The project “The impact of the frozen soil environment on the construction of the Qinghai-Tibet Railway and the environmental effects of the construction” is part of the “Environmental and Ecological Science in West China” programme supported by the National Natural Science Foundation of China. The person in charge of the project is Wei Ma, a researcher at the Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences. The project ran from January 2002 to December 2004. Data collected in this project included the following: Monitoring data of the active layer in the Beiluhe River Basin (1) Description of the active layer in the Beiluhe River Basin (2) Subsurface moisture data from the Beiluhe River Basin, 2002.9.28-2003.8.10 (Excel file) * Site 1 - Grassland moisture data * Site 2 – Removed turf moisture data * Site 3 - Natural turf moisture data * Site 4 - Gravel moisture data * Site 5 - Insulation moisture data (3) Subsurface temperature data from the Beiluhe River Basin, 0207-0408 Excel file * Temperature data for the ballast surface * Temperature data for insulation materials * Temperature data for a surface without vegetation * Temperature data for a grassland surface * Temperature data for a grit and pebble surface Data on the impact of construction on the ecological environment were obtained at Fenghuoshan, Tuotuohe, and Wudaoliang. Sample survey included plant type, abundance, community coverage, total coverage, aboveground biomass ratio and soil structure. The moisture content at different depths of the soil was detected using a time domain reflectometer (TDR). A set of soil samples was collected at a depth of 0-100 cm at each sample site. An EKKO100 ground-penetrating radar detector was used to continuously sample 1-1.5 km long sections parallel to the road to determine the upper limit depth of the frozen soil. 3. Predicted data: The temperature of the frozen soil at different depths and times was predicted in response to temperature increases of 1 degree and 2 degrees over the next 50 years based on initial surface temperatures of -0.5, -1.5, -2.5, -3.5, and -4.5 degrees. 4. The frozen soil parameters of the Qinghai-Tibet Railway were as follows: location, railway mileage, total mileage (km), frozen soil type mileage, mileage of zones with an average temperature conducive to permafrost, frozen soil with high temperatures and high ice contents, frozen soils with high temperatures and low ice contents, frozen soils with low temperatures and high ice contents, frozen soils with low temperatures and low ice contents, and melting area.
MA Wei, WU Qingbai
This data is digitized from the "Zhangye Land Use Status Map" of the drawing. This map is a key scientific and technological research project of the "Seventh Five-Year Plan" of the country: "Three North" Shelter Forest Remote Sensing Comprehensive Survey, and one of the series maps of Ganqingning Type Area. The information is as follows: * Chief Editor: Wang Yimou * Deputy Editors: Feng Yushun, You Xianxiang, Shen Yuancun * Editors: Wang Xian, Wang Jingquan, Qiu Mingxin, Quan Zhijie, Mou Xindai, Qu Chunning, Yao Fafen, Qian Tianjiu, Huang Autonomy, Mei Chengrui, Han Xichun, Li Yujiu, Hu Shuangxi * Responsible Editor: Huang Meihua * Manuscript: Mou Xin-shi, Cui Sai-hua, Wang Xian. He Shouhua * Compiling: He Shouhua, Wang Xian, Quan Zhijie, Cui Saihua, Long Yaping, Mu Xinshi, He Shouhua, Mao Xiaoli, Cui Saihua, Wang Changhan * Editors: Feng Yushun and Wang Yimou * Qing Hua: Feng Yushun, Zhang Jingqiu, Yang Ping * Cartography: Feng Yushun, Yao Fafen, Wang Jianhua, Zhao Yanhua, Li Weimin * Cartographic unit: compiled by Desert Research Office of Chinese Academy of Sciences * Publishing House: Xi 'an Map Publishing House * Scale: 1: 500000 * Publication time: not yet available 1. File Format and Naming Data is stored in ESRI Shapefile format, including the following layers: Zhang Ye's landuse Map, River, Road, 2. Data Fields and Attributes Type number type face desert Paddy field 12 Irrigated field 13 dryland Non-irrigated field 131 Plain non-irrigated field Valley non-irrigated field Slope non-irrigated field, 133 slope dryland 134 dryland Terrace non-irrigated field ................. Please refer to the data document for details. 3. 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 Yimou, YOU Xianxiang, SHEN Yuancun, FENG Yusun, WANG Xian, YAO Fafen, SHEN Yuancun, FENG Yusun, WANG Jianhua
