005 Heihe River basin boundary data, 2010 Heihe River Basin road data, 2008 1 million Heihe River basin administrative boundary data, 2009 Heihe River Basin residential area data, 2009 100000 river data.
ZHAO Jun, WANG Xiaomin
"Heihe River Basin Ecological hydrological comprehensive atlas" is supported by the key project of Heihe River Basin Ecological hydrological process integration research. It aims at data arrangement and service of Heihe River Basin Ecological hydrological process integration research. The atlas will provide researchers with a comprehensive and detailed background introduction and basic data set of Heihe River Basin. The TM image index map of Heihe River Basin is one of the basic geographic part of atlas, with a scale of 1:2500000, positive axis equal product conic projection and standard latitude of 25 47 N. Data source: TM image index data, Heihe River basin boundary.
ZHAO Jun, WANG Xiaomin
The annual total net primary productivity (NPP) and average productivity of different ecosystems in heihe river basin from 1998 to 2002 were estimated by using the light energy utilization model c-fix, high spatial and temporal resolution remote sensing data of SPOT/VEGETATION, global grid meteorological reanalysis data and land use map of heihe river basin. From 1998 to 2002, the 10-day 1-km resolution SPOT VEGETATATION NDVI (10-day maximum synthesis) data product in the heihe basin, provided by the image processing and archiving center (CTIV) of VITO institute, Belgium, was used to calculate the key parameters fAPAR required by the c-fix model. The daily temperature and total radiation of heihe river basin from 1998 to 2002 were obtained using a global 1.5 °× 1.5 ° grid meteorological data product from MeteoFrance. It contains the spatial distribution pattern of annual accumulation of NPP in heihe basin and the seasonal dynamic map of NPP.The spatial resolution of this data is 1km.
LU Ling
SRTM (Shuttle Radar Topography Mission) is by NASA and the national geospatial intelligence agency (NGA) cooperation to build the global 3 d graphics data project.In February 2000, the SRTM system mounted on the U.S. space shuttle endeavour collected radar image data between latitude 60 ° north and latitude 57 ° south, and acquired radar image data covering more than 80% of the world's land surface.After more than two years of processing, the digital terrain elevation model was made. This data set including the heihe river basin SRTM points picture and Mosaic two kinds of data, and the points of the graph is SRTM version 4 data by the CGIAR - CSI (international centre for tropical agriculture, http://srtm.csi.cgiar.org/) treatment, compared with the previous version has greatly improved, including: 1) use a lot of interpolation algorithm, 2) use more auxiliary DEM data to fill the blank spots and blank area, 3) compared with the third version of the data and migration half a yuan.The Mosaic map is obtained by splicing on the basis of sub-map. The sub-charts include srtm_56_04,srtm_56_05,srtm_57_04 and srtm_57_054. The data are 16 bit values representing the elevation value (-/+/32767 m). The maximum positive elevation is 9000 m and the maximum negative elevation is 12,000 m below sea level.Null data is identified by -32767.Divide the file into 24 rows (-60 to 60 degrees) and 72 columns (-180 to 180 degrees) per 5 latitude and longitude squares.
TYLER B. STEVENS
"Heihe River Basin Ecological hydrological comprehensive atlas" is supported by the key project of Heihe River Basin Ecological hydrological process integration research. It aims at data arrangement and service of Heihe River Basin Ecological hydrological process integration research. The atlas will provide researchers with a comprehensive and detailed background introduction and basic data set of Heihe River Basin. The industrial structure map of Heihe River Basin is one of the social and economic chapters in the atlas, with a scale of 1:2500000, positive axis and equal product conic projection, and standard latitude of 25 47 n. Data sources: social and economic data of Heihe River Basin, road data of Heihe River Basin in 2010, administrative boundary data of one million Heihe River Basin in 2008, residential area data of Heihe River Basin in 2009, and 100000 river data of 2009.
WANG Jianhua, ZHAO Jun, WANG Xiaomin
This data set comes from the Land use data of Zhangye city in 2005 completed by YAN Changzhen and others from Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences. The data was generated by manual interpretation based on Landsat TM and ETM remote sensing data around 2005. This data uses a hierarchical land cover classification system. There are six first-class classifications (cultivated land, woodland, grassland, waters, urban and rural areas, industrial and mining, residential land and unused land), and 25 second-class classifications covering five counties and one district of Zhangye City, Gansu Province. The land use classification criteria used by the Chinese Academy of Sciences since 1986 are adopted in this data. The data type is vector polygon, stored in Shape format, and the data range covers Zhangye City.
