This data set is the global high accuracy global elevation control point dataset, including the geographic positioning, elevation, acquisition time and other information of each elevation control point. The accuracy of laser footprint elevation extracted from satellite laser altimetry data is affected by many factors, such as atmosphere, payload instrument noise, terrain fluctuation in laser footprint and so on. The dataset extracted from the altimetry observation data of ICESat satellite from 2003 to 2009 through the screening criteria constructed by the evaluation label and ranging error model, in order to provide global high accuracy elevation control points for topographic map or other scientific fields relying on good elevation information. It has been verified that the elevation accuracy of flat (slope<2°), hilly (2°≤slope<6°), and mountain (6°≤slope<25°) areas meet the accuracy requirements of 0.5m, 1.5m, and 3m respectively.
XIE Huan, LI Binbin, TONG Xionghua, TANG Hong, LIU Shijie, JIN Yanmin, WANG Chao, YE Zhen, CHEN Peng, XU Xiong, LIU Sicong, FENG Yongjiu
The data was obtained from the 30-second global elevation dataset developed by the US Geological Survey (USGS) and completed in 1996. Downloaded the data from the NCAR and UCAR Joint Data Download Center (https://rda.ucar.edu/datasets/ds758.0/) and redistributed it through this data center. GTOPO30 divides the world into 33 blocks. The sampling interval is 30 arc seconds, which is 0.00833333333333333 degrees. The coordinate reference is WGS84. The DEM is the distance from the sea level in the vertical direction, ie the altitude, in m, the altitude range from -407 to 8752, the ocean depth information is not included here, the negative value is the altitude of the continental shelf; the ocean is marked as -9999, the elevation above the coastline is at least 1; the island less than 1 square kilometer is not considered. In order to facilitate the user's convenience, on the basis of the block data, splice 10 blocks in -10S-90N and 20W-180E without any resampling processing. This data file is DEM_ptpe_Gtopo30.nc
HE Yongli
The sand drift potential data sets of Central Asia in 2017 is in tif format. It covers five countries in Central Asia, including Uzbekistan, Tajikistan, Kyrgyzstan, Kazakhstan and Turkmenistan. The sand drift potential is absolutely drift potential, that is, the sum of the flux in all directions, regardless of the direction of the potential. The data was obtained by GLDAS global three-hour assimilation data extraction calculation. The temporal resolution is month, the spatial resolution is 0.25°, and the time range is 2017. This data set can be used as an important reference data for sand storm disaster assessment.
GAO Xin
The data set is the vegetation coverage in Central Asia including three temperate deserts, the Karakum, Kyzylkum and Muyunkun Deserts, and one of the world's largest arid zones. This is the MODIS-NDVI data set calculated by using the NDVI and the vegetation coverage in arid region. The space and time resolutions are 500 m and 16 days, respectively. The time is from 01, January, 2017 to 18, December, 2017. The data set uses the the Geodetic coordinate system. It can be used for the investigation of the Desert oil and gas field, and oasis cities.
GAO Xin
Basic Geographic Data Set of Resources and Environment in Central and Western Asia Region, includes six parts: administrative divisions map, topographic and geomorphological map, river system maps, precipitation map, temperature map and potential evapotranspiration map. The precipitation and temperature datasets are interpolated based on the ground observations, while the potential evapotranspiration dataset is calculated based on the Penman-Monteith equation. The precipitation, temperature and potential evapotranspiration datasets are resampled from the original 0.5° CRU dataset by using the linear interpolation method in ArcGIS software. This dataset is made based a large number of gauge observations with good quality control and homogeneity check. The results of the related studies (Deng and Chen, 2017; Li et al., 2017; Li et al., 2016) suggested that this dataset is applicable and satisfactory for the climatological studies. The data produced by the key laboratory of remote sensing and GIS, Xinjiang institute of ecology and geography, Chinese Academy of Sciences. Data production Supported by the Strategic Priority Research Program of Chinese Academy of Sciences, Grant No. XDA20030101.