This dataset: Editor-in-Chief: Hou Xueyu Drawing: Hou Xueyu, Sun Shizhou, Zhang Jingwei, He Miaoguang. Wang Yifeng, Kong Dezhen, Wang Shaoqing Publishing: Map Press Issue: Xinhua Bookstore Year: 1979 Scale: 1: 4,000,000 It took five years to complete from May 1972 to July 1976. In the process of drawing legends and mapping, referring to the vast majority of vegetation survey data (including maps and texts) after 1949 in China, we held more than a dozen mapping seminars involving researchers from inside and outside the institute. During the layout after the mapping work was completed, many new survey data were added, especially vegetation data in western Tibet. The nature of this map basically belongs to the current vegetation map, including two parts of natural vegetation and agricultural vegetation. The legend of natural vegetation is arranged according to the seven vegetation groups. They are mainly divided according to the appearance of plant communities and certain ecological characteristics. The concept of agricultural vegetation community, like the natural vegetation community, also has a certain life form (appearance, structure, layer), species composition and a certain ecological location. In 1990, the State Key Laboratory of Resources and Environmental Information Systems of the Institute of Geographical Sciences and Resources, Chinese Academy of Sciences completed the digitization of this map, and wrote relevant data description documents. The digitized data also adopt equal product cone projection and can be converted into other projections by GIS software. This data includes a vector file in e00 format, a Chinese vegetation coding design description, a dataset description, a vegetation data layer attribute data table, and a scanned "People's Republic of China Vegetation Map-Brief Description" and other files. Data projection: Projection: Albers false_easting: 0.000000 false_northing: 0.000000 central_meridian: 110.000000 standard_parallel_1: 25.000000 standard_parallel_2: 47.000000 latitude_of_origin: 0.000000 Linear Unit: Meter (1.000000) Geographic Coordinate System: Unknown Angular Unit: Degree (0.017453292519943299) Prime Meridian: Greenwich (0.000000000000000000) Datum: D_Unknown Spheroid: Clarke_1866 Semimajor Axis: 6378206.400000000400000000 Semiminor Axis: 6356583.799999999800000000 Inverse Flattening: 294.978698213901000000
HOU Xueyu, SUN Shizhou, ZHANG Jingwei, HE Miaoguang, WANG Yifeng, KONG Dezhen, WANG Shaoqing
The project on the impact of agricultural development in northwest Lvzhou on watershed scale water cycle and eco-environmental effects belongs to the major research program of "Environmental and Ecological Science in Western China" sponsored by the National Natural Science Foundation. The person in charge is Professor Kang Shaozhong of Northwest China Agriculture and Forestry University. The project runs from January 2003 to December 2005. Data collected from this project: soil experimental data of Shiyang River Basin, including: 1. Saturated hydraulic conductivity (excel table): includes four fields: number, sampling point, measured value and saturated hydraulic conductivity. 2. Conductivity (excel table): including number, sampling point, measured value, temperature, temperature correction value and conductivity. 3. Original indoor infiltration data (excel table): including number, time, cumulative value and reading. 4. Field Infiltration Data (excel Form): Including Number, Time, Cumulative Value and Reading. 5. Sampling point of horizontal infiltration data (excel form): including time, measuring cylinder (ml), wetting peak (ml), wet weight, dry weight, box weight and distance. 6. soil particle analysis (excel form): including numbers, > 0.25 mm, < 0.05 mm, < 0.01 mm, < 0.005 mm, < 0.001 mm. 7. Soil moisture characteristic curve (excel table): including soil weight and drying weight when the pressure of pressure membrane instrument is 0,0.05,0.1,0.3,0.5,0.8,1.5,3,5,14.4. 8. Organic matter (excel form): including number, sampling point, amount of soil taken (G), titration amount (ml) 9. Sampling Point Coordinates (excel Form)
KANG Shaozhong
The project studying the evolution pattern and development trend of the arid environment in western China was a major research component of the project Environmental and Ecological Science for West China, which was funded by the National Natural Science Foundation of China. The leading executive of the project was Academician Zhisheng An from the Institute of Earth Environment of the Chinese Academy of Sciences. The project ran from January 2002 to December 2004. The data collected by the project include the following: 1. History and variability data for arid regions in western China: 1) Chinese Loess Plateau mass accumulation rate data (3600-0 kyr BP): Fields include age and mass accumulation rate (MAR) (txt file). 2) Chinese Loess Plateau grain size and magnetic susceptibility data (3600-0 kyr BP): Fields include age, stacked mean grain size, and stacked magnetic susceptibility (txt file). 2. Sporopollen content data of different loess strata since 12 kyr BP in the Yaozhou District of Shanxi Province (excel table): The distributions of 27 species of sporopollen (0-397 cm) from 67 different layers of loess samples are included. 3. 10Be record data (table) 10Be concentration, magnetic susceptibility and bulk density data of loess with different thicknesses (79.67- 0.09 kyr BP). 4. Simulation data on the modulation of the East Asian monsoon resulting from orbital variability driven by the uplift of the Tibetan Plateau: ah0-sum.nc nc file, hh0-sum.nc nc file, jfh0-sum.nc nc file, kdh0-sum.nc nc file, lfh0-sum.nc nc file, mask.nc nc file, phis.nc nc file.
