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
Climate records obtained by most instruments are relatively short in time, which limits the study of climate change, necessitating the use of proxy data to extend records to the past. It was not until the late 1940s that atmospheric data of sufficient quality and spatial resolution were available to determine the main patterns of climate change such as the North American Pacific model and the Pacific Decadal Oscillation. The global ice cores are from the north and south poles and the third pole, and there are also mountain glaciers in Alaska. The ice core data obtained in that area are of great significance for revealing the climate in North America and climate change in the Arctic regions at both low and high latitudes. The physical meaning of each variable: First column: time; second column: accumulation rate data; third column: oxygen isotope data value
Du Zhiheng
The Greenland Ice Sheet Project Two (GISP2), initiated by the United States, has provided detailed oxygen isotope data for a time span of more than 100,000 years, covering almost the entire glacial-interglacial cycle. These data include the oxygen isotope changes from 818 to 1987, with a clear record showing that the Little Ice Age was the coldest period of the past 1000 years. Fluctuating warming occurred from 1850 to 1987, and the changes were consistent with those of GRIP, NGRIP and the latest NEEM ice core obtained in Greenland. This finding indicated that the snow and ice records from the Greenland ice sheet were highly consistent. The physical meaning of each variable is as follows: First column: ice core depth; second column: oxygen isotope value; third column: time
Du Zhiheng
From 1000 AD to the present, the concentration of methane in the atmosphere has increased significantly in the ice cores of the Antarctic and Arctic. These data came from the Tasmanian laboratory of Australia, where the high resolution data were obtained by using wet extraction of ice core samples, and the same measurement and calibration procedures were applied to all samples. The results are consistent with the results of internationally renowned ice core greenhouse gas laboratories such as the University of Bern, the University of Copenhagen and the University of Ohio. The physical meaning of each variable: First column: time; second column: methane concentration value
Du Zhiheng
The microwave radiometer data set comprises brightness temperature data from SMMR (1978-1987), SSM/I (1987-2009) and SSMIS (2009-2015), with temporal coverage from 1978 to 2015 and a spatial resolution of 25 km. Each Antarctic data file consists of 316*332 grids, and each Arctic freeze-thaw data file consists of 304*448 grids. The microwave scatterometer data set comprises backscattering data from QScat (2000-2009) and ASCAT (2009-2015), with a temporal coverage from 2000 to 2015 and a spatial resolution of 4.45 km. Each Antarctic data file consists of 1940*1940 grids, and each Arctic data file consists of 810*680 grids. The temporal resolution of the data set is one day, and the data cover both Antarctica and Arctic ice sheets.
Li Xinwu, Liang Lei
Using the Modis1B data of 11 scenes from 2003 to 2013 (the ice shelf Modis1B data published on the NSIDC website), the surface velocity of the Antarctic Amery Ice Shelf was extracted by the subpixel cross-correlation method, the ice velocity was extracted by the COSI-Corr software, and then the time sequence of annual average velocities for nearly ten years was obtained. Due to the lack of field observations in the study area, the accuracy of the ice flow results was estimated by using the offset value of the stable region, and the ice flow error was approximately ±50 m/year. The ice velocity data date from 2003 to 2013, the temporal resolution is one year, and the data cover the Amery area with a spatial resolution of 500 m. A GeoTIFF file of velocity data is stored every year. For details regarding the data, please refer to the Amery Ice Flow Field - Data Description.
JIANG Liming
Under the background of global warming, mountain glaciers worldwide are facing strong ablation and retreat, but from existing field observations, it is found that most of the glaciers in the Karakorum region remain stable or are advancing, which is called the "Karakorum anomaly". Glacier surface velocity is an important parameter for studying glacier dynamics and mass balance. Studying the temporal and spatial variation characteristics of glacier velocity in central Karakorum is significant for understanding the dynamic characteristics of the glacier in this region and its response to climate change. Four pairs of Landsat 7 ETM+ images acquired in 1999 to 2003 (images acquired on 1999.7.16, 2000.6.16, 2001.7.21, 2002.8.9, 2002.4.19, 2003.3.21) were selected; using the panchromatic band with a resolution of 15 m, each pair of images was accurately registered, and then cross-correlation calculations were then performed on each image pair after registration to obtain the surface velocity of the glacier in the central Karakorum region from 1999 to 2003. Due to the lack of velocity observation data in the study area, the accuracy of the ice flow results is estimated using the offset value of the stable region, and the surface velocity error of the glacier is approximately ±7 m/year. The glacier velocity data dates are from 1999 to 2003, with a temporal resolution of one year. They cover the central Karakorum region, with a spatial resolution of 30 m. The data are stored as a GeoTIFF file every year. For details regarding the data, please refer to the data description.