The data set is the distribution of the average roughness in Central Asia including three temperate deserts, the Karakum, Kyzylkum and Muyunkun Deserts, and one of the world's largest arid zones. This is the MODIS-NDVI data set calculated by using the median particle diameter and the vegetation coverage. The space and time resolutions are 500 m and 16 days, respectively. The time is from 01, January, 2017 to 18, December, 2017. The data set uses the the Geodetic coordinate system. It can be used for the investigation of the Desert oil and gas field, and oasis cities.
GAO Xin
This database includes slope, aspect and digital elevation model (DEM) data of Qinghai Tibet Plateau. The data comes from the 30m * 30m resolution numerical elevation model data downloaded from the geospatial data cloud website. Using the surface analysis function of ArcGIS software, the slope and aspect information of the Qinghai Tibet Plateau are extracted. The data has been rechecked and reviewed by many people, and its data integrity, position accuracy and attribute accuracy meet the standards, with excellent and reliable quality. As one of the engineering geological conditions, this data is the basic data for the research on the development law of major engineering disturbance disasters and major natural disasters in the Qinghai Tibet Plateau and the analysis of susceptibility, risk and risk.
QI Shengwen
Ⅰ. Overview This dataset is derived from the global 30m-resolution digital elevation product dataset, which is processed using the data of the first version (v1) of ASTER GDEM. Its spatial resolution is 30m. Due to the influence of clouds, lines, pits, bulges, dams or other anomalies generated by the boundary stacking, there are local anomalies in the first version of the original data of ASTER GDEM, so the digital elevation processed by ASTER GDEM v1 Data products have data anomalies in individual areas, and users need to pay attention to them during use. In addition, this data set can complement the SRTM global 90m resolution elevation dataset. Ⅱ. Data processing description ASTER GDEM is a fully automated method to process and generate ASTER archived data of 1.5 million scenes, including 1,264,118 ASTER DEM data based on independent scenes generated through stereo correlation. After de-cloud processing, residual outliers are removed, and the average value is taken as the final pixel value of ASTER GDEM object area. After correcting the remaining abnormal data, the global ASTER GDEM data was generated by 1°× 1° sharding. Ⅲ. Data content description The dataset covers the entire upper reaches of the Yellow River, and each data file name is generated based on the latitude and longitude of the lower left (southwest) Angle of the fractal geometry center. For example, the lower-left coordinate of the ASTGTM_N40E116 file is 40 degrees north latitude and 116 degrees east longitude. ASTGTM_N40E116_dem and ASTGTM_N40E116_num correspond to digital elevation model (DEM) and quality control (QA) data, respectively. Ⅳ. Data usage description ASTER GDEM data can be calculated and visualized. It has a broad application prospect in various fields, especially in mapping, surface deformation and military fields.Specifically, it mainly includes the following aspects: In scientific research, ASTER GDEM data plays an important role in geology, geophysics, seismic research, horizontal modeling, volcano monitoring and remote sensing image registration.The three-dimensional model of the ground is built by using high-precision digital terrain elevation data, which can be embedded and superimposed with the image of the ground to observe subtle changes of the earth surface. In civil and industrial applications, ASTER GDEM data can be used for civil engineering calculation, dam site selection, land use planning, etc. In communications, digital topographic data can help businesses build better broadcast towers and determine the best location of mobile phone booths.In terms of aviation safety, ASTER GDEM digital elevation data can be used to establish the enhanced aircraft landing alarm system, which greatly improves the aircraft landing safety coefficient. In the military, ASTER GDEM data is the basic information platform of C4ISR (army automatic command system), which is indispensable in the study of battlefield regional structure, combat direction, battlefield preset, combat deployment, troop concentration in projection, protection conditions, logistics support and other aspects.