AN Zhisheng
This glacial lake inventory is jointly supported by the International Centre for Integrated Mountain Development (ICIMOD) and United Nationenvironment Programme / Regional Resourc Centre, Asia and The Pacific (UNEP / RRC-AP). 1. The glacial lake inventory refers to remote sensing data such as Landsat 4/5 (MSS, TM1982 / 1985/1984/1999), Landsat 7 (ETM +), IRS-1C, LISS-III (1995IRS-1C), (1997 IRS-1D), etc. It reflects the current status of glacial lakes in the region in 2000. 2. Glacial lake inventory coverage: India-Uttaranchal. 3. The content of the glacial lakeinventory includes: glacial lake inventory, glacial lake type, glacial lake orientation, glacial lake width, glacial lake area, glacial lake depth, glacial lake length and other attributes. 4. Projection parameters: Projection: Universal Transverse Mercator (UTM) Ellipsoid: WGS84 Datum: WGS84 Ellipsoid Parameters: a = 6378137.000 1 / f = 298.257223563 Northem Hemisphere: Yes MinimumX: 221473.969 MinimumY: 3300590.500 MaximumX: 513943.969 MaximumY: 3488960.500 Zone: 44 For detailed data description, please refer to data files and reports.
Pradeep Kumar Mool, WU Lizong, Samjwal Ratna Bajracharya Samjwal Ratna Bajracharya, Basanta Shrestha
Impact of Climate and Glacier Evolution in Southwest Monsoon Region on Resources and Sustainable Development in Lijiang-Yulong Snow Mountain Region Project is a major research program of "Environmental and Ecological Science in Western China" sponsored by the National Natural Science Foundation. The person in charge is a researcher from He Yuanqing, Institute of Environment and Engineering in Cold and Arid Regions, Chinese Academy of Sciences. The project runs from January 2004 to December 2006. This project collects data: the data of Yulong Snow Mountain Glacier and Environment Observation and Research Station are compiled in word document, and the data content includes: 1. Material Balance of Baishui Glacier No.1 from September to December 2008 (Profile, Lever, Accumulation and Dissipation) 2.Changes of Baishui Glacier No.1 in Yulong Snow Mountain from 1997 to 2008 (date, end elevation, end advancing and retreating distance, south advancing and retreating distance) 3. Monthly Average Flow Statistics of Mujia Station from 1979 to 2003 (Annual Average Flow, Annual Maximum Flow, Annual Maximum Time, Annual Minimum Flow, and Annual Minimum Time) 4. Meteorological data of the test station of Yulong Snow Mountain Glacier Observation Room From 2000 to 2008, the daily average temperature (℃), daily precipitation (mm), daily average relative humidity, daily average sunshine hours, daily air pressure value and daily average wind speed of the base camp weather station. From 2006 to 2008, Ganhaizi Meteorological Station daily average temperature (℃), daily precipitation (mm), daily average relative humidity, daily average sunshine hours, daily air pressure value and daily average wind speed In 2008, the day-to-day average temperature table (℃), day-to-day precipitation (mm), day-to-day average relative humidity, day-to-day average sunshine hours, day-to-day air pressure value and day-to-day average wind speed in the Baishui No.1 glacier accumulation area of Yulong Snow Mountain. In 2008, the day-to-day average temperature table (℃), day-to-day precipitation (mm), day-to-day average relative humidity, day-to-day average sunshine hours, day-to-day air pressure, and day-to-day average wind speed at the end of glacier Baishui No.1 in Yulong Snow Mountain were recorded. Dew point temperature of Ganhaizi from 2006 to 2008 Daily average CO2 content (ppm) at Ganhaizi Meteorological Station from 2006 to 2007 Air Water Vapor Pressure (kPa) at Glacier Terminal Meteorological Station Air Water Vapor Pressure (kPa) of Meteorological Station in Glacier Accumulation Area 5. glacier ice Temperature Data of Baishui No.1, Yulong Snow Mountain Measured resistance values of ice temperature holes at measuring points 1, 2 and 3
HE Yuanqing
These data are a digitization of the frozen soil distribution map of the Map of the Glaciers, Frozen Ground and Deserts in China (1:4,000,000). Considering the unification with the global frozen soil classification system, the permafrost is divided into the following five types: (1) Discontinuous permafrost: continuous coefficient 50%-90% (2) Island permafrost: continuous coefficient <50% (3) Plateau discontinuous permafrost: continuous coefficient 50%-90% (4) Plateau island permafrost: continuous coefficient 50%-90% (5) Mountain permafrost The compilation basis of the frozen soil map includes (1) the measured field survey data and exploration of frozen soil; (2) aerial image and satellite image interpretation; (3) TOPO30 1-km resolution ground elevation data; and (4) and temperature and ground temperature data. The distribution of frozen soil on the Tibetan Plateau adopted the research results of Zhuotong Nan et al. (2002). Using the average annual temperature data of 76 boreholes along the Qinghai-Tibet Highway, a statistical regression analysis was performed to obtain