Numerical test: The climate model used is the regional climate model RegCM4.1. RegCM4.1 developed by the Italian Research Center for Theoretical Physics (ICTP). In the test of regional model simulation, the horizontal resolution of the atmospheric model is 50 km and the vertical direction is 18 layers; Online coupling sand dust module. Sea surface temperature The sea surface temperature interpolated by OISST is used. The test includes two groups: the Middle Paleocene topographic test (MP,~60Ma BP, test name 60ma_regcm4.1_xxx. nc) and the Late Oligocene (LO,~25Ma BP, test name 25ma_regcM4.1_xxx. nc) The MP regional terrain modification test removed the northern part of the plateau and approximately replaced the terrain distribution of Asian land during the 60Ma period. BP regional terrain modification test only removed the terrain of Pamirs Plateau, approximately replacing the terrain distribution of Asian land during the 25Ma period. The sand and dust source areas of the two tests have not changed, and the sand and dust circulation process has been opened online. Output time: All tests were integrated for 22 years, using the average results of the last 20 years of each test. The data can be used to explain the difference of drought evolution in different regions around the plateau.
SUN Hui
Topographic data of China Pakistan Economic Corridor and Tianshan Mountains are produced by Japan Aerospace Exploration Agency (JAXA). The 30m digital elevation model (DEM) (2006-2011) of China Pakistan Economic Corridor and Tianshan Mountains describes the ground elevation information, which is an important raw data for studying and analyzing terrain, watershed and feature recognition. It is widely used in surveying and mapping, hydrology, hydrology, meteorology, geomorphology, geology, soil, engineering construction and other fields of national economy as well as humanities and natural sciences. In terms of flood control and disaster reduction, DEM is the basis for hydrological analysis, such as catchment area analysis, water network analysis, rainfall analysis, flood storage calculation, inundation analysis, etc; At the same time, DEM data can reflect local terrain features with a certain resolution. Through DEM, a large amount of surface morphology information can be extracted, which can be used to draw contour lines, elevation maps, slope maps, water system maps, three-dimensional perspective maps, three-dimensional landscape maps, and used to make orthophotos, three-dimensional terrain models, and map revision. The horizontal resolution of the data is 30m (1 arc second), and the elevation accuracy is 5m. It is one of the most accurate terrain data in the world. The data download address is https://www.eorc.jaxa.jp/ALOS/en/aw3d30/data/ 。
QIU Haijun
The dataset includes three high-resolution DSM data as well as Orthophoto Maps of Kuqionggangri Glacier, which were measured in September 2020, June 2021 and September 2021. The dataset is generated using the image data taken by Dajiang Phantom 4 RTK UAV, and the products are generated through tilt photogrammetry technology. The spatial resolution of the data reaches 0.15 m. This dataset is a supplement to the current low-resolution open-source topographic data, and can reflect the surface morphological changes of Kuoqionggangri Glacier from 2020 to 2021. The dataset helps to accurately study the melting process of Kuoqionggangri Glacier under climate change.
LIU Jintao
The riverbed surface of the main channel in Nyangqu river is composed of gravel particles with wide grain size distribution. there are abundant gravel particles on the beach and riverbed. In this investigation, the bed surface grain size distribution of the main channel and tributaries of the Nyangqu river was measured. This data set contains the information of the five sampling locations in five main channels and two locations in tributaries of the Nyangqu River Basin (Table 1) and the bed surface grain size distribution (Table 2). The sampling locations were generally selected near the cross-section with obvious riverbed. It was considered that water flow through these sections in the straight channel for a long. At the same time, because it was a dry season, the bed grain size distribution on the river beach could be considered as the movement of gravel bedload carried by the last flood season. Therefore, it was considered that the bed grain size distribution in the sampling area on the river beach in the dry season was the bedload size distribution in the flood season. The grain size distributions were measured by the automatic identification method of full particle size based on image processing (e.g., Baserain software), with high identification accuracy of sediment particles is high. It is of great value to the scientific research on the evolution of source to sink process，bedlaod transport, and flood numerical simualtion， as well as the basic research on the flash flood prevention and control.