YAN Changzhen
Investigation of plant sample plots can reflect the structure and distribution of plant communities, the declining succession of plant communities and their interrelation with environmental changes, reveal the ecological damage process in the lower reaches of the Tarim River, and provide scientific basis for the environmental remediation of the Tarim River Basin in the large-scale development of the western part of the country. According to the difference of species composition of plant communities in different sections of 9 monitoring sections in the lower reaches of Tarim River, plant sample plots are set up along the direction perpendicular to the river course in each monitoring section. Due to the different vegetation growth in each section, the size and number of sample plots are not equal. Among them, the sample plot of 5m×5m is arranged on the section of the herbaceous community. 30m×30m sample plots are arranged on the section where vegetation grows sparsely or is basically free of herbaceous plants, and 4 15m× 15 m arbor and shrub sample plots are arranged at intervals of 15 m; 50m×50m sample plots are arranged on the section where arbor, shrub and grass vegetation all occupy a certain proportion. In each plot of 50×50m, four plots of 25m×25m are set at 25m intervals to record the individual number, coverage, DBH, basal diameter, height and crown width of each tree (or shrub). At the same time, 4 small sample plots of 5m×5m are set up in each sample plot to record the individual number, coverage, height and other indicators of each herbaceous plant, and GPS is used to locate and record the altitude and longitude and latitude of each sample plot. Data content includes: 1. word Document for Statistics of Plant Sample Land Survey Data from 2000, 2002 to 2007 2. 2000 Inventory of Plant Sample Sites in Lower Reaches of Tarim River (Akdun, Yahopumahan, Yingsu, Abodah, Keldayi Section Vegetation Coverage, Canopy Density, Root Weight, etc.) excel Table 3. excel Table of Plant Sample Plot Survey in Lower Reaches of Tarim River in August 2002 (Data on Individual Number, Crown Width, Plant Height, Density and Coverage of Plants in Akdun, Yingsu, Khaldayi, Arakan and Shidaoban Sections) 4. 2003 Inventory of Plant Sample Sites in Lower Reaches of Tarim River (Data on Individual Number, Crown Width, Plant Height, Density and Base Diameter of Plants in Lower Reaches of Tahe River and Herbaceous Biomass in Akerdun Section) excel Table 5. In September 2004, the lower reaches of the Tarim River plant sample plot questionnaire (data of individual number, crown width, plant height, basal diameter (or DBH), coverage and biomass) excel table of the lower reaches of the Tarim River in Yahefu Mahan, Yingsu, Abodah Le, Khaldayi, Tugamale, Arakan, Yiganbuma and Kaogan sections 6. In July 2005, the lower reaches of Tarim River plant sample plot questionnaire (9 monitoring sections in the lower reaches of Tahe River and data of individual number, crown width, plant height, basal diameter (or DBH) and coverage of plants in taitema lake, and herbaceous biomass data in Akerdun section) excel table 7. In July 2006, the lower reaches of Tarim River plant sample plot questionnaire (the number of individual plants, crown width, plant height, basal diameter (or DBH) and herbaceous biomass data of Akerdun section in 9 monitoring sections in the lower reaches of Tahe River) excel table 8. July 2007, the lower reaches of Tarim river plant sample plot questionnaire (the number of individual plants, crown width, plant height, basal diameter (or DBH) and herbaceous biomass data of akdun section in 9 monitoring sections in the lower reaches of Tahe river) excel table
CHEN Yaning, HAO Xingming, WU Lizong
This dataset is the first 1: 100,000 desert spatial database in China based on the graphic data of desert thematic maps. It mainly reflects the geographical distribution, area size, and mobility of sand dunes in China. According to the system design requirements and relevant standards, the input data is standardized and uniformly converted into a standard format for various types of data input. Build a library to run the delivery system. This project uses the TM image in 2000 as the information source, and interprets, extracts, and edits the coverage of the national land use map and TM digital image information in 2000. It uses remote sensing and geographic information system technology to 1: 100,000 Thematic mapping requirements for scale bar maps were made on the desert, sandy land and gravel Gobi in China. The 1: 100,000 desert map across the country can save users a lot of data entry and editing work when they are engaged in research on resources and the environment. Digital maps can be easily converted into layout maps The dataset properties are as follows: Divided into two folders e00 and shp: Desert map name and province comparison table in each folder 01 