the relation between annual mean ground temperature, latitude and elevation. Based on the relation combined with GTOPO30 elevation data (global 1-km digital elevation model data developed by the Earth Resources Observation and Technology Center of the U.S Geological Survey), the annual average ground temperature distribution over the entire Tibetan Plateau was simulated. Taking the annual average ground temperature of 0.5 °C as the boundary between permafrost and seasonal frozen soil and the Map of Snow Ice and Frozen Ground in China (1:4,000,000) (Yafeng Shi, et al., 1988) as a reference, the boundary between the plateau discontinuous permafrost and plateau island permafrost was determined. In addition, taking the Distributions Map of Permafrost in Daxiao Hinganling Northeast China (Dongxin Guo, et al. 1981), the Distribution Map of Permafrost and Ground Ice in Circum-Arctic (Brown et al. 1997) and the latest field data as references, the permafrost boundary of northeast China has been revised; the mountain permafrost boundary in the northwest mostly adopted the boundary delineated in the Map of Snow Ice and Frozen Ground in China (1:4,000,000) (Yafeng Shi, et al., 1988). According to this data set, permafrost area in China is approximately 1.75×106 km2, accounting for 18.25% of the territory of China, among which the mountain permafrost area is 0.29×106 km2, which accounts for 3.03% of the territory of China. For more information, please refer to the Map of the Glaciers, Frozen Ground and Deserts in China (1:4,000,000) specification (Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, 2006).
WANG Tao, SHI Yafeng, GUO Dongxin
This dataset uses daily temperature data from SMMR (1978-1987), SSM/I (1987-2009) and SSMIS (2009-2015). It is generated by the dual-index (TB, 37v, SG) freeze-thaw discrimination algorithm. The classification results include the frozen surface, the thawed surface, the deserts and water bodies. The data coverage is the main part of China’s mainland, with a spatial resolution of 25.067525 km via the EASE-Grid projection method, and it is stored in ASCIIGRID format. All the ASCII files in this data set can be opened directly with a text program such as Notepad. Except for the head file, the body content is numerically characterized by the freeze/thaw status of the surface soil: 1 for frozen, 2 for thawed, 3 for desert, and 4 for precipitation. If you want to use the icon for display, we recommend using the ArcView + 3D or Spatial Analyst extension module for reading; in the process of reading, a grid format file will be generated, and the displayed grid file is the graphical expression of the ASCII file. The read method comprises the following. [1] Add the 3D or Spatial Analyst extension module to the ArcView software and then create a new View. [2] Activate View, click File menu, and select the Import Data Source option. When the Import Data Source selection box pops up, select ASCII Raster in the Select import file type box. When the dialog box for selecting the source ASCII file automatically pops up, click to find any ASCII file in the data set, and then press OK. [3] Type the name of the Grid file in the Output Grid dialog box (it is recommended that a meaningful file name is used for later viewing) and click the path to store the Grid file, press OK again, and then press Yes (to select integer data) and Yes (to put the generated grid file into the current view). The generated files can be edited according to the Grid file standard. This completes the process of displaying an ASCII file into a Grid file. [4] In the batch processing, the ASCIGRID command of ARCINFO can be used to write AML files, and then use the Run command to complete the process in the Grid module: Usage: ASCIIGRID <in_ascii_file> <out_grid> {INT | FLOAT}. The production of this data is supported by the following Natural Science Foundation Projects: Environmental and Ecological Science Data Center of West China (90502010), Land Data Assimilation System of West China (90202014) and Active and Passive Microwave Radiation Transmission Simulation and Radiation Scattering Characteristics of the Frozen Soil (41071226).
LI Xin
This dataset is the spatial distribution map of the marshes in the source area of the Yellow River near the Zaling Lake-Eling Lake, covering an area of about 21,000 square kilometers. The data set is classified by the Landsat 8 image through an expert decision tree and corrected by manual visual interpretation. The spatial resolution of the image is 30m, using the WGS 1984 UTM projected coordinate system, and the data format is grid format. The image is divided into five types of land, the land type 1 is “water body”, the land type 2 is “high-cover vegetation”, the land type 3 is “naked land”, and the land type 4 is “low-cover vegetation”, and the land type 5 is For "marsh", low-coverage vegetation and high-coverage vegetation are distinguished by vegetation coverage. The threshold is 0.1 to 0.4 for low-cover vegetation and 0.4 to 1 for high-cover vegetation.