LUO Ming, HUANG Er, YAN Xufeng, MA Xudong, WANG Lu
The dataset based on synthesized data from 1114 sites across the Tibetan permafrost region which report that paleoclimate is more important than modern climate in shaping current permafrost carbon distribution.A new estimate of modern soil carbon stock to 3m depth on Tibetan permafrost region was derived by machine learning algorithm, including factors such as climate (paleoclimate and modern climate), vegetation, soil (soil thickness and soil physical and chemical properties, etc.) and topography. This dataset shows that ecosystem models clearly underestimated the Tibetan soil carbon stock, due to the absence of paleoclimate effects in the model. Future modelling of soil carbon cycling should include paleoclimate .
DING Jinzhi
The multi-scale dataset of environment and element-at-risk for the Qinghai-Tibet Plateau includes geomorphic data, normalized vegetation index data, annual temperature and rainfall data, and disaster bearing value grade data, covering an area of 6.56 million square kilometers. The data set is mainly prepared for disaster and risk assessment. Due to the huge coverage, the geomorphic data adopts 150m spatial resolution and other data adopts 1000m spatial resolution. Geomorphology, vegetation index, temperature and rainfall data are mainly produced by processing open source data, and disaster bearing value grade data are produced by superposition calculation, comprehensively considering population data, night light index, buildings and surface cover types.
TANG Chenxiao
The Cenozoic strata developed within and around the Tibetan Plateau, contain fruitful information on the tectonic evolution, paleoenvironment and paleoclimate changes. It's very significant on revealing the history of the uplift and deformation of the Tibetan Plateau and its relevant effects on the regional and even global environment and climate. This data set contains several well developed sections, which have been identified by the systematic geological survey. Depending on the tools (e.g. GPS, geological compass) in the fieldwork, we have finished the geological measurements and descriptions of these sections as well as the relevant geological maps. It includes a 90-m loess deposit of the Duikang section in the Linxia basin, several fluvial and lacustrine deposits (such as the 1890-m Dayu section in the Lunpola basin, the 300-m Shuanghe section in the Jianchuan basin, the 252-m Caijiachong section in the Qujing basin) and a 932-m saline lacustrine deposit with gypsolyte of the Jiangcheng section in the Simao basin. This data set provides a solid geological foundation for the following researches on stratigraphic chronology, tectonic evolution, paleoenvironment and paleoclimate, and so forth.
FANG Xiaomin , FANG Xiaomin, YAN Maodu, ZHANG Weilin, ZHANG Dawen
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
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
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
Through the investigation of tourist spots, tourist routes and tourist areas at different levels, form photos and video data of tourism resources, tourism services and tourism facilities of scenic spots, scenic spots, corridors and important tourism transportation nodes, tourism villages and tourism towns, record the tourism development status, find problems in tourism development, and form corresponding ideas for the construction of world tourism destinations; The data sources are UAV, tachograph and camera, mobile phone and GPS, and are divided into different folders according to scenic spots and data categories; The data has been checked for many times to ensure its authenticity; This data can provide a traceable basis for the construction of world tourism destinations on the Qinghai Tibet Plateau.
SHI Shanshan
On October 24, 2019 and June 9, 2021, the special group conducted UAV flight operations in the debris flow gullies of Jilong gully, Tianmo gully and Guxiang gully in Bomi County, Nyingchi City, Tibet Autonomous Region, and generated the real three-dimensional model and digital surface model (DSM) of the debris flow gully in the demonstration area; In 2020, he worked in Kada village, Bomi county and generated real 3D model, digital surface model, digital orthophoto (DOM) and digital elevation model (DEM); On June 9, 2021, it was operated again in guxianggou to obtain the real 3D model and digital surface model. The spatial resolution of the above products is about 0.1M, and the main processing methods are as follows: (1) The real scene 3D modeling method based on UAV remote sensing can obtain rich texture information and generate dense 3D point clouds by using UAV photogrammetry technology. Combined with automatic real scene 3D modeling technology, the real 3D scene can be obtained. (2) The obtained three-dimensional model is optimized by cavity repair and filtering, which effectively fills the water cavity in the three-dimensional model. (3) Based on 3D modeling, DSM data of the demonstration area can be directly generated in CC. (4) Use mapmatrix to interpolate the polygon of DSM, erase the height of vegetation and other ground objects, and get DEM data. (5) The accuracy of 3D modeling is optimized by pricking operation.