Ahsm Anhui 02 Bjsm Beijing 03 Fjsm Fujian 04 Gdsm Guangdong 05 Gssm Gansu 06 Gxsm Guangxi Zhuang Autonomous Region 07 Gzsm Guizhou 08 Hebsm Hebei 09 Hensm Henan 10 Hljsm Heilongjiang 11 Hndsm Hainan 12 Hubsm Hubei 13 Jlsm Jilin Province 14 Jssm Jiangsu 15 Jxsm Jiangxi 16 Lnsm Liaoning 17 Nmsm Inner Mongolia Gu Autonomous Region 18 Nxsm Ningxia Hui Autonomous Region 19 Qhsm Qinghai 20 Scsm Sichuan 21 Sdsm Shandong 22 Sxsm Shaanxi Province 23 Tjsm Tianjin 24 Twsm Taiwan Province 25 Xjsm Xinjiang Uygur Autonomous Region 26 Xzsm Tibet Autonomous Region 27 Zjsm Zhejiang 28 Shxsm Shanxi 1. Data projection: 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) 2. Data attribute table: area (area) perimeter ashm_ (sequence code) class (desert encoding) ashm_id (desert encoding) 3. Desert coding: mobile sandy land 2341010 Semi-mobile sandy land Semi-fixed sandy land 2341030 Gobi 2342000 Saline land 2343000 4: File format: National, sub-provincial and county-level desert map data types are vector shapefiles and E00 5: File naming: Data organization based on the National Basic Resources and Environmental Remote Sensing Dynamic Information Service System is performed on the file management layer of Windows NT. The file and directory names are compound names of English characters and numbers. Pinyin + SM composition, such as the desert map of Gansu Province is GSSM. The flag and county desert map is the pinyin + xxxx of the province name, and xxxx is the last four digits of the flag and county code. The division of provinces, districts, flags and counties is based on the administrative division data files in the national basic resources and environmental remote sensing dynamic information service operation system.
WANG Jianhua, WANG Yimou, YAN Changzhen, QI Yuan
On August 6, 2004, the institute of cold and drought, Chinese academy of sciences, organized a remote sensing experiment in the upper reaches of the heihe river basin, which obtained soil survey data of 14 sections, DEM of 1:500 scale in the drainage ditch basin, spectral data of typical features and synchronous ground observation data of dapingding TM and QuickBird satellite.It mainly includes: 1) spectral measurement data of typical ground objects The data mainly includes in continental river basin in linze county comprehensive research station near the station (hereinafter referred to as linze) of elaeagnus angustifolia, two poplars, tamarisk, bark, ephedra, sand, alfalfa, corn, cotton and salinization land spectra and dew ditch valley concept-people mei, grass, moss, alpine meadow grass, sword leaf thorns son, the spectra of soil and rock. 2) soil profile survey data Valley in line according to the altitude and vegetation types were set up 12 soil profile, and also in front of the row of dew ditch forest weather stations and linze weather station set up a soil profile 1, 14 were measured profile of soil moisture content, bulk density, adhering sand content and soil spectrum, dew ditch forest top weather stations and linze profile is measuring the thermal conductivity of soil and water parameters. 3) field measurement data of biophysical parameters of typical ground objects Standing near the corn, cotton, including linze small pine, alfalfa, and leaf area index measurement data of ephedra row dew in different heights with leaf photosynthesis, leaf area index data and vegetation features data (photosynthetic rate, stomatal conductance, intercellular CO2 concentration, leaf transpiration rate, leaf temperature) and the corresponding environmental factor data (air temperature, air relative humidity and atmospheric CO2 concentration, air, water content, atmospheric pressure, solar total radiation, photosynthetic active radiation). 4) ground synchronization test of remote sensing by large flat-topped satellite The simultaneous observation experiment of TM and QuickBird satellite was carried out in a relatively flat grass area (big flat roof) beside the drainage ditch watershed.On July 27, 2004, spectra, above-ground biomass and leaf area were measured at intervals of 15 meters in a 150m×150m quadrangular at a large flat roof.
LI Xin, RAN Youhua, HUANG Chunlin, QI Yuan, LU Ling, LI Jing, JING Zhefang, PENG Hongchun, Li Haiying, WANG Shugong
This data was compiled by Qiu Baoming, Gao Qianzhao, Peng Qilong, etc. of Lanzhou Desert Research Institute, Chinese Academy of Sciences, and published by Xi'an map publishing house in 1988 (Qiu Baoming, etc., 1988). The grassland is mainly divided into eleven categories: swamp grassland, low humidity grassland, plain desert grassland, plain semi desert grassland, desert riverside sparse forest shrub grassland, mountain desert grassland, mountain semi desert grassland, mountain grassland grassland, mountain meadow grassland, mountain meadow grassland, mountain shrub meadow grassland and ancillary grassland. Property fields include: Grassland code, type, and subclass.