KHROMOVA Tatiana,
These data are digitized for the Geocryological Regionalization and Classification Map of the Frozen Soil in China (1:10 million) (Guoqing Qiu et al., 2000; Youwu Zhou et al., 2000), adopting a geocryological regionalization and classification dual series system. The geocryological regionalization system and classification system are used on the same map to reflect the commonality and individuality of the formation and distribution of frozen soil at each level. The geocryological regionalization system consists of three regions of frozen soil: (1) the frozen soil region of eastern China; (2) the frozen soil region of northwestern China; and (3) the frozen soil region of southwestern China (Tibetan Plateau). Based on the three large regions, 16 regions and several subregions are further divided. In the division of the geocryological boundary in the frozen soil area, the boundary between major regions I and III mainly consults the results of Bingyuan Li (1987). The boundary between major regions II and III is the northern boundary of the Tibetan Plateau, which is the Kunlun Mountains-Altun Mountains-Northern Qilian Mountains and the piedmont line. The boundary between major regions I and II is in the area of Helan Mountain-Langshan Mountain. The boundary of the secondary region is divided by the geomorphological conditions in regions II and III. However, in region I, it is mainly divided by the ratio of the annual temperature range A to the annual mean temperature T, and the frozen depths of various regions are taken into consideration. The classification system is divided into 8 types based on the continuity of frozen soil, the time of existence of frozen soil and the seasonal frozen depth. The various classifications of boundaries are mainly taken from the "Map of Snow, Ice and Frozen Ground in China" (1:4 million) (Yafeng Shi et al., 1988) and consult some new materials, whereas the seasonal frozen soil boundary is mainly based on the weather station data. The definitions of each classification are as follows: (1) Large permafrost: the continuous coefficient is 90%-70%; (2) Large-island permafrost: the continuous coefficient is 70%-30%; (3) Sparse island-shaped permafrost: the continuous coefficient is <30%; (4) Permafrost in the mountains; (5) Medium-season seasonal frozen soil: the maximum seasonal frozen depth that can be reached is >1 m; (6) Shallow seasonal frozen soil: the maximum seasonal frozen depth that can be reached is <1 m; (7) Short-term frozen soil: less than one month of storage time; and (8) Nonfrozen soil. According to the data, China's permafrost areas sum to approximately 2.19 × 106 km², accounting for 22.83% of China's territory. Among those areas, the mountain permafrost is found over 0.42×106 km2, which is 4.39% of the territory of China. The seasonal frozen soil area is approximately 4.76×106 km², accounting for 49.6% of China's territory, and the instantaneous frozen soil area is approximately 1.86×106 km², i.e., 19.33% of China's territory. For more information, please see the references (Youwu Zhou et al., 2000).
GUO Dongxin, QIU Guoqing
The assessment of changes in the atmospheric water cycle and the associated impacts in a key area of the Tibetan Plateau under the background of the global warming was a major component of the research project “The Environmental and Ecological Science of West China” run by the National Natural Science Foundation of China. The leading executive of the project was Xiangde Xu from the Chinese Academy of Meteorological Sciences. The project ran from January 2006 to December 2008. The following data were collected by the project of the Sino-Japan Joint Research Center of Meteorological Disaster (JICA Project): 1. Observation category, time period and number of stations 1) JICA AWS data: From January to July of 2008, 73 automatic stations (including 5 automatic stations of the Chinese Academy of Sciences) collected data in Tibet, Yunnan, Sichuan and other provinces or autonomous regions. 2) JICA GPS water vapour data: From January to October of 2008, 24 observation stations collected data in Tibet, Yunnan, Sichuan and other provinces or autonomous regions. 3) JICA encrypted observation GPS sonde data: From March to July of 2008, observations were made in Tibet, Yunnan, Sichuan and other provinces or autonomous regions (detailed observation time and location data can be found in the data catalogue). 2. Observation categories, data content 1) GPS water vapour Data content: serial number, station name (Chinese), station number, longitude, latitude, altitude, year, month, day, time, surface pressure, surface air temperature, relative humidity, total delay (m), precipitation (cm) (Measurement interval: 1 hour). 