JIANG Liming
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
This data set contains the wide swath mode Level 1B SAR data acquired over Greenland in 2005 by the ASAR sensor of the ENVISAT-1 satellite. The width is 400 km, the spatial resolution is 75 m, and the absolute positioning accuracy is approximately 200 m. The SAR data are stored in a time-growth order, which causes the images of the descending track to be left-right mirror images and the images of the ascending track to be up-down images. The naming scheme for these data is as follows: ASA_IMS_1PPIPA 20050402_095556_000000162036_00065_16151_0388.N1 ASA: Product identification, ASAR Sensor IMS: Reception and processing information of the data (imaging modes, such as WS, WSS, IM, ...) 1PPIPA: Customized number 20050402: Acquisition time of the data (UTC time) 095556: Geographic location (start, end) 000000162036: Information on the satellite orbit 00065: Product trust data 16151: Size and structure information of the product 0388 => Check code
HUI Fengming
The Antarctic and Arctic bacterial distribution data set provides distribution characteristics of bacteria in the Arctic and Antarctic. The collection period of the samples was from December 13,2005, to December 8,2006; 52 samples were obtained from 3 Arctic regions (Spitsbergen Slijeringa, Spitsbergen Vestpynten, and Alexandra Fjord_Highlands), and 171 samples were obtained from 5 Antarctic regions (the Mitchell Peninsula, Casey station main Power house, Robinsons Ridge, Herring Island, and Browning Peninsula). The soil surface samples were stored in liquid nitrogen after collection, shipped to a Sydney laboratory, and extracted using the FastPrep DNA kit. The extracted DNA samples were processed by 27F (5'-GAGTTTGATCNTGGCTCA-3' and 519R (5'-GTNTTACNGCGGCKGCTG-3') to amplify the 16S rRNA gene fragments. The amplified fragments were sequenced by the 454 method, and the raw data were analyzed by Mothur software. First, the sequences with poor sequencing quality were removed, the sequences were then sorted, and the chimera sequences were removed. The similarities between the sequences were calculated, the sequences with similarities above 97% were clustered into one OTU, and the OTU representative sequence was defined. By comparison with the Silva database, the OTU sequences with reliabilities greater than 80% were identified as level one. This data system compared the diversity of microorganisms in the eastern Antarctic with that in the Arctic and is of great significance for the study of the distributions of microorganisms in the Antarctic and Arctic.
JI Mukan
A high-resolution remote sensing image mosaic of the entire Antarctic was generated by synthesizing the 1073 images taken by American Landsat 7 during 1999 to 2003 and the medium-resolution MODIS image (taken in 2005) covering south of 82.5°southern latitude. Based on the mosaic, combined with the needs of Antarctic scientific research, Antarctica land cover was divided into six types using the combination method of computer automatic interpretation and artificial assistance. They were blue ice, fissures, bare rocks, water bodies, moraines and firns, and the areas and proportions of the above types were 225,207.29 square kilometers (1.651%), 7153.36 square kilometers (0.052%), 72,958.04 square kilometers (0.535%), 189.43 square kilometers (0.001%), 310.76 square kilometers (0.003%), and 13337392.66 square kilometers (97.758%), respectively. The map is a satellite image map of approximate true color synthesis, and the regions of various cover types are represented by different color blocks. The map mainly provides a reference for popular scientific research, geography education and science popularization.
HUI Fengming
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.
Li Xinwu, Liang Lei
From 2013 to 2014, the Glacial Geomorphology of the upper reaches of Heihe River in the late Quaternary was investigated and sampled. Based on the field investigation and remote sensing image, the distribution map of moraine at different levels near the ridge of the upper reaches of the Bailang river was obtained.
HU Xiaofei, PAN Baotian
From July 21 to September 2, 2012, the observation data of snowmelt water temperature and near surface temperature in hulugou small watershed were observed by hobo automatic temperature recorder, with the observation frequency of once / 15 minutes, and the near surface temperature recorder was 20cm away from the surface. The observation point 01 is an ice lake, which is formed by the permanent snow supply of Hunan slope. The lake is approximately triangular, and the long side trend is parallel to the slope foot, with the coordinates of 99 ° 53 ′ 11 ″ E and 38 ° 13 ′ 6 ″ n. The observation period is from July 21, 2012 to September 2, 2012. No.02 observation point is located under the ice lake, the source of the East tributary of hulugou, the foot of permanent snow slope and the lower edge of snow melting. The coordinates are 99 ° 53 ′ 12 ″ e, 38 ° 13 ′ 6 ″ n. The observation period is from July 21, 2012 to September 2, 2012. The distance between the two points is relatively close, and the near surface temperature is the uniform temperature, which is the near surface temperature of point 01.