Chou Baoming, Peng Qilong, Gao Qianzhao
Vegetation functional type (PFT) is the combination of large plant species according to the ecosystem function of plant species and the way of resource utilization. Each plant functional type shares similar plant properties, which simplifies the diversity of plant species to the diversity of plant function and structure.Vegetation functional types have been used in the dynamic global vegetation model (DGVM) to predict changes in ecosystem structure and function under global change scenarios.The 1km vegetation functional pattern map of heihe basin is based on the 1km land cover map of heihe basin (MICLCover subset of heihe basin), and is divided by using the vegetation functional climate rules proposed by Bonan et al. (2002).The climate data utilize the 0.1 degree atmospheric drive data of he jie and Yang kun, developing China region from 1981 to 2008.This map can be used in the land surface process model of heihe river basin.
RAN Youhua
一. Data overview In the heihe river basin simulation model development and environment construction of cross integration research, project support, ren-sheng Chen (RReDC) in the center of the renewable energy data provided by the model, on the basis of considering the data of heihe river and other radiation model parameterization scheme, by 1 km resolution DEM, heihe surface weather observation data and NECP reanalysis data, the preparation of total radiation, direct radiation and scattering radiation three data sets. 二, data processing process 1) data source Watershed basic data mainly include DEM data, as well as slope and slope direction data generated thereby.The model adopts Alberts equal area conic projection), the grid size is 1km*1km, a total of 411×562 grids, that is, the actual calculated area is about 23*10^4 km^2.The calculated year is 2002, and the temporal resolution is 1h. Two sets of NCEP/NCAR reanalysis data were used, one set was instantaneous data of 1°*1° per 6h, mainly ozone and precipitable data.The other set is based on the assimilation data of 4 times a day of 192*94 grid (which is the average value per 6h), mainly the data of total cloud cover and precipitation rate.The main reason for applying the two sets of data is that the total cloud cover changes dramatically with time, and the instantaneous data cannot control the overall change of the weather.However, it is impossible to control the weather change within 6 hours by using the average data of 6 hours. 2) method A. Short-wave solar incident radiation model in clear sky horizontal plane.Rayleigh scattering, aerosol absorption, water vapor absorption, ozone absorption and heterogeneous mixed gases (O2, CO2, etc.) are mainly considered in the calculation of direct radiation from clear sky. B. Short-wave radiation model of clear-sky solar incidence under arbitrary topographic conditions.According to the principle of solid geometry and the algorithm of the short-wave radiation of horizontal plane, a simple algorithm of the short-wave radiation considering the self-masking effect of mountain slopes is designed. C. Calculation of solar incident short-wave radiation under arbitrary terrain conditions in actual weather.Based on the Ver4Fortran source code provided by Dr. Harry d. K of the Greek institute of meteorology and atmospheric physics. D. Spatial interpolation adopts the three-dimensional interpolation method based on triangular grid. The time interpolation of the first set of data adopts linear interpolation. For specific algorithm description, please refer to: Chen rensheng, kang ersi, et al. (2006). "model of hourly incident short-wave radiation under arbitrary terrain and actual weather conditions -- a case study of heihe river basin." Chinese desert (05). 3) data verification The simulation results were verified by using the total radiation observation data of three automatic meteorological stations located in the mountainous area, xishui, linze in the middle reaches and ejinaqi in the lower reaches. The calculated results of the total radiation of xishui were relatively poor, with R2 = 0.71.The measured and calculated results of total radiation of linze and ejin flags are better, with R2 of 0.90 and 0.91, respectively. 4) conclusion It is a feasible method to calculate the solar incident short-wave radiation with large range, long time and high spatial and temporal resolution under any terrain and actual weather conditions by combining the radiation transmission parameterization scheme and remote sensing information, especially in the northwest arid region.The established model only USES DEM data of the basin and the slope and slope direction data generated thereby, while other data are reanalysis data, so it is easy to be popularized and applied.The weather changes at any time in high mountain areas. The main reason for the poor calculation effect of the model in high mountain areas is still the low spatial and temporal resolution of the total cloud cover data. Meanwhile, the inconsistency between the calculated value and the measured value partly leads to the poor comparison results.