2) GPS encrypted sonde Data content: air pressure P, temperature T, relative humidity RH, V component, U component, vertical height H, dew point temperature Td, water vapour content Mr, wind direction Wd, wind speed Ws, longitude Lon, latitude Lat, radar height RdH. A value of "-999.90" means no observation data. 3) AWS Data content: station number, longitude, latitude, elevation, site level, total cloud volume, wind direction, wind speed, sea level pressure, 3-hour pressure variable, past weather 1, past weather 2, 6-hour precipitation, low cloud form, low cloud volume, low cloud height, dew point, visibility, current weather, temperature, medium cloud form, high cloud form, 24-hour temperature variable, 24-hour pressure variable. Project Science Advisers: Guoguang Zheng, Xiaofeng Xu, Xiuji Zhou, Zechun Li, Jifan Niu, Jianmin Xu, Lianshou Chen, Dahe Qin, Yihui Ding Project Superintendent: Jixin Yu Project Executives: Renhe Zhang, Xiangde Xu Data set hosting organizations: Chinese Academy of Meteorological Sciences, JICA Project Implementation Expert Group, State Key Laboratory of Severe Weather, JICA Project Implementation Office. Collaborative organizations involved in the production of the data set: Chinese Academy of Meteorological Sciences, State Key Laboratory of Severe Weather, National Satellite Meteorological Center, The Research Center for Atmospheric Sounding Techniques, National Meteorological Center, National Meteorological Information Center, National Climate Center, Sichuan Meteorological Department, Yunnan Meteorological Department, Tibet Autonomous Region Meteorological Department, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Tianjin Meteorological Department. Data set implementation organizations: Beijing Headquarters of JICA Project; JICA Project Sub-center in Sichuan Province, Yunnan Province, Tibet Autonomous Region and Institute of Tibetan Plateau Research, Chinese Academy of Sciences.
XU Xiangde
The data set includes 1. permaice (map of frozen soil types), 2. subsea (subsea boundary vectorgraph), 3. treeline (timberline vectorgraph), 4. nhipa (grid map) and 5. llipa (grid map). Permaice includes the following attribute fields: Num_code (frozen soil attribute code), Combo (frozen soil attribute), extent (frozen soil coverage) and content (ice content). The attribute comparison is as follows. (1) Frozen soil attribute comparison table: 0 （No information） 1 - chf （Continuous permafrost extent with high ground ice content and thick overburden） 2 - dhf （Discontinuous permafrost extent with high ground ice content and thick overburden） 3 - shf （Sporadic permafrost extent with high ground ice content and thick overburden） 4 - ihf （Isolated patches of permafrost extent with high ground ice content and thick overburden） 5 - cmf （Continuous permafrost extent with medium ground ice content and thick overburden） 6 - dmf （Discontinuous permafrost extent with medium ground ice content and thick overburden） 7 - smf （Sporadic permafrost extent with medium ground ice content and thick overburden） 8 - imf （Isolated patches of permafrost extent with medium ground ice content and thick overburden） 9 - clf （Continuous permafrost extent with low ground ice content and thick overburden） 10 - dlf （Discontinuous permafrost extent with low ground ice content and thick overburden） 11 - slf （Sporadic permafrost extent with low ground ice content and thick overburden） 12 - ilf （Isolated patches of permafrost extent with low ground ice content and thick overburden） 13 - chr （Continuous permafrost extent with high ground ice content and thin overburden and exposed bedrock） 14 - dhr （Discontinuous permafrost extent with high ground ice content and thin overburden and exposed bedrock） 15 - shr （Sporadic permafrost extent with high ground ice content and thin overburden and exposed bedrock） 16 - ihr （Isolated patches of permafrost extent with high ground ice content and thin overburden and exposed bedrock） 17 - clr （Continuous permafrost extent with low ground ice content and thin overburden and exposed bedrock） 18 - dlr （Discontinuous permafrost extent with low ground ice content and thin overburden and exposed bedrock） 19 - slr （Sporadic permafrost extent with low ground ice content and thin overburden and exposed bedrock） 20 - ilr （Isolated patches of permafrost extent with low ground ice content and thin overburden and exposed bedrock） 21 - g （Glaciers） 22 - r （Relict permafrost） 23 - l （Inland lakes） 24 - o （Ocean/inland seas） 25 - ld （Land） （2）The frozen soil coverage attribute comparison table c = continuous (90-100%) d = discontinuous (50-90%) s = sporadic (10-50%) i = isolated patches (0-10%) （3）The ice content comparison table h = high (>20% for "f" landform codes) (>10% for "r" landform codes) m = medium (10-20%) l = low (0-10%) ------------------------------------------------------------ Projection of the shapefiles is: PROJCS["Sphere_ARC_INFO_Lambert_Azimuthal_Equal_Area", GEOGCS["GCS_Sphere_ARC_INFO", DATUM["Sphere_ARC_INFO", SPHEROID["Sphere_ARC_INFO",6370997.0,0.0]], PRIMEM["Greenwich",0.0], UNIT["Degree",0.0174532925199433]], PROJECTION["Lambert_Azimuthal_Equal_Area"], PARAMETER["False_Easting",0.0], PARAMETER["False_Northing",0.0], PARAMETER["longitude_of_center",180.0], PARAMETER["latitude_of_center",90.0], UNIT["Meter",1.0]] Projection for the raster (*.byte) files is: Projection: Lambert Azimuthal Units: meters Spheroid: defined Major Axis: 6371228.00000 Minor Axis: 6371228.000 Parameters: radius of the sphere of reference: 6371228.00000 longitude of center of projection: 0 latitude of center of projection: 90 false easting (meters): 0.00000 false northing (meters): 0.00000