CHANG Qixin
Glaciers are sensitive to climate change and are important indicators and amplifiers of global change. In inland river regions, river runoff mainly comes from mountain ice and snow melt. Glaciers are very important "solid reservoirs" in these regions, and glacial melt water is an important source of supply for the tributaries of the Heihe River. The inventory of glaciers in the Heihe River Basin was completed from 1979 to 1980. For related information, please refer to "Chinese Glacier Inventory-Qilian Mountains" edited by Wang Zongtai and others. In 2004, the relevant results of the "China Glacier Inventory" were systematically digitized and a database was established. The final results were released through the "China Glacier Information System". However, in the process of coordinate restoration, the accuracy of the reference data was poor, and the glaciers in the Heihe River Basin had obvious position shifts. Therefore, we used the Landsat remote sensing image corrected by ortho-geometric correction. The processed Heihe Glacier distribution data is highly consistent with the existing basic geographic information in China in terms of geometric accuracy, and consistent with the first glacier inventory in terms of attributes.
WANG Zongtai
The compilation basis of frozen soil map includes: (1) frozen soil field survey, exploration and measurement data; (2) aerial photo and satellite image interpretation; (3) topo300 1km resolution ground elevation data; (4) temperature and ground temperature data. Among them, the distribution of permafrost in the Qinghai Tibet Plateau adopts the research results of nanzhuo Tong et al. (2002). Using the measured annual average ground temperature data of 76 boreholes along the Qinghai Tibet highway, regression statistical analysis is carried out to obtain the relationship between the annual average ground temperature and latitude, elevation, and based on this relationship, combined with the gtopo30 elevation data (developed under the leadership of the center for earth resources observation and science and technology, USGS) Global 1 km DEM data) to simulate the annual mean ground temperature distribution over the whole Tibetan Plateau. Taking the annual average ground temperature of 0.5 ℃ as the boundary between permafrost and seasonal permafrost, the boundary between discontinuous Permafrost on the plateau and island Permafrost on the plateau is delimited by referring to the map of ice and snow permafrost in China (1:4 million) (Shi Yafeng et al., 1988); in addition, the division map of Permafrost on the big and small Xing'an Mountains in the Northeast (Guo Dongxin et al., 1981), the distribution map of permafrost and underground ice around the Arctic (b According to rown et al. 1997) and the latest field survey data, the Permafrost Boundary in Northeast China has been revised; the Permafrost Boundary in Northwest mountains mostly uses the boundary defined in the map of ice and snow permafrost in China (1:4 million) (Shi Yafeng et al., 1988). According to the data, the area of permafrost in China is about 1.75 × 106km2, accounting for about 18.25% of China's territory. Among them, alpine permafrost is 0.29 × 106km2, accounting for about 3.03% of China's territory. For more information, please refer to the specification of "1:4 million map of glacial and frozen deserts in China" (Institute of environment and Engineering in cold and dry areas, Chinese Academy of Sciences, 2006)
WANG Tao
The map is "1:4 Million Ice, Snow and Frozen Soil Map of China" compiled by Mr. Shi Yafeng and Mr. Meadson. The working map compiled by the map is "Chinese Pinyin Edition of the People's Republic of China", which retains the water system and mountain annotation of the map and adds some mountain annotation. The compilation of frozen soil map is based on the actual data of frozen soil survey and exploration, interpretation of remote sensing data, temperature conditions and topographic characteristics that affect the formation and distribution of frozen soil. The height of glacier snow line is expressed by isolines. Seasonal snow accumulation and seasonal icing are based on the data of 1600 meteorological observation stations and the results of many years of investigation in China. They are expressed by isoline notation and symbols. The selection of cold (periglacial) phenomena is a representative and schematic representation observed on the spot. The boundary line between permafrost and non-permafrost is mapped by calculation based on the field data, and its comprehensive degree is relatively high (Tö pfer, 1982) "China Ice and Snow Frozen Soil Map" reflects the scale, types and characteristics of distribution of glaciers, snow cover, frozen soil and periglacial, as well as its value in scientific research and the prospect of utilization and prevention in production practice. It shows our achievements in glacier and frozen soil research in the past 30 years.