CHEN Rensheng
In April 1999, Landsat 7 was launched. As a supplement and enhancement to the Landsat series, the sensor it carried was ETM+. The parameters of each band were close to those of Landsat 5, but the resolution of panchromatic band with a resolution of 15m was added, and the resolution of thermal infrared band was improved to 60m. At present, there are 85 ETM + data scenes in heihe river basin.Data acquisition time is 1999-07-07, 1999-09-23 (2 scenes), 1999-10-18, 1999-11-26, 2000-01-20, 2000-04-20, 2000-05-06 (2 scenes), 2000-05-20, 2000-06-14 (2 scenes), 2000-07-07 (2 scenes), 2000-07-08, 2000-08-10, 2000-10-02, 2000-10-11,2000-10-13, 2001-05-25, 2001-07-03, 2001-08-20 (2 king), 2001-10-23, 2002-05-03, 2002-05-28, 2002-06-13, 2002-06-29, 2002-07-24, 2004-12-11, 2005-07-23, 2005-09-09, 2005-10-09, 2006-05-07,2006-05-21, 2006-06-24, 2006-07-26, 2006-08-25, 2006-12-01, 2007-08-12, 2008-01-05, 2008-02-06, 2008-03-25, 2008-05-10, 2008-05-19, 2008-05-28, 2008-06-04, 2008-07-15 (2 scenes), 2008-07-22, 2008-08-16 (4 scenes),2008-08-30, 2008-09-08, 2008-09-15, 2008-09-17, 2008-10-01, 2008-10-10 (2 scenes), 2008-10-19 (3 scenes), 2008-10-26 (3 scenes), 2008-11-02, 2008-11-04 (4 scenes), 2008-11-18, 2008-11-20 (4 scenes), 2008-11-27 (3 scenes), 2008-12-04, 2008-12-062008-12-13 (3 scenes).
LP DAAC User Services
Reservoir refers to the artificial water area formed in valley, river or low-lying area by dam, dike, sluice, weir and other projects. It is the main measure used for runoff regulation to change the distribution process of natural water resources and plays an important role in social and economic development. Many reservoirs have been built in Heihe River Basin, which has an important impact on the utilization of water resources in this area. In order to facilitate the mapping needs of users, we use topographic map and remote sensing image to prepare the reservoir distribution map of the Heihe River Basin. The location and shape of the reservoir are mainly obtained by manual interpretation based on Google map image, which basically shows the current situation of the reservoir distribution in the Heihe River Basin around 2010.
National Basic Geographic Information Center
The data set includes ASTER GDEM data and its Mosaic. ASTER Global DEM (ASTER GDEM) is a Global digital elevation data product jointly released by NASA and Japan's ministry of economy, trade and industry (METI) on June 29, 2009. The DEM data is based on the observation results of NASA's new earth observation satellite TERRA.It is produced by the ASTER(Advanced Space borne Thermal Emission and Reflection Radio meter) sensor, which collects 1.3 million stereo image data, covering more than 99% of the earth's land surface.The data has a horizontal accuracy of 30 m (95% confidence) and an elevation accuracy of 7-14 m (95% confidence).This data is the third global elevation data, which is significantly higher than previous SRTM3 DEM and GTOPO30 data. We from NASA's web site (http://wist.echo.nasa.gov/api) to download the data of heihe river basin, and through the data center to distribute.The data distributed by the center completely retains the original appearance of the data without any modification to the data.If users need details about ASTER GDEM preparation process, please refer to the data documents of metadata connections, or visit http://www.ersdac.or.jp/GDEM/E/3.html or directly from https://lpdaac.usgs.gov/ reading and ASTER Global DEM related documents. ASTER GDEM is divided into several data blocks of 1×1 degree in distribution, and the distribution format is zip compression format. Each compressed file includes three files. The file naming format is as follows: ASTGTM_NxxEyyy_dem.tif ASTGTM_NxxEyyy_num.tif reademe.pdf Where xx is the starting latitude and yyy is the starting longitude._dem. Tif is the dem data file, _num. Tif is the data quality file, and reademe is the data description file. In order to facilitate users to use the data, on the basis of the fractional ASTER GDEM data, we splice fractional SRTM data to prepare the ASTER GDEM Mosaic map of the black river basin, which retains all the original features of ASTER GDEM without any resamulation. This data includes two files: heihe_aster_gdem_mosaic_dem.img Heihe_Aster_GDEM_Mosaic_num. Img The data is stored in the format of Erdas image, where the file _dem.img is the dem data file and the file _num. Img is the data quality file.