O. Ferrians, J. A. Heginbottom, E. Melnikov, ZHANG Tingjun, RAN Youhua
This data set includes the observation data of the automatic meteorological station from January 2008 to September 2009 in Linze Inland River Basin Comprehensive station. The station is located in Linze County, Zhangye City, Gansu Province, with longitude and latitude of 100 ° 08 ′ e, 39 ° 21 ′ N and altitude of 1382m. The observation items include: atmospheric temperature and humidity gradient observation (1.5m and 3.0m), wind speed (2.2m and 3.7m), wind direction, air pressure, precipitation, net radiation and total radiation, carbon dioxide (2.8m and 3.5m), soil tension, multi-layer soil temperature (20cm, 40cm, 60cm, 80cm, 120cm and 160cm) and soil heat flux (5cm, 10cm and 15cm). Please refer to the instruction document published with the data for specific header and other information.
Zhang Zhihui, ZHAO Wenzhi, MA Mingguo
The phased array type l-land synthetic aperture radar (PALSAR) is a phased array L-band SAR sensor mounted on alos satellite. The sensor has three observation modes: high resolution, scanning synthetic aperture radar and polarization, which make it possible to obtain a wider ground width than the general SAR. At present, there are 13 scenes of ALOS pallsar data in Heihe River Basin. The coverage and acquisition time are as follows: 1 scene in the northeast of Zhangye City, HH / HV polarization, 2008-04-25; 2 scenes in Binggou basin + Arjun encrypted observation area, HH / HV polarization, 2008-05-122008-06-27; 2 scenes in Dayekou basin + Yingke oasis intensified observation area, HH / HV polarization, 2008-05-122008-06-27; observation station encrypted observation area Survey area + Linze station densified observation area + Linze grassland densified observation area 2 scenes, HH / HV polarization, time 2008-05-122008-06-27; Linze station densified observation area 1 scene, HH / HV polarization, time 2008-05-12; Binggou basin densified observation area 1 scene, HH / HV polarization, time 2008-07-14; bindukou densified observation area 4 scenes, 2008-04-25 2 scenes, HH / HV polarization, 2008-06-10 2 scenes, HH pole Change. The product level is L1 without geometric correction. The alos PALSAR remote sensing data set of Heihe comprehensive remote sensing joint experiment was obtained from JAXA by Dr. Takeo tadono, researcher Ye Qinghua and Professor Shi Jiancheng (the cooperation project between Qinghai Tibet Institute of Chinese Academy of Sciences and JAXA). (Note: "+" means to overwrite at the same time)
Japan Aerospace Exploration Agency
Proba (project for on board autonomy) is the smallest earth observation satellite launched by ESA in 2001. Chris (compact high resolution imaging Spectrometer) is the most important imaging spectrophotometer on the platform of proba. It has five imaging modes. With its excellent spectral spatial resolution and multi angle advantages, it can image land, ocean and inland water respectively for different research purposes. It is the only on-board sensor in the world that can obtain hyperspectral and multi angle data at the same time. It has high spatial resolution, wide spectral range, and can collect rich information in biophysics, biochemistry, etc. At present, there are 23 scenes of proba Chris data in Heihe River Basin. The coverage and acquisition time are as follows: 4 scenes in Arjun dense observation area, 2008-11-18, 2008-12-05, 2009-03-29, 2009-05-22; 1 scene in pingdukou dense observation area, 2009-07-13; 7 scenes in Binggou basin dense observation area, 2008-11-19, 2008-11-26, 2008-12-06, 2009-01-10, 2009-03-04, 2009-03-30, 2009-03-31; dayokou basin dense observation area, 2009-07-13 There are two views in the observation area, 2008-10-23, 2009-06-08; one in Linze area, 2008-06-23; one in Minle area, 2008-10-22; seven in Yingke oasis dense observation area, 2008-04-30, 2008-05-09, 2008-06-04, 2008-07-01, 2008-07-19, 2009-05-31, 2009-08-10. The product level is L1 without geometric correction. Except that there are only four angles for the images of 2009-03-29 and 2009-05-24 in the Arjun encrypted observation area, each image has five different angles. The remote sensing data set of the comprehensive remote sensing joint experiment of Heihe River, proba Chris, was obtained through the "dragon plan" project (Project No.: 5322) (see the data use statement for details).
