The integration of geomorphological information in western China was completed by a team led by Dr. Xie Chuanjie, Institute of Geography, Resources and Environment, Chinese Academy of Sciences. These include the national geomorphological database of 1: 4 million and the western geomorphological database of 1: 1 million. The geomorphological data of 1: 4 million are tracked, collected and collated by the Geography Department of the National Planning Commission of the Chinese Academy of Sciences, "China Geomorphological Map (1: 4 million)" edited by Li Bingyuan and "Geomorphological Map of China and Its Adjacent Areas (1: 4 million)" edited by Chen Zhiming. Scan and register the data, vectorize all registered maps by ArcMap software, and establish their own classification and code systems. Geomorphological types are divided into basic geomorphological types and morphological structure types (point, line and surface representation) according to map spots (common staining) and symbols. Data are divided into structural geomorphology and morphological geomorphology. Projection information: Projection: Albers False_Easting: 0.000000 False_Northing: 0.000000 Central_Meridian: 105.000000 Standard_Parallel_1: 25.000000 Standard_Parallel_2: 47.000000 Latitude_Of_Origin: 0.000000 Linear Unit: Meter (1.000000) Geographic Coordinate System: datumg Angular Unit: Degree (0.017453292519943299) Prime Meridian: <custom> (0.000000000000000000) Datum: D_Krasovsky_1940 Spheroid: Krasovsky_1940 Semimajor Axis: 6378245.000000000000000000 Semiminor Axis: 6356863.018773047300000000 Inverse Flattening: 298.300000000000010000
CHENG Weiming, ZHOU Chenghu
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
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
Ⅰ. this data Compilation: Lanzhou Desert Research Institute, Chinese Academy of Sciences Publication: Map Publishing House, Map Printing House Issue: Xinhua Bookstore Beijing Publishing House Ⅱ. The 1: 1.5 million Taklimakan Desert Aeolian Landform Map includes: 1. aeolian _ landform _ taklimakan _ 150 (aeolian landform) 2, height (dune height) 3, lake (lake) 4river1, 2, 3 (river), 5, road1, 2, 3 (road) Ⅲ. aeolian landform attribute fields: Aeolian_c (attribute), Aeolian_ (English control), Code (attribute code) Classification codes of geomorphic data attributes are as follows: (a), sand landform types 111. Ridge-shaped Compound Sand Mountain 112. Compound crescent dunes and dune chains 113. Pyramid dunes 114. Crescent dunes and dune chains 115, lattice sand dune and lattice sand dune chain 116, wind erosion residual hills 117. Compound Sand Ridge 118. Dome dunes 119. Fish Scale Sand Dunes 120, crescent sand ridges and linear sand ridges 121, red willow sandbags 122. Gobi (b) Sand dune height types 211, less than 10 meters 212, 10-25m 213, 25-50m 214, 50-100m 215, more than 100 meters (3) Other types 311, woodland and shrub forest 312. Artificial Oasis 313. Saline-alkali Land and Swamp Iv. projection information: Angular Unit: Degree (0.017453292519943295) Prime Meridian: Greenwich (0.000000000000000000) Datum: D_Beijing_1954 Spheroid: Krasovsky_1940 Semimajor Axis: 6378245.000000000000000000 Semiminor Axis: 6356863.018773047300000000 Inverse Flattening: 298.300000000000010000
WANG Jianhua
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 Trimble 5800 GPS was used to measure the carrier phase of the terrace surface in real time, and the elevation data of the terrace surface was obtained.The deformation characteristics and amplitude of the terrace are analyzed.The data include the deformation of landform near zhengyi gorge in the middle reaches of heihe river and the deformation of landform near yingluo gorge in the upper reaches of heihe river.
PAN Baotian, HU Xiaofei
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
"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. Comprehensive ecological and hydrological Atlas of Heihe River Basin: the main geomorphic form and genetic type of Heihe River Basin, scale 1:2500000, positive axis and equal conic projection, standard latitude: 25 47 n. Data source: 1:1 million landform data of Heihe River Basin, river data of Heihe River Basin, residential area data of Heihe River Basin, administrative boundary data of Heihe River Basin.