HUANG Fang , PENG Shuying
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 ages of glacial traces of the last glacial maximum, Holocene and little ice age in the Westerlies and monsoon areas were determined by Cosmogenic Nuclide (10Be and 26Al) exposure dating method to determine the absolute age sequence of glacial advance and retreat. The distribution of glacial remains is investigated in the field, the location of moraine ridge is determined, and the geomorphic characteristics of moraine ridge are measured. According to the geomorphic location and weathering degree of glacial remains, the relationship between the new and the old is determined, and the moraine ridge of the last glacial maximum is preliminarily determined. The exposed age samples of glacial boulders on each row of moraine ridges were collected from the ridge upstream. This data includes the range of glacier advance and retreat in Karakoram area during climate transition period based on 10Be exposure age method.
SHANG Cheng
This dataset is the Digital Elevation Model （DEM）in the Qilian Mountain， spatial resolution 30m. This dataset is based on the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model （ASTER-GDEM）. The data set has a vertical accuracy of 20 m and a horizontal accuracy of 30 m. Through the data download, preprocessing and splicing, the 30m×30m DEM data of Qilian Mountain is generated. This data set can extract a large amount of surface morphology information, which is an important basic data for terrain analysis and feature recognition in Qilian Mountain. The data will serve the ecological environment monitoring, ecological environmental protection and treatment project implementation, hydrology and water resources analysis and evaluation in Qilian Mountain area.
QI Yuan, ZHANG Jinlong, ZHOU Shengming, WANG Hongwei
The data is the large-scale DSM data of debris flow gully area generated by using the purchased resource No. 3 satellite remote sensing image of the demonstration area and based on the stereo image pair matching method. The processing method is as follows: (1) Due to the large amount of cloud and shadow noise in the original image, this study uses IDL language to develop and form a special denoising and information completion program for satellite images in cloudy mountainous areas. (2) The emmetropia correction image is used as the left image and the front view correction image is the right image. Envi is used for DSM production. (3) Using aster-dem data with 30 m resolution, at least 4 typical ground control points are selected for geographic correction to ensure that the geographic coordinate error is in the order of 1 ". (4) Cross entropy, root mean square error and area error information entropy are used as accuracy evaluation indexes. Compared with the DSM obtained from the original data, it is verified that the imaging accuracy of the processed DSM is improved.
HUANG Fang , PENG Shuying
Based on the distribution locations of the Qinghai toad-headed lizard (Phrynocephalus vlangalii) collected by field investigation and literature investigation, combined with five climate factors from WorldClim database, the current (1960-1990) and future (2061-2080) climate data were input into the trained species distribution model to predict the current and future suitable habitats. The prediction results shows that the lizard will lose a lot of original habitats under the climate change, and the protection measures for the lizard species should focus on the eastern margin of Qinghai-Tibet Plateau, the northern and eastern parts of Qaidam Basin. The model also predicts that after the climate change, new suitable habitats will appear in areas that were not suitable for the Qinghai toad-headed lizard. However, due to the very limited diffusion ability of reptiles (the maximum annual diffusion distance recorded in the literature is less than 500m), the newly emerging suitable habitats may not be used by the Qinghai toad-headed lizard. Meanwhile, based on the physiological, life history, behavior and morphological data of three altitudinal populations of the Qinghai toad-headed lizard collected by field work, and combined with microclimate data, the physiological consequences of climate change on the Qinghai toad-headed lizard in the current suitable distribution area were predicted by using the mechanism niche model. The prediction results of the model show that, whether in the SSP245 or SSP585 climate change scenarios, the activity time of the lizard will increase in most areas (> 93%) of the current suitable distribution area, and the thermal safety threshold will decrease in all places of the current suitable distribution area. The increase of activity time of high-altitude populations is less than that of low-altitude populations, but the decrease of thermal safety threshold is greater than that of low-altitude populations. The results reveal that climate change may have a greater impact on lizard populations in high altitude areas.