LI Xin
ALOS PRISM dataset includes 13 scenes; one covers the A'rou foci experimental area on Mar. 19, 2008, one covers the Haichaoba on Mar. 19, 2008, one covers the Biandukou foci experimental area on Apr. 17, 2008, and one covers the Linze grassland and Linze station foci experimental areas on Apr. 22, 2008. The data version is LB2, which was released after radiometric correction and geometric correction.
Japan Aerospace Exploration Agency
BJ-1 dataset includes 11 scenes, covering the upper and middle reaches of the Heihe river basin, which were acquired on 10-21-2007, 11-19-2007, 01-09-2008, 03-03-2008, 04-04-2008, 04-16-2008, 05-01-2008, 05-16-2008, 07-01-2008, 07-06-2008 and 07-08-2008. The sensor was MSI, substar resolution was 32m, fov was 22.06°, the orbit was 686km high and the dip angle was 98.1725°, the focal distance was 150mm, CCD pixel was 7μm, the near infrared band was 760nm-900nm, red wave band was 630nm-690nm and green wave band was 520nm-620nm. The data version is Level 2, which was released after geometric correction. BJ-1 dataset was acquired from "Dragon Programme" (grant number: 5322).
LI Xin
Advanced along orbit scanning radiometer (AATSR) is an advanced tracking scanning radiometer sensor mounted on the European Space Agency ENVISAT satellite. It is one of many high-precision and stable infrared radiometers for retrieving sea surface temperature (SST). Its accuracy can reach 0.3k, and it can also be used to record meteorological data. AATSR is a multi-channel imaging radiometer. Its main goal is to provide global ocean surface temperature with high accuracy and stability for monitoring the earth's climate change. At present, there are 38 ENVISAT AATSR images in Heihe River Basin. The acquisition time is 2008-05-17 (2 scenes), 2008-05-27 (2 scenes), 2008-05-30 (2 scenes), 2008-06-02 (2 scenes), 2008-06-12 (2 scenes), 2008-06-15 (2 scenes), 2008-06-18 (2 scenes), 2008-06-21 (2 scenes), 2008-07-04 (2 scenes), 2008-07-072008-07-102008-07-172008-07-202008-07-232008-07-262008-08-022008-08-052008-08-082008 -08-11，2008-08-14，2008-08-21，2008-08-24，2008-08-27，2008-08-30，2008-09-06，2008-09-12，2008-09-15，2008-09-18，2008-09-25。 The product level is L1B, which has been corrected by radiation but not by geometry. The ENVISAT AATSR remote sensing data set of Heihe comprehensive remote sensing joint test was obtained through the China EU "dragon plan" project (Project No.: 5322) (see the data use statement for details).
LI Xin
The Map of Permafrost on the Qinghai-Tibet Plateau (1:3,000,000) (Shude Li and Guodong Cheng, 1996) was made by the State Key Laboratory of Frozen Soil Engineering, LIGG, CAS (currently called the Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences). It was based on first-hand information from the study of frozen soil and previous research papers and literature. By detailed study and consultation of aerial photographs, satellite images, the Permafrost Map along the Qinghai-Tibet Highway (1:600,000) (Boliang Tong, et al., 1983), Geomorphological Map of the Qilian Mountains (1:1,000,000) (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 1985), Natural Landscape Map of Qinghai-Tibetan Plateau (1:3,000,000) (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 1990), Quaternary Glacial Distribution Map of the Qinghai-Tibetan Plateau (1:3,000,000) (Bingyuan Li and Jijun Li, 1991), Frozen Soil Remote Sensing Map of the Western Channel Project of the South-North Water Diversion in the Region of the Tongtian-Yalong Rivers (1:500,000) (Lanzhou Institute of Glaciology and Cryopedology, Chinese Academy of Sciences, 1995), and Map of Snow, Ice, Frozen Ground in China (1:4,000,000) (Yafeng Shi and Desheng Mi, 1988), with editing on 1,000,000 aerial survey topographic maps, and the 1:3,000,000 Map of Permafrost on the Qinghai-Tibetan Plateau was then generated. It was later digitized by Zhuotong Nan of the Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences. The data include: 1) Digitized distribution map of frozen soil on the Qinghai-Tibetan Plateau 2) Scanned map of frozen soil map on the Qinghai-Tibetan Plateau The types of frozen soil in the digitized frozen soil map include: 0. Seasonally frozen ground; seasonal frozen soil 1. Permafrost 2. Island permafrost; 3. Continuous permafrost;
CHENG Guodong, LI Shude, NAN Zhuotong, TONG Boliang
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