WANG Jianhua, ZHAO Jun, WANG Xiaomin, FENG Bin
The dataset contains all individual glacial storage (unit: km3) over the Qinghai-Tibetan Plateau in 1970s and 2000s. It is sourced from the resultant data of the paper entitled "Consolidating the Randolph Glacier Inventory and the Glacier Inventory of China over the Qinghai-Tibetan Plateau and Investigating Glacier Changes Since the mid-20th Century". The first draft of this paper has been completed and is planned to be submitted to Earth System Science Data journal. The baseline glacier inventories in 1970s and 2000s are the Randolph Glacier Inventory 4.0 dataset, and the Glacier Inventory of China, respectively. Based on the individual glacial boundaries extracted from the above-mentioned two datasets, the grid-based bedrock elevation dataset (https://www.ngdc.noaa.gov/mgg/global/global.html, DOI: 10.7289/v5c8276m), and the glacier surface elevation obtained by a slope-dependent method, the individual glacier volumes in 1970s and 2000s are then calculated. In addition, the calculated results of individual glacier volumes in this study have been compared and verified with the existent results of several glacier volumes, relevant remote sensing datasets, and the global glacier thickness dataset based on the average of multiple glacier model outputs (https://www.research-collection.ethz.ch/handle/20.500.11850/315707, doi:10.3929/ethz-b-000315707), and the errors in the calculations have also been quantified. The established dataset in this study is expected to provide the data basis for the future regional water resources estimation and glacier ablation-involved researches. Moreover, the acquisition of the data also provides a new idea for the future glacier storage estimation.
HU Xiaofei, PAN Baotian
"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. Comprehensive atlas of ecological hydrology of Heihe River Basin: topographic map of Heihe River Basin, scale 1:2500000, positive axis isometric conic projection, standard latitude: 25 47 n. Data source: 1:1 million landform data of Heihe River Basin, river data of Heihe River Basin, residential area data of Heihe River Basin, administrative boundary data of Heihe River Basin. According to the distribution, topography and topography of Heihe River Basin, it can be divided into four areas: high mountain area of Qilian Mountain, plain area of Hexi Corridor, middle mountain area of North Mountain of corridor and Ejina Basin.
ZHAO Jun, WANG Xiaomin, FENG Bin
"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. Comprehensive atlas of ecological hydrology of Heihe River Basin: landform type map of Heihe River Basin, scale 1:2500000, positive axis isometric conic projection, standard latitude: 2547 n. Data source: 1 million topographic map of Heihe River Basin, administrative boundary data of Heihe River Basin, river data set of Heihe River Basin, residential area data of Heihe River Basin and other basic data.
ZHAO Jun, WANG Xiaomin, FENG Bin
The data from the Digital Mountain Map of China depicts the spatial pattern and complex morphological characteristics of mountains in China from a macro scale, including the mountains’ spatial distribution, classification, morphological elements and area ratio. It is a set of basic data that can be used for mountain zoning, mountain genetic classification and resource environment correlation analysis. Mountains carry great natural resource supply, provide ecological service and regulation functions, and play an important part in eco-civilization construction and socioeconomic development in China. Lately,Prof. Li Ainong of the Institute of Mountain Hazards and Environment, CAS, developed this data set based on the spatial definition of mountains, an a topography adaptive slide window method for the relief amplitude. The data include: (1) Spatial distribution of mountains in China; (2) Mountain classification; (3) Main mountain ranges (with range alignment, relief grade and ridge morphology); (4)Main mountain peaks; (5)Mountain proportion table of the provinces/autonomous regions/municipalities of China; (6) Contour zoning data; (7) General situation of mountain formation; (8)Mountain division and zoning data; (9) List of main mountain peaks. The spatial resolution of the original DEM source is about 90m. And the boundaries of mountains have been revised with multisource remote sensing data, which has good spatial consistency with the relief shading map. The cartographic generalization accuracy of mountain ranges and relevant features is 1:1 000 000. Mountain features in this data set have higher spatial resolution and pertinence, which are available for the zonality of mountain environment and mountain hazards, and the spatial analysis for ecological, production and living spaces in mountain areas, surpporting macro decision-making on mountain areas' development in China. p
NAN Xi , LI Ainong , DENG Wei
1) Data content: this data set is the landslide disaster data of Sanjiang Basin in the southeast of Qinghai Tibet Plateau; 2) Data source and processing method: this data set was independently interpreted by Dai Fuchu of Beijing University of technology using Google Earth; This data file is finally formed by remote sensing interpretation - on-site verification - re interpretation - re verification and other methods after 7 systematic interpretation. More than 5000 landslides have been verified on site with high accuracy; 4) This data has broad application prospects for hydropower resources development, traffic engineering construction and geological disaster evaluation in the three river basins in the southeast of Qinghai Tibet Plateau.