ZENG Zhigao
This data set is a digital elevation model of the Tibetan Plateau and can be used to assist in analysis and research of basic geographic information for the Tibetan Plateau. The raw data were the Shuttle Radar Topography Mission (SRTM) data, which were provided by Global Land Cover Network (GLCN), and the raw data were framing data , using the WGS84 coordinate system, including latitude and longitude, with a spatial resolution of 3″. After the mosaic processing, the Nodata (null data) generated in the mosaic process were interpolated and filled. After filling, the projection conversion process was performed to generate data as Albers equal area conical projection. After the conversion projection, the spatial resolution of the data was 90 m. Finally, the boundary of the Tibetan Plateau was used for cutting to obtain DEM data. This data table has two fields. Field 1: value Data type: long integer Interpretation: altitude elevation Unit: m Field 2: count Data type: long integer Interpretation: The number of map spots corresponding to the altitude elevation Data accuracy: spatial resolution: 90 m
Food and Agriculture Organization of the United Nations
The data is from JAXA earth observation research center（ http://www.eorc.jaxa.jp/ALOS/en/aw3d30/ ）The product is alos World 3D - 30m (aw3d30). Select and download the map by importing the SHP boundary of Sichuan Tibet traffic corridor, and merge it into one by using relevant software. The format is raster data, the spatial resolution is 30m, and the data size is 1.3GB. The DEM data can generate topographic factor data such as slope, aspect and river network by using relevant software. They are the basic data for topographic analysis of Sichuan Tibet traffic corridor, help to understand the geomorphic form of the basin, and are also the key factors for disaster zoning research and risk assessment. The acquisition of high-precision DEM is of great significance for disaster risk management and decision-making level and reducing the loss of major geological disasters.
SUI Tianbo
The data comes from radar topographic mapping SRTM product, and the download address is http://gdex.cr.usgs.gov/gdex/ 。 Import the SHP boundary of Sichuan Tibet traffic corridor on the download website to select the map within the study area and merge it into one by using ArcGIS software. The accuracy of the data is 90m, and the format is grid data. The data size is 136mb. The area is Sichuan Tibet traffic corridor. This data is applicable to the extraction of 1:100000 relevant topographic data, such as slope, aspect, river network and other topographic factor data. As the basic data for the topographic analysis of Sichuan Tibet traffic corridor, it is helpful to understand the topographic and geomorphic characteristics of the whole region and is of great significance to the disaster risk management and decision-making level of a large region.
WANG Lixuan
The SRTM (Shuttle Radar Topography Mission) data were obtained from the Endeavour space shuttle jointly launched by NASA and NIMA in February 2000. The SRTM system on the Endeavour had been collecting data for 222 hours and 23 minutes. It covered more than 80% of the global land surface from 60° north latitude to 56° south Latitude, including the whole territory of China. The radar image data acquired by the program have been processed for more than two years to form a digital terrain elevation model. The raw data of this data set were downloaded from the SRTM data distribution website (http://srtm.csi.cgiar.org). For the convenience of using the data, based on the framing of STRM data, we use Erdas software to splice and prepare the STMR mosaic of the Tibetan Plateau. The accuracy is 30 meters, and the data are in geoTIFF format. The raw data of this data set was downloaded from the SRTM data distribution website (http://srtm.csi.cgiar.org). The SRTM data provides a file for each latitude and longitude square. There are two kinds of longitude files, which are 1 arc-second and 3 arc-second, denoted SRTM1 and SRTM3, or 30-m and 90-m data. This data set comprises SRTM3 data with a resolution of 90 m, and the version is SRTM V4.1 (GeoTIFF format).
Food and Agriculture Organization of the United Nations（FAO）
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
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
The ASTER Global Digital Elevation Model (ASTER GDEM) is a global digital elevation data product jointly released by the National Aeronautics and Space Administration of America (NASA) and the Ministry of Economy, Trade and Industry of Japan (METI). The DEM data were based on the observation results of NASA’s new generation of Earth observation satellite, TERRA, and generated from 1.3 million stereo image pairs collected by ASTER (Advanced Space borne Thermal Emission and Reflection Radio meter) sensors, covering more than 99% of the land surface of the Earth. These data were downloaded from the ASTER GDEM data distribution website. For the convenience of using the data, based on framing the ASTER GDEM data, we used Erdas software to splice and prepare the ASTER GDEM mosaic of the Tibetan Plateau. This data set contains three data files: ASTER_GDEM_TILES ASTERGDEM_MOSAIC_DEM ASTERGDEM_MOSAIC_NUM The ASTER GDEM data of the Tibetan Plateau have an accuracy of 30 meters, the raw data are in tif format, and the mosaic data are stored in the img format. The raw data of this data set were downloaded from the ASTERGDEM website and completely retained the original appearance of the data. ASTER GDEM was divided into several 1×1 degree data blocks during distribution. The distribution format was the zip compression format, and each compressed package included two files. The file naming format is as follows: ASTGTM_NxxEyyy_dem.tif ASTGTM_NxxEyyy_num.tif xx is the starting latitude, and yyy is the starting longitude. _dem.tif is the dem data file, and _num.tif is the data quality file. ASTER GDEM TILES: The original, unprocessed raw data are retained. ASTERGDEM_MOSAIC_DEM: Inlay the dem.tif data using Erdas software, and parameter settings use default values. ASRERGDEM_MOSAIC_NUM: Inlay the num.tif data using Erdas software, and parameter settings use default values. The original raw data are retained, and the accuracy is consistent with that of the ASTERGDEM data distribution website. The horizontal accuracy of the data is 30 meters, and the elevation accuracy is 20 meters. The mosaic data are made by Erdas, and the parameter settings use the default values.