XUE Xian, DU Heqiang
This data is based on the DEM data generated by 1:250,000 digital contour lines and elevation points in China released by national basic geographic information center, and the DEM data set of heihe river basin is generated by the nearest neighbor method resampling method of ARCGIS spatial analysis module with a spatial resolution of 30 SEC.
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
The SRTM sensor has two bands, namely C-band and X-band. The SRTM we are using now comes from the C-band. The publicly released SRTM digital elevation products include DEM data at three different resolutions: * SRTM1 covers only the continental United States, with a spatial resolution of 1s; * SRTM3 data covers the world with a spatial resolution of 3s. This is the most widely used dataset. The elevation reference of SRTM3 is the geoid of EGM96 and the horizontal reference is WGS84. The nominal absolute elevation accuracy is ± 16m, and the absolute plane accuracy is ± 20m. * SRTM30 data also covers the world, with a resolution of 30s. There are multiple versions of SRTM data. The early SRTM data was completed by NASA's "JPL" (Jet Propulsion Laboratory) ground data processing system (GDPS). The data is called SRTM3- 1. The National Geospatial Intelligence Agency has further processed the data, and the lack of data has been significantly improved. The data is called SRTM3-2. This dataset is mainly the fourth version of SRTM terrain data obtained by CIAT (International Center for Tropical Agriculture) using a new interpolation algorithm. This method better fills the SRTM 90 data hole. The interpolation algorithm comes from Reuter et al. (2007). The data of SRTM is organized as follows: every 5 latitude and longitude grids is divided into a file, which are divided into 24 rows (-60 to 60 degrees) and 72 columns (-180 to 180 degrees). The file naming rule is srtm_XX_YY.zip, where XX indicates the number of columns (01-72), and YY indicates the number of rows (01-24). The resolution of the data is 90 m. Data use: SRTM data uses a 16-bit value to represent the elevation value (-/ + / 32767 meters), the maximum positive elevation is 9000 meters, and the negative elevation (12,000 meters below sea level). -32767 standard for empty data.
CGIAR-CSI
The Antarctic ice sheet elevation data were generated from radar altimeter data (Envisat RA-2) and lidar data (ICESat/GLAS). To improve the accuracy of the ICESat/GLAS data, five different quality control indicators were used to process the GLAS data, filtering out 8.36% unqualified data. These five quality control indicators were used to eliminate satellite location error, atmospheric forward scattering, saturation and cloud effects. At the same time, dry and wet tropospheric, correction, solid tide and extreme tide corrections were performed on the Envisat RA-2 data. For the two different elevation data, an elevation relative correction method based on the geometric intersection of Envisat RA-2 and GLAS data spot footprints was proposed, which was used to analyze the point pairs of GLAS footprints and Envisat RA-2 data center points, establish the correlation between the height difference of these intersection points (GLAS-RA-2) and the roughness of the terrain relief, and perform the relative correction of the Envisat RA-2 data to the point pairs with stable correlation. By analyzing the altimetry density in different areas of the Antarctic ice sheet, the final DEM resolution was determined to be 1000 meters. Considering the differences between the Prydz Bay and the inland regions of the Antarctic, the Antarctic ice sheet was divided into 16 sections. The best interpolation model and parameters were determined by semivariogram analysis, and the Antarctic ice sheet elevation data with a resolution of 1000 meters were generated by the Kriging interpolation method. The new Antarctic DEM was verified by two kinds of airborne lidar data and GPS data measured by multiple Antarctic expeditions of China. The results showed that the differences between the new DEM and the measured data ranged from 3.21 to 27.84 meters, and the error distribution was closely related to the slope.