National Aeronautics and Space Administration
This set of data mainly includes the demographic data of 12 counties in 6 prefecture-level cities of Qinghai, Gansu and Inner Mongolia in Heihe River Basin, covering the time period of 2000-2009. The data source is the local statistical yearbook, which mainly includes: Statistical Bureau of Suzhou District. Statistical Yearbook of Suzhou. 2004-2009; Yumen Statistical Bureau. Yumen Statistical Yearbook. 2000-2008; Jinta County Statistical Bureau. Jinta County Statistical Yearbook. 2004-2009; Gaotai Statistical Bureau. Gaotai Statistical Yearbook. 2000-2007; Shandan County Statistical Bureau. Shandan County Statistical Yearbook. 2000-2009; Sunan Yugur Statistical Bureau. Statistical Yearbook of Sunan Yugur Autonomous County. 2004-2009; Minle County Statistical Bureau. Minle County Statistical Yearbook. 2004-2009; Shandan County Statistical Bureau. Shandan County Statistical Yearbook. 2000-2009; Linze County Statistical Bureau. Linze County Statistical Yearbook. 2000-2009; Ejin Banner Statistical Bureau. Ejin Banner Statistical Yearbook. 1990-2005; Qilian County Statistical Bureau. Qilian County National Economic Statistics. 2004-2009; Part of the data of Zhangye City comes from the basic social and economic situation of townships of Zhangye City in 2005. Data of Jiayuguan City is derived from the CNKI statistical data database of China National Knowledge Infrastructure, and only contains some county-level data. Data Content Description: The data mainly includes three population indicators of 12 counties in the basin, including Ganzhou District, Gaotai County, Shandan County, Minle County, Linze County, Sunan Yugur Autonomous County, Jinta County, Sunzhou District and Yumen City, Jiayuguan City, Qilian County, and Ejin Banner. The population indicators are permanent population, agricultural population and non-agricultural population at the end of the year. It is divided into two levels: county level and township level. The statistics currently available are: County level: Ejina Banner: 2006-2009: resident population, agricultural population, non-agricultural population at the end of each year Ganzhou District: 2009: agricultural population, non-agricultural population of the year; Gaotai County: 2009: agricultural population, non-agricultural population of the year; Sunan: 2000-2009: permanent population, agricultural population, non-agricultural population at the end of each year; Minle County: 2009: permanent population, agricultural population, non-agricultural population at the end of the year; Linze: 2009: permanent population, agricultural population, non-agricultural population at the end of the year; Yumen City: 2000-2005: permanent population, agricultural population, non-agricultural population at the end of each year; Township level: Ejin Banner: 2000-2005: permanent population, agricultural population, non-agricultural population at the end of the year; Ganzhou District: 2000-2008: permanent population, agricultural population, non-agricultural population at the end of the year; 2009: resident population at the end of the year; Gaotai County: 2000-2004, 2006, 2007: permanent population, agricultural population, non-agricultural population at the end of the year; 2009: resident population at the end of the year; Shandan County: 2000-2007: permanent population, agricultural population, non-agricultural population at the end of the year; 2009: resident population at the end of the year; Minle County: 2000-2008: permanent population, agricultural population, non-agricultural population at the end of the year; Jinta County: 2004-2009: permanent population, agricultural population, non-agricultural population at the end of the year; Yumen City: 2006-2008: permanent population, agricultural population, non-agricultural population at the end of the year; Suzhou District 2004-2009: permanent population, agricultural population, non-agricultural population at the end of the year; Qilian County: 2004-2009: permanent population, agricultural population, non-agricultural population at the end of the year; Permanent population at the end of the year, agricultural population, non-agricultural population County level township level county level township level county level township level Ejin Banner:2006-2009 2000-2005 2006-2009 2000-2005 2006-2009 2000-2005 Ganzhou District 2000-2009 2009 2000-2008 2009 2000-2008 Gaotai County 2000-2004、 2006、2007、2009 2009 2000-2004、 2006、2007 2009 2000-2004、 2006、2007 Shandan County 2000-2007、2009 2000-2007 2000-2007 Sunan County 2000-2009 2000-2009 2000-2009 Minle County 2009 2000-2008 2009 2000-2008 2009 2000-2008 Linze County 2009 2009 2009 Jinta County 2004-2009 2004-2009 2004-2009 Sunzhou District 2004-2009 2004-2009 2004-2009 Qilian County 2004-2009 2004-2009 2004-2009 Yumen City 2000-2005 2006-2008 2000-2005 2006-2008 2000-2005 2006-2008
ZHAO Jun
"Heihe River Basin Ecological hydrological comprehensive atlas" is supported by the key project of Heihe River Basin Ecological hydrological process integration research. It aims at data arrangement and service of Heihe River Basin Ecological hydrological process integration research. The atlas will provide researchers with a comprehensive and detailed background introduction and basic data set of Heihe River Basin. The soil type map of Heihe River Basin is one of the land surface layers in the atlas, with a scale of 1:2500000, a positive axis equal conic projection, and a standard latitude of 25 47 n. Data source: 1:1 million soil type data of Heihe River Basin Based on the second Soil Census, road data of Heihe River Basin in 2010, administrative boundary data of Heihe River Basin in 2008, residential area data of Heihe River Basin in 2009 and 100000 river data in 2009.