METI, National Aeronautics and Space Administration
This data set is mainly the SRTM terrain data obtained by International Center for Tropical Agriculture （CIAT）with the new interpolation algorithm, which better fills the data void of SRTM 90. The interpolation algorithm was adpoted from Reuter et al. (2007). SRTM's data organization method is as follows: divide a file into 24 rows (-60 to 60 degrees) and 72 columns (-180 to 180 degrees) in every 5 degrees of latitude and longitude grid, and the data resolution is 90 meters. Data usage: SRTM data are expressed as elevation values with 16-bit values (-/+/32767 m), maximum positive elevation of 9000m, and negative elevation (12000m below sea level). For null data use the -32767 standard.
Food and Agriculture Organization of the United Nations（FAO）
The data is vectorized from the national 1 ∶ 100W digital geological map spatial database. According to the regional scope of Sichuan Tibet traffic corridor and the division mode of 1:100w topographic map, the geological maps of h45, h46, H47, h48, i45, i46, I47 and i48 are used. The data source format is WP area file, which is converted into SHP format vector file by relevant software, which can be viewed and edited by arcigs software. This data contains basic geological information such as stratum, stratum symbol and rock type. The acquisition of geological data can basically understand the stratum and lithology within the scope of Sichuan Tibet traffic corridor, which is conducive to tracing the geological conditions of debris flow and landslide disasters.
WANG Lixuan
Based on China's daily meteorological elements data set and National Geographic basic data, the extreme precipitation, extreme temperature, drought intensity, drought frequency and other indicators in Hengduan Mountain area were calculated by using rclimdex, nspei and bilinear interpolation methods. The data set includes basic data set of disaster pregnant environment, basic data set of extreme precipitation index, basic data set of extreme temperature index, basic data set of drought intensity and frequency. The data set can provide a basic index system for regional extreme high temperature, precipitation and drought risk assessment.
SUN Peng
Hengduanshan multi-scale disaster causing, disaster pregnant and disaster bearing data spatiotemporal unified data set includes a series of geomorphic data derived from elevation data, annual average normalized vegetation index data, annual average temperature and rainfall data, and night light data of viirs. The geomorphological data cover Hengduanshan area, the vegetation and climate data cover the Qinghai Tibet Plateau, and the nighttime lamp index data cover the whole country. Data collection time varies according to different sources, with the earliest in 2000 and the latest in 2018. The data set is mainly prepared for disaster and risk assessment. In this data set, these data are processed by resampling, spatial correction, optical correction, geomorphic factor calculation, spatial statistics and other processes. The accuracy of the data is consistent with the original accuracy of the data source, and has not been processed by fuzzy processing such as downsampling. In the process of processing, the scientific standard process is used to distinguish continuous and discontinuous data, so as to minimize the data loss in the process of processing.
TANG Chenxiao
1) Data content (including elements and significance) This data set contains information of flow direction, accumulation of vector river network of Lancang Mekong River Basin. <br><br> 2) Data sources and processing methods In this data set, the remote sensing stream buring (RSSB) method (Wang et al., 2021) is adopted, and the high-precision elevation model MERIT-DEM and Sentinel-2 optical imagery are fused. <br><br> 3) Data quality description Validations show that this data set has high spatial accuracy (Wang et al, 2021). <br><br> 4) Data application achievements and Prospects This data set provides basic information of river networks, which can be used for hydrological model, land surface model, earth system model, as well as for mapping and spatial statistical analysis.