DAI Fuchu
Paleo-shorelines are widely developed in the lakes of the Tibetan Plateau (TP), which record the history of paleo-lake level changes. The development age of the mega-lake represented by the highest paleo-shoreline is controversial. The age of the shoreline or the mega-lake can be obtained by measuring the burial age of the shoreline sand in the sedimentary strata of the paleo-shoreline by using the optical stimulated luminescence (OSL) dating technology. This data includes the OSL ages of the highest paleo-shorelines of three lakes in the northwestern TP. The dating is based on the K-feldspar pIRIR method developed in recent years, which effectively solves the problem that the quartz OSL signal is not suitable for dating in the study area. This data can provide key information for the evolution history of the mega-lakes on the TP.
ZHAO Hui, ZHANG Shuai, SHENG Yongwei
The Central Asia West Asia economic corridor is dominated by deserts, mountains and plateaus, with an average altitude of about 1000m. The climate is extremely arid, the desert distribution area is large, the ecology is fragile, the dry and hot season lasts for a long time, up to 7 months, and the annual average rainfall is only 150mm at most. There are great differences in natural environment and complex geological conditions in the area. Under the compound driving action of regional differentiated structure, earthquake, meteorology, hydrology and ecology, debris flow and landslide are widely distributed in the corridor. Based on remote sensing images, the landslide and debris flow disasters in China Central Asia West Asia economic corridor are interpreted. Statistics show that 303 landslides and 2159 debris flow disasters are developed in China Central Asia West Asia economic corridor. Debris flows mainly include freeze-thaw debris flow, ice water debris flow and rainstorm debris flow.
ZOU Qiang
1) In mountainous areas, due to the complex topographic and geological background conditions, landslides are very easy to occur triggered by external factors such as rainfall, snow melting, earthquake and human engineering activities, resulting in the loss of life and property and the destruction of the natural environment. In order to meet the safety of project site construction, the rationality of land use planning and the urgent needs of disaster mitigation, it is necessary to carry out regional landslide sensitivity evaluation. When many different evaluation results are obtained by using a variety of different methods, how to effectively combine these results to obtain the optimal prediction is a technical problem that is still not difficult to solve at present. It is still very lack in determining the optimal strategy and operation execution of the optimal method for landslide sensitivity evaluation in a certain area. 2) Using the traditional classical multivariate classification technology, through the evaluation of model results and error quantification, the optimal evaluation model is combined to quickly realize the high-quality evaluation of regional landslide sensitivity. The source code is written based on the R language software platform. The user needs to prepare a local folder separately to read and store the software operation results. The user needs to remember the folder storage path and make corresponding settings in the software source code. 3) The source code designs two different modes to display the operation results of the model. The analysis results are output in the standard format of text and graphic format and the geospatial mode that needs spatial data and is displayed in the standard geographic format. 4) it is suitable for all people interested in landslide risk assessment. The software can be used efficiently by experienced researchers in Colleges and universities, and can also be used by government personnel and public welfare organizations in the field of land and environmental planning and management to obtain landslide sensitivity classification results conveniently, quickly, correctly and reliably. It can serve regional land use planning, disaster risk assessment and management, disaster emergency response under extreme induced events (earthquake or rainfall, etc.), and has great practical guiding significance for the selection of landslide monitoring equipment and the reasonable and effective layout and operation of early warning network. It can be popularized and applied in areas with serious landslide development
YANG Zhongkang
The data is 1:4 million geomorphic type data of the Qinghai Tibet Plateau. The geomorphic map can express the results of geomorphic research and is an important method to study geomorphology. It plays an important role in geomorphology and the continuous development of geomorphic research. The data includes two parts. SHP data comes from China's 1:4 million morphological and geomorphic map, and the spatial scope is in China; Grid data is from USGS( https://rmgsc.cr.usgs.gov/outgoing/ecosystems/Global/ ), the spatial scope extends to the Qinghai Tibet Plateau and adjacent mountainous areas, including some overseas areas. The vector data consists of 1:4 million morphological geomorphic map, which is scanned, registered and vector digitized. During digitization, the accuracy is guaranteed to be within 2 pixels. The grid data is obtained through spatial calibration, accuracy verification and cutting. The detailed data processing process can be seen https://onlinelibrary.wiley.com/doi/full/10.1111/tgis.12265 。
YANG Yaping