WANG Jianhua, ZHAO Jun, WANG Xiaomin
Data overview: this set of data mainly includes the spatial distribution of major roads in the heihe river basin, the attributes include road classification and road coding, and the data base year is 2010. Data preparation process: this set of data is based on the topographic map, remote sensing image and the latest road traffic map updated by the transportation department of gansu province in 2009. Data description: there are two important attributes of the data, namely, road classification and road code. The road classification is divided into national road, provincial road, county road, township road and private road. The road code is defined in accordance with the highway grade code of the traffic department.
WU Lizong, NIAN Yanyun
Data Overview: Zhangye's channels are divided into five levels: dry, branch, bucket, agricultural and Mao channels, of which the agricultural channels are generally unlined. Mao channels are field projects, so the three levels of dry, branch and bucket channels and a small part of agricultural channels are mainly collected. The irrigation canal system data includes 2 main canals (involving multiple irrigation districts), 157 main canals (within a single irrigation district), 782 branch canals and 5315 dou canals, with a total length of 8, 745.0km. Data acquisition process: remote sensing interpretation and GPS field measurement are adopted for data acquisition of irrigation canal system. Direct GPS acquisition channel is the most effective method, but the workload of GPS acquisition channel is too large, and we only verify the measurement in some irrigation areas. The main method is to first collect the manual maps of irrigation districts drawn by each water pipe. Most of these maps have no location, only some irrigation districts such as Daman and Shangsan have been located based on topographic maps, and some irrigation districts in Gaotai County have used GPS to locate some channels. Referring to the schematic diagram of the irrigation district, channel spatial positioning is carried out based on Quikbird, ASTER, TM remote sensing images and 1: 50000 topographic maps. For the main canal and branch canal, due to the obvious linear features on remote sensing images and the general signs on topographic maps, it can be located more accurately. For Douqu, areas with high-resolution images can be located more accurately, while other areas can only be roughly located according to fuzzy linear features of images and prompt information of irrigation district staff, with low positioning accuracy. Each water management office simultaneously provides channel attribute data, which is one-to-one corresponding to spatial data. After the first draft of the channel distribution map is completed, it is submitted twice to the personnel familiar with the channel distribution of each water pipe for correction. The first time is mainly to eliminate duplication and leak, and the second time is mainly to correct the position and perfect the attribute data. Description of data content: The fields in the attribute table include code, district and county name, irrigation area name, channel whole process, channel name, channel type, location, total length, lined, design flow, design farmland, design forest and grass, real irrigation farmland, real irrigation forest and grass, water right area, and remarks. Code example: G06G02Z15D01, where the first letter represents the county name, the 2nd and 3rd numbers represent the county (district) number, the 4th to 6th characters represent the trunk canal code, the 7th to 9th characters represent the branch canal code, and the 10th to 12th characters represent the dou canal code.
MA Mingguo
The geomorphic data of Heihe River are from the geomorphic Atlas of the people's Republic of China (1:1 million). This data is based on remote sensing image and other multi-source data integration and update. The main data used and referenced include: 1) remote sensing image data: TM and 2000's around 1990's nationwide About ETM image; 2) historical geomorphic map: 15 published 1 million geomorphic maps, two sets of 1:4 million geomorphic maps in China, 500000 or 1 million geomorphic sketches in all provinces and cities in China; 3) basic geographic data: 1:250000 basic geographic data and 250000 DEM data in China; 4) geological data: 1:500000 geological map in China; 5) relevant thematic maps: land use map, vegetation map and land resource map And so on. The interpretation method adopts the human-computer interaction method based on ArcGIS, and is carried out according to the interpretation sequence of hierarchical classification: the first layer: plain and mountain; the second layer: basic geomorphic types (28); the third layer: 10 genetic types; the fourth layer: secondary genetic types; the fifth layer: morphological difference classification types; the sixth layer: secondary morphological difference classification types; the seventh layer: slope, slope The eighth layer is the type of geomorphic material determined by material composition or lithology; the ninth layer is the combination of 1-7 layers of map spots. There are 441 geomorphic types and codes. Data fields include: fenfu (view frame number), name (attribute), class (code), sname (administrative division).