WANG Zifeng
1) Data content (including elements and significance) This data set contains information of flow direction, accumulation of vector river network of Lancang Mekong River Basin. <br><br> 2) Data sources and processing methods In this data set, the remote sensing stream buring (RSSB) method (Wang et al., 2021) is adopted, and the high-precision elevation model MERIT-DEM and Sentinel-2 optical imagery are fused. <br><br> 3) Data quality description Validations show that this data set has high spatial accuracy (Wang et al, 2021). <br><br> 4) Data application achievements and Prospects This data set provides basic information of river networks, which can be used for hydrological model, land surface model, earth system model, as well as for mapping and spatial statistical analysis.
WANG Zifeng
1) Data content (including elements and significance) This data set contains information of flow direction, accumulation of vector river network of Lancang Mekong River Basin. <br><br> 2) Data sources and processing methods In this data set, the remote sensing stream buring (RSSB) method (Wang et al., 2021) is adopted, and the high-precision elevation model MERIT-DEM and Sentinel-2 optical imagery are fused. <br><br> 3) Data quality description Validations show that this data set has high spatial accuracy (Wang et al, 2021). <br><br> 4) Data application achievements and Prospects This data set provides basic information of river networks, which can be used for hydrological model, land surface model, earth system model, as well as for mapping and spatial statistical analysis.
WANG Zifeng
The 10m level elevation data set of Yangon deep water port area is the DEM data of the main urban area of Yangon deep water port. DEM is the abbreviation of digital elevation model, which is the important original data of watershed terrain and feature recognition. The data set can reflect the local topographic features of the main urban area of Yangon deep-water port with 10m resolution. Therefore, a large amount of surface morphological information can be extracted from the data set, which includes the slope, aspect and the relationship between cells of the basin grid. It can provide accurate topographic data and reliable verification data for the study of the main urban area of Yangon deep-water port.
GE Yong, LI Qiangzi, LI Yi
This dataset is derived from the paper: Su, T. et al. (2019). No high tibetan plateau until the Neogene. Science Advances, 5(3), eaav2189. doi:10.1126/sciadv.aav2189 This data contains supplementary material of this article. Researchers discovered well-preserved palm fossil leaves from the Lunpola Basin (32.033°N, 89.767°E), central Tibetan Plateau at a present elevation of 4655 m in 2016. Researchers compared the newly discovered fossil with those present fossil that are most similar, find that there is no similar leaves among present fossil, therefore, researchers proposed the new species <em>S. tibetensis</em> T. Su et Z.K. Zhou sp. nov. Using the climate model, combined with the research of the fossil, researchers rebuilt the paleoelevation of the central Tibetan Plateau, it shows that a high plateau cannot have existed in the core of Tibet in the Paleogene. The data contains the following tables: 1) Table S1. Fossil records of palms around the world. 2) Table S2. Morphological comparisons between fossils from Lunpola Basin and modern palm genera. 3) Table S3. Climate ranges of 12 living genera that show the closest morphological similarity to <em>S. tibetensis</em> T. Su et Z.K. Zhou sp. nov. This dataset also contains the figures in the supplementary material in the article.
SU Tao
The data is clipped from "1: 1 million wetland data of China". "1: 1 million wetland data of China" mainly reflects the national marsh wetland information in the 2000s. It is expressed in geographic coordinates using the decimal degree. The main contents include: marsh wetland types, wetland water supply types, soil types, main vegetation types, geographical area, etc. Implemented the "Standard for Information Classification and Coding of Sustainable Development Information Sharing System of China". Data source of this database: 1:20 swamp map (internal version), Tibetan Plateau 1: 500,000 swamp map (internal version), swamp survey data 1: 1 million and national 1: 4 million swamp map; processing steps are: data source selection, preprocessing, digitization and encoding of marsh wetland elements, data editing processing, establishing topological relationships, edge processing, projection conversion, linking with attribute databases such as place names and obtaining attribute data.