1) The work of automatically dividing a wide and complex geospatial area or even a complete watershed into repeatable and geomorphically consistent topographic units is still in the stage of theoretical concept, and there are great challenges in practical operation. Terrain unit is a further subdivision of topography and geomorphology, which can ensure the maximum uniformity of geomorphic features in slope unit and the maximum heterogeneity between different units. It is suitable for geomorphic or hydrological modeling, landslide detection in remote sensing images, landslide sensitivity analysis and geological disaster risk assessment. 2) Slope unit is an important type of topographic unit. Slope unit is defined as the area surrounded by watershed and catchment line. In fact, the area surrounded by watershed and catchment line is often multiple slopes or even a small watershed. Theoretically, each slope unit needs to ensure the maximum internal homogeneity and the maximum heterogeneity between different units. The slope unit is an area with obviously different topographic characteristics from the adjacent area. These topographic characteristics can be based on the characteristics of catchment or drainage boundary, slope and slope direction, such as ridge line, valley line, platform boundary, valley bottom boundary and other geomorphic boundaries. According to the high-precision digital elevation model, the slope unit with appropriate scale and quality can be drawn manually, but the manual drawing method is time-consuming and error prone. The quality of the divided slope unit depends on the subjective experience of experts, which is suitable for small-scale areas and has no wide and universal application value. Aiming at the gap in practical operation in this field, we propose an innovative modeling software system to realize the optimal division of slope units. Automatic division system of slope unit based on confluence analysis and slope direction division v1 0, written in Python programming language, runs and calculates as the grass GIS interpolation module, and realizes the automatic division of slope units in a given digital elevation data and a set of predefined parameters. 4) Based on python programming language, the code is flexible and changeable, which is suitable for scientific personnel with different professional knowledge to make a wide range of customization and personalized customization. In addition, the software can provide high-quality slope unit division results, reflect the main geomorphic characteristics of the region, and provide a based evaluation unit for fine landslide disaster evaluation and prediction. It can serve regional land use planning, disaster risk assessment and management, disaster emergency response under extreme induced events (earthquake or rainfall, etc.), and has great practical guiding significance for the selection of landslide monitoring equipment and the reasonable and effective layout and operation of early warning network. It can be popularized and applied in areas with serious landslide development.
YANG Zhongkang
The gridded desertification risk data of The Arabian Peninsula in 2021 was calculated based on the environmentally sensitive area index (ESAI) methodology. The ESAI approach incorporates soil, vegetation, climate and management quality and is one of the most widely used approaches for monitoring desertification risk. Based on the ESAI framework, fourteen indicators were chosen to consider four quality domains. Each quality index was calculated from several indicator parameters. The value of each parameter was categorized into several classes, the thresholds of which were determined according to previous studies. Then, sensitivity scores between 1 (lowest sensitivity) and 2 (highest sensitivity) were assigned to each class based on the importance of the class’ role in land sensitivity to desertification and the relationships of each class to the onset of the desertification process or irreversible degradation. A more comprehensive description of how the indicators are related to desertification risk and scores is provided in the studies of Kosmas (Kosmas et al., 2013; Kosmas et al., 1999). The main indicator datasets were acquired from the Harmonized World Soil Database of the Food and Agriculture Organization, Climate Change Initiative (CCI) land cover of the European Space Agency and NOAA’s Advanced Very High Resolution Radiometer (AVHRR) data. The raster datasets of all parameters were resampled to 500m and temporally assembled to the yearly values. Despite the difficulty of validating a composite index, two indirect validations of desertification risk were conducted according to the spatial and temporal comparison of ESAI values, including a quantitative analysis of the relationship between the ESAI and land use change between sparse vegetation and grasslands and a quantitative analysis of the relationship between the ESAI and net primary production (NPP). The verification results indicated that the desertification risk data is reliable in the Arabian Peninsula in 2021.
XU Wenqiang
The ups and downs of the earth's surface become landforms. This data set is geomorphic data within the Sichuan Tibet traffic corridor area with an accuracy of 90m, and the data format is TIF. The data is digitized from the geomorphic Atlas of the people's Republic of China (1:1 million). The landforms of plains, hills and platforms are classified according to altitude and fluctuation. The accuracy of the data is low, and there are few types of landforms in the study area. The regional combination and vertical differentiation of various landforms are not only closely related to the changes of climate and hydrology and the distribution of soil and organisms, but also have a significant impact on industrial and agricultural production, water conservancy and transportation construction, but also an important factor that must be considered in the evolution and management of ecological environment.
WANG Lixuan
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