SHI Yafeng, MI Desheng
China's second glacier inventory uses the high-resolution Landsat TM/ETM+ remote sensing satellite data as the main glacier boundary data source and extracts the data source with the latest global digital elevation model, SRTM V4, as the glacier attribute, using the current international ratio threshold segmentation method to extract the glacier boundary in bare ice areas. The ice ridge extraction algorithm is developed to extract the glacier ice ridge, and it is used for the segmentation of a single glacier. At the same time, the international general algorithm is used to calculate the glacier attributes, so that the vector data and attribute data that contain the glacier information of the main glacier regions in west China are obtained. Compared with some field GPS field measurement data and higher resolution remote sensing images (such as from QuickBird and WorldView), the glacial vector data in the second glacier inventory data set of China have higher positioning accuracy and can meet the requirements for glacial data in national land, water conservancy, transportation, environment and other fields. Glacier inventory attributes: Glc_Name, Drng_Code, FCGI_ID, GLIMS_ID, Mtn_Name, Pref_Name, Glc_Long, Glc_Lati, Glc_Area, Abs_Accu, Rel_Accu, Deb_Area, Deb_A_Accu, Deb_R_Accu, Glc_Vol_A, Glc_Vol_B, Max_Elev, Min_Elev, Mean_Elev, MA_Elev, Mean_Slp, Mean_Asp, Prm_Image, Aux_Image, Rep_Date, Elev_Src, Elev_Date, Compiler, Verifier. For a detailed data description, please refer to the second glacier inventory data description.
LIU Shiyin, GUO Wanqin, XU Junli
The glacial change trend in the Tarim River Basin and its impact on water resources change belong to the National Natural Science Foundation of China's Western Environment and Ecological Science major research project. The time is 2003.1-2005.12. The project submitted data: Kochikarbachi Glacier Observation Data (excel): Including precipitation, wind direction, wind speed and temperature data 1.3300a_climate (2003.6.29-2004.6.22): 4 hours data during the day, including field date, time, wind speed, wind up, temperature. 2.4200b_climate (2004.1.29-2004.5.12): 6:00, 8:00, 9:00, 10:00, 12:00, 14:00, 16:00, 18:00, 20:00, 22: 00, 23:00 observation data, including field date, time, wind speed, wind up, temperature. 3.3700_Precipitation: 13 days daily precipitation from 2003.7 to 2005.9 4.4200_Precipitation: 18-day daily precipitation between 2003.7 and 2006. 6
LIU Shiyin
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
Chinese Cryospheric Information System is a comprehensive information system for the management and analysis of Chinese Cryospheric data. The establishment of Chinese Cryospheric Information System is to meet the needs of earth system science, to provide parameters and validation data for the development of response and feedback model of frozen soil, glacier and snow cover to global change under GIS framework; on the other hand, it is to systemically sort out and rescue valuable cryospheric data, to provide a scientific, efficient and safe management and division for it Analysis tools. The basic datasets of the Tibet Plateau mainly takes the Tibetan Plateau as the research region, ranging from longitude 70 -- 105 ° east and latitude 20 -- 40 ° north, containing the following types of data: 1. Cryosphere data. Includes: Permafrost type (Frozengd), (Fromap); Snow depth distribution (Snowdpt) Quatgla (Quatgla) 2. Natural environment and resources. Includes: Terrain: elevation, elevation zoning, slope, slope direction (DEM); Hydrology: surface water (Stram_line), (Lake); Basic geology: Quatgeo, Hydrogeo; Surface properties: Vegetat; 4. Climate data: temperature, surface temperature, and precipitation. 3. Socio-economic resources (Stations) : distribution of meteorological Stations on the Tibetan Plateau and it surrounding areas. 4. Response model of plateau permafrost to global change (named "Fgmodel"): permafrost distribution data in 2009, 2049 and 2099 were projected. Please refer to the following documents (in Chinese): "Design of Chinese Cryospheric Information System.doc", "Datasheet of Chinese Cryospheric Information System.DOC", "Database of the Tibetan Plateau.DOC" and "Database of the Tibetan Plateau 2.DOC".
LI Xin
This glacial lake inventory receives joint support from the International Centre for Integrated Mountain Development (ICIMOD) and United Nations Environment Programme/Regional Resource Centre, Asia and the Pacific (UNEP/RRC-AP). 5. This glacial lake inventory referred to Landsat 4/5 (MSS and TM), SPOT(XS), IRS-1C/1D(LISS-III) and other remote sensing data. It reflects the current situation of glacial lakes with areas larger than 0.01 km2 in 2004. 6. Glacial Lake Inventory Coverage: Yamuna basin, Ravi basin, Chenab basin, Satluj River Basin and others. 7. The Glacial Lake Inventory includes glacial lake inventory, glacial lake type, glacial lake width, glacial lake orientation, glacial lake length from the glacier and other attributes. 8. Projection parameter: Projection: Albers Equal Area Conic