ZHANG Shuqing
The data is clipped from "1: 1 million wetland data of China". "1: 1 million wetland data of China" mainly reflects the national marsh wetland information in the 2000s. It is expressed in geographic coordinates using the decimal degree. The main contents include: marsh wetland types, wetland water supply types, soil types, main vegetation types, geographical area, etc. Implemented the "Standard for Information Classification and Coding of Sustainable Development Information Sharing System of China". Data source of this database: 1:20 swamp map (internal version), Tibetan Plateau 1: 500,000 swamp map (internal version), swamp survey data 1: 1 million and national 1: 4 million swamp map; processing steps are: data source selection, preprocessing, digitization and encoding of marsh wetland elements, data editing processing, establishing topological relationships, edge processing, projection conversion, linking with attribute databases such as place names and obtaining attribute data.
ZHANG Shuqing
The data is clipped from "1: 1 million wetland data of China". "1: 1 million wetland data of China" mainly reflects the national marsh wetland information in the 2000s. It is expressed in geographic coordinates using the decimal degree. The main contents include: marsh wetland types, wetland water supply types, soil types, main vegetation types, geographical area, etc. Implemented the "Standard for Information Classification and Coding of Sustainable Development Information Sharing System of China". Data source of this database: 1:20 swamp map (internal version), Tibetan Plateau 1: 500,000 swamp map (internal version), swamp survey data 1: 1 million and national 1: 4 million swamp map; processing steps are: data source selection, preprocessing, digitization and encoding of marsh wetland elements, data editing processing, establishing topological relationships, edge processing, projection conversion, linking with attribute databases such as place names and obtaining attribute data.
ZHANG Shuqing
From 2012 to 2013, the geomorphic surface near the Zhengyi gorge in the middle reaches of the Heihe River was investigated, mainly including the 4-level river terrace. The data are mainly obtained through field investigation, and analyzed and mapped indoors to obtain the distribution map of geomorphic surface at all levels near the middle reaches of Zhengyi gorge.
HU Xiaofei, PAN Baotian
The landform near Qilian in the upper reaches of Heihe River includes the first level denudation surface (wide valley surface) and the Ninth level river terrace. The stage surface distribution data is mainly obtained through field investigation. GPS survey is carried out for the distribution range of all levels of geomorphic surface. The field data is analyzed in the room, and then combined with remote sensing image, topographic map, geological map and other data, the distribution map of all levels of geomorphic surface in the upper reaches of Heihe river is drawn. The age of the denudation surface is about 1.4ma, and the formation of Heihe terrace is later than this age, all of which are terraces since late Pleistocene.
HU Xiaofei, PAN Baotian
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
"Digital data including slope and aspect (slope and aspect) data are the basic data of GIS, and can be used as two important indicators to describe the terrain feature information, which can not only indirectly express the relief shape and structure of the terrain, It includes hydrological model, landslide monitoring and analysis, surface material movement, soil erosion, land use planning, etc The basic data of geoscience analysis model. At present, slope and aspect data are generally calculated by certain calculation model on digital elevation model (DEM). This data takes 34 key nodes of Pan third pole as the research area, takes DEM data with resolution of 30 meters as the base, realizes the digital simulation of slope and aspect in terrain data (that is, the digital expression of slope and aspect in terrain surface data), and finally obtains the slope and aspect data of pan third pole key nodes. The data area is 34 key nodes of Pan third pole (Abbas, Astana, Colombo, Gwadar, Mengba, Teheran, Vientiane, etc.).
SHANG Cheng
Chinese Cryospheric Information System is a comprehensive information system for the management and analysis of cryospheric data over China. The establishment of Chinese Cryospheric Information System is to meet the needs of earth system science, and provide parameters and verification data for the development of response and feedback models of permafrost, glacier and snow cover to global changes under GIS framework. On the other hand, the system collates and rescues valuable cryospheric data to provide a scientific, efficient and safe management and analysis tool. Chinese Cryospheric Information System selected three regions with different spatial scales as its main research areas to highlight the research focus. The research area along the Qinghai-Tibet highway is mainly about 700 kilometers long from Xidatan to Naqu, and 20 to 30 kilometers wide on both sides of the highway. The datasets of the Tibetan highway contains the following types of data: 1. Cryosphere data.Including: snow depth distribution. 2. Natural environment and resources.Include: Digital elevation topography (DEM) : elevation elevation, elevation zoning, slope and slope direction; Fundamental geology: Quatgeo 3. Boreholes: drilling data of 200 boreholes along the qinghai-tibet highway. Engineering geological profile (CAD) : lithologic distribution, water content, grain fraction data, etc 4. Model of glacier mass equilibrium distribution along qinghai-tibet highway: prediction of frozen soil grid data. The graphic data along the qinghai-tibet highway includes 13 map scales of 1:250,000.The grid size is 100×100m. For details, please refer to the documents (in Chinese): "Chinese Cryospheric Information System design. Doc", "Chinese Cryospheric Information System data dictionary. Doc", "Database of the Tibetan highway. Doc".