CHENG Weiming
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
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
This data uses soil conversion functions to take sand, silt, clay, organic matter, and bulk density as inputs to estimate soil hydrological parameters, including parameters of the Clapp and Hornberger function and van Genuchten and Mualem function, field water holding capacity, and withering coefficient. Median and coefficient of variation (CV) provide estimates. The data set is in a raster format with a resolution of 30 arc seconds, and the soil is layered vertically into 7 layers with a maximum thickness of 1.38 meters (ie 0-0.045, 0.045--0.091, 0.091--0.166, 0.166--0.289, 0.289-- 0.493, 0.493--0.829, 0.829--1.383 meters). The data is stored in NetCDF format. The data file name and its description are as follows: 1. THSCH.nc: Saturated water content of FCH 2. PSI_S.nc: Saturated capillary potential of FCH 3. LAMBDA.nc: Pore size distribution index of FCH 4. K_SCH.nc: Saturate hydraulic conductivity of FCH 5. THR.nc: Residual moisture content of FGM 6. THSGM.nc: Saturated water content of FGM 7. ALPHA.nc: The inverse of the air-entry value of FGM 8. N.nc: The shape parameter of FGM 9. L.nc: The pore-connectivity parameter of FGM 10. K_SVG.nc: Saturated hydraulic conductivity of FGM 11. TH33.nc: Water content at -33 kPa of suction pressure, or field capacity 12. TH1500.nc: Water content at -1500 kPa of suction pressure, or permanent wilting point
SHANGGUAN Wei, DAI Yongjiu
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
This data is from "China 1:100,000 land use data".China 1:100,000 land use data was constructed in three years based on Landsat MSS, TM and ETM remote sensing data by using satellite remote sensing as a means to organize remote sensing science and technology teams from 19 institutes affiliated to the Chinese academy of sciences (cas) in the "eighth five-year plan" major application project "national macro survey and dynamic research on remote sensing of resources and environment". According to the 1:100,000 land use data of gansu province, a hierarchical land cover classification system is adopted, which divides the whole country into 6 primary categories (arable land, forest land, grassland, water area, urban and rural areas, industrial and mining areas, residential land and unused land) and 31 secondary categories.It is the most accurate land use data product in China and has played an important role in national land resource survey, hydrological and ecological research.
LIU Jiyuan, ZHUANG Dafang, WANG Jianhua, ZHOU Wancun, WU Shixin
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 compilation basis of frozen soil map includes: (1) frozen soil field survey, exploration and measurement data; (2) aerial photo and satellite image interpretation; (3) topo300 1km resolution ground elevation data; (4) temperature and ground temperature data. Among them, the distribution of permafrost in the Qinghai Tibet Plateau adopts the research results of nanzhuo Tong et al. (2002). Using the measured annual average ground temperature data of 76 boreholes along the Qinghai Tibet highway, regression statistical analysis is carried out to obtain the relationship between the annual average ground temperature and latitude, elevation, and based on this relationship, combined with the gtopo30 elevation data (developed under the leadership of the center for earth resources observation and science and technology, USGS) Global 1 km DEM data) to simulate the annual mean ground temperature distribution over the whole Tibetan Plateau. Taking the annual average ground temperature of 0.5 ℃ as the boundary between permafrost and seasonal permafrost, the boundary between discontinuous Permafrost on the plateau and island Permafrost on the plateau is delimited by referring to the map of ice and snow permafrost in China (1:4 million) (Shi Yafeng et al., 1988); in addition, the division map of Permafrost on the big and small Xing'an Mountains in the Northeast (Guo Dongxin et al., 1981), the distribution map of permafrost and underground ice around the Arctic (b According to rown et al. 1997) and the latest field survey data, the Permafrost Boundary in Northeast China has been revised; the Permafrost Boundary in Northwest mountains mostly uses the boundary defined in the map of ice and snow permafrost in China (1:4 million) (Shi Yafeng et al., 1988). According to the data, the area of permafrost in China is about 1.75 × 106km2, accounting for about 18.25% of China's territory. Among them, alpine permafrost is 0.29 × 106km2, accounting for about 3.03% of China's territory. For more information, please refer to the specification of "1:4 million map of glacial and frozen deserts in China" (Institute of environment and Engineering in cold and dry areas, Chinese Academy of Sciences, 2006)
WANG Tao
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
This data is from "China 1:100,000 land use data".China 1:100,000 land use data was constructed in three years based on Landsat MSS, TM and ETM remote sensing data by using satellite remote sensing as a means to organize remote sensing science and technology teams from 19 institutes affiliated to the Chinese academy of sciences (cas) in the "eighth five-year plan" major application project "national macro survey and dynamic research on remote sensing of resources and environment". The 1:100,000 land use data set in gansu province adopts a hierarchical land cover classification system, which divides the whole country into 6 primary categories (arable land, forest land, grassland, water area, urban and rural areas, industrial and mining areas, residential land and unused land) and 31 secondary categories.It is the most accurate land use data product in China and has played an important role in national land resource survey, hydrological and ecological research.
LIU Jiyuan, ZHUANG Dafang, WANG Jianhua, ZHOU Wancun, WU Shixin
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
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
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