HUANG Huabin
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
The DEMs of the typical glaciers on the Tibetan Plateau were provided by the bistatic InSAR method. The data were collected on November 21, 2013. It covered Puruogangri and west Qilian Mountains with a spatial resolution of 10 meters, and an elevation accuracy of 0.8 m which met the requirements of national 1:10 000 topographic mapping. Considering the characteristics of the bistatic InSAR in terms of imaging geometry and phase unwrapping, based on the TanDEM-X bistatic InSAR data, and adopting the improved SAR interference processing method, the surface DEMs of the two typical glaciers above were generated with high resolution and precision. The data set was in GeoTIFF format, and each typical glacial DEM was stored in a folder. For details of the data, please refer to the Surface DEMs for typical glaciers on the Tibetan Plateau - Data Description.
JIANG Liming
Ⅰ. Overview The SRTM (Space Shuttle Radar Topographic Mapping Mission) was performed by NASA, the Geospatial Intelligence Agency, and German and Italian space agencies in February 2002. A total of 222 hours and 23 minutes of data collection was performed by the US space shuttle Endeavour onboard the SRTM system, and 9.8 trillion bytes of radar images were collected between 60 degrees in North America and 56 degrees in south latitude with an area of more than 119 million km2 Data, Fei changed more than 80% of the earth's surface, this data set covers the entire territory of China. It took two years to process, and finally obtained a global digital elevation model (DEM) with a plane longitude of ± 20m and an elevation longitude of ± 16m. Ⅱ. Data processing description The processing of SRTM data is done by the Ground Data Processing System (GDPS). The GDPS consists of three parts: (1) an interferometric processor, which uses the interferometric processor to convert the data into elevation maps and radar image bands; (2) a mosaic processor, which is used to compile collected global airborne data Draw a mosaic map of continental elevation data and images; (3) Verification system is responsible for checking the quality of the mosaic map and providing accuracy maps. These processors are currently installed on JPL workstations, and the next step is to install them on a set of supercomputers for the systematic processing of real SRTM data. As this work progresses, JPL will release auxiliary data to the work. Ⅲ. Data content description SRTM data provides a file for each latitude and longitude grid. There are two types of longitude: 1 arc-second and 3 arc-second. Called SRTM1 and SRTM3, or 30m and 90m data. This dataset uses SRTM3 data with 90m resolution. Each file contains elevation data of 1201 × 1201 sampling points. The data format is DEM format. The spatial position of each picture frame is shown in the attached picture (1-25 thousand pictures in the country). Ⅳ. Data usage description SRTM data has computable and visual functions, and has broad application prospects in various fields, especially in the fields of surveying and mapping, surface deformation, and military. Specifically, it mainly includes the following aspects: In scientific research, SRTM data plays a very important role in geology, geophysics, seismic research, level modeling, volcano monitoring, and registration of remote sensing images. Using high-precision digital terrain elevation data to build a three-dimensional three-dimensional model of the ground, which is superimposed on the ground image, can observe slight changes in the earth's surface. In civil and industrial applications, SRTM data can be used for civil engineering calculations, reservoir dam site selection, land use planning, etc. In terms of communications, digital terrain data can help businesses build better broadcast towers and determine the best In terms of aviation safety, the use of SRTM digital elevation data can establish an enhanced aircraft landing alarm system, which greatly improves the aircraft landing safety factor. In the military, SRTM data is the basic information platform of C4ISR (Army Automatic Command System). It is necessary to study the structure of the battlefield, the direction of the battlefield, the presetting of the battlefield, the deployment of operations, the concentration of forces in the delivery, the protection conditions, and logistics support Essential.
XUE Xian, DU Heqiang
Digital Elevation Model (DEM) is a kind of solid ground Model that represents the ground Elevation in the form of a set of ordered numerical arrays. The third pole region of40°1′52″N~23°11′59″N、105°43′45″E~61°28′45″E of the roof of the world ecological geographic area,These include the qinghai-tibet plateau, the hengduan mountains, the Himalayas, the Hindu kush mountains and the pamirs plateau.Classified according to：At 4000 m altitude as a benchmark, the fusion of slope, reference mountain integrity and ecological system integrity, the spatial resolution of 0.008 ° x 0.008 °
National Aeronautics and Space Administration
Adopt aster with 30 meter resolution provided by Heihe project data management center GDEM data and 90 meter resolution SRTM data are two sets of grid data, as well as multi-source point data. These point data include radar point cloud elevation data in the middle and upper reaches; elevation data extracted from soil sample points and vegetation sample in the data management center of Heihe plan; elevation data extracted from climate and hydrological stations; and elevation sample data measured by the research group. By using the HASM scaling up algorithm, the grid data of different sources and different precision are fused with the elevation point data to obtain the high-precision DEM data of Heihe River Basin. First of all, the accuracy of two groups of grid data is verified by using various point data. According to the results of accuracy verification, different grid data are used as the trend surface of data fusion in different regions. The residuals of various point data and trend surface are calculated, and the residual surface is obtained by interpolation with HASM algorithm, and the trend surface and residual surface are superposed to obtain the final DEM surface. The spatial resolution is 500 meters.
YUE Tianxiang, ZHAO Na
DEM is the English abbreviation of Digital Elevation Model, which is the important original data of watershed topography and feature recognition.DEM is based on the principle that the watershed is divided into cells of m rows and n columns, the average elevation of each quadrilateral is calculated, and then the elevation is stored in a two-dimensional matrix.Since DEM data can reflect local topographic features with a certain resolution, a large amount of surface morphology information can be extracted through DEM, which includes slope, slope direction and relationship between cells of watershed grid cells, etc..At the same time, the surface flow path, river network and watershed boundary can be determined according to certain algorithm.Therefore, to extract watershed features from DEM, a good watershed structure pattern is the premise and key of the design algorithm. Elevation data map 1km data formed according to 1:250,000 contour lines and elevation points in China, including DEM, hillshade, Slope and Aspect maps. Data set projection: Two projection methods: Equal Area projection Albers Conical Equal Area (105, 25, 47) Geodetic coordinates WGS84 coordinate system
TANG Guoan
DEM (digital elevation model) is the abbreviation of digital elevation model, which is an important original data for watershed terrain and feature recognition. The principle of DEM is to divide the watershed into M rows and N columns of quadrilateral (cell), calculate the average elevation of each quadrilateral, and then store the elevation in a two-dimensional matrix. Because DEM data can reflect the local terrain features of a certain resolution, a large amount of surface morphology information can be extracted by DEM, which includes the slope, slope direction and the relationship between cells of watershed grid unit [7]. At the same time, the surface water flow path, river network and watershed boundary can be determined by certain algorithm. Therefore, to extract basin features from DEM, a good basin structure model is the premise and key of the design algorithm.
XU Zongxue, HU Litang, XU Maosen
ASTER Global Digital Elevation Model (ASTER GDEM) is a global digital elevation data product jointly released by National Aeronautics and Space Administration (NASA) and Japan's Ministry of Economy, Trade and Industry (METI) .The DEM data is based on the observation results of the new generation of Earth observation satellite TERRA Completed, it is produced by 1.3 million stereo pair data collected by ASTER (Advanced Space borne Thermal Emission and Reflection Radio meter) sensors, and its coverage area exceeds 99% of the earth's land surface. The data has a horizontal accuracy of 30 meters (95% confidence) and an elevation accuracy of 20 meters (95% confidence). This data is the third global elevation data, which is a significant improvement over the previous SRTM3 DEM and GTOPO30 data. ASTER GDEM released two versions. The first version was released in June 2009 and the second version was released in October 2011. Compared with the first version, the second version has make further progress in water coverage and deviation removal. The quality of the data has been greatly improved. This dataset is the second version of the ASTER GDEM dataset in the Shule River Basin, including DEM, mountain shadow, slope, and aspect data. Spatial resolution: 1 radian second (about 30 meters), accuracy: vertical accuracy of 20 meters, horizontal accuracy of 30 meters.
National Aeronautics and Space Administration
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