LI Xin
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 data set contains the slope aspect (resolution: 30 m) factor affecting soil erosion on the Loess Plateau and the slope aspect data extracted from the elevation data of the Loess Plateau. Each theme map is divided into frames according to the 1:250000 scale standard map cartography method, and the frames are denoted by the 1:250000 scale standard map cartography number. The geographical coordinate is WGS1984; the accuracy can meet the requirements of regional scale hydrology and soil erosion analysis and forecasting.
LIU Baoyuan, SHI Haijing
This data set contains the digital slope aspect distribution and slope aspect degree data of the Tibetan Plateau, which can be used to assist in basic geographic information analysis and research work on the Tibetan Plateau region. The raw data were the Shuttle Radar Topography Mission (SRTM) data provided by Global Land Cover Network (GLCN) using the WGS84 coordinate system, and the raw data were framing data, including latitude and longitude data, with a spatial resolution of 3″. After the mosaic processing, the Nodata (null data) generated in the mosaic process were interpolated and filled, and after filling, a projection conversion process was performed to generate an equal-area conical projection of the data bit Albers, after conversion projection, the spatial resolution was 90 m. Finally, the boundary of the Tibetan Plateau was used for cutting to obtain DEM data. Use the spatial analysis module under ArcMap to calculate the slope aspect and generate the slope aspect map. Pixel data: value Data type: floating point Interpretation: slope degree Dimension: degree Data accuracy: spatial resolution 90 m
GLCN
This data set contains the digital slope distribution and slope degree data of the Tibetan Plateau, which can be used to assist in basic geographic information analysis and research work on the Tibetan Plateau region. The raw data were the Shuttle Radar Topography Mission (SRTM) data provided by Global Land Cover Network (GLCN) using the WGS84 coordinate system, and the raw data were framing data, including latitude and longitude data, with a spatial resolution of 3″. After the mosaic processing, the Nodata (null data) generated in the mosaic process were interpolated and filled, and after filling, a projection conversion process was performed to generate an equal-area conical projection of the data bit Albers, after conversion projection, the spatial resolution was 90 m. Finally, the boundary of the Tibetan Plateau was used for cutting to obtain DEM data. Use the spatial analysis module under ArcMap to calculate the slope aspect and generate the slope map. Field: value Data type: floating point Interpretation: slope degree Dimension: degree Data accuracy: spatial resolution 90 m
Food and Agriculture Organization of the United Nations
DEM data of economic corridors in Silk Road can reflect the altitude of the six economic corridors, the unit is meter(m). The spatial resolution of the data is 0.016 degrees, which is about 1.8km. The longitude range is 12.09°E-180°, and the latitude range is 10.99°S-90°N. The source is derived from the Global Relief Model built by the National Oceanic and Atmospheric Administration of the United States (NOAA). The range is cut by the border of the Silk Road. This data is one of the basic data necessary to assess the risks of natural disasters (including debris flows, landslides, flash floods, etc.) in the six economic corridors. The application frequency will be high and the prospects will be broad.
The National Oceanic and Atmospheric Administration of the United States (NOAA), ZOU Qiang
Slope data of economic corridors in Silk Road can reflect the degree of steepness of the surface units of the six major economic corridors, the unit is degree (°). The spatial resolution of the data is 0.016 degrees, which is about 1.8km. The longitude range is 12.09°E-180°, and the latitude range is 10.99°S-90°N. The source is derived from the Global Relief Model built by the National Oceanic and Atmospheric Administration of the United States (NOAA). The range is cut by the border of the Silk Road. This data is one of the basic data necessary to assess the risks of natural disasters (including debris flows, landslides, flash floods, etc.) in the six economic corridors. The application frequency will be high and the prospects will be broad.
ZOU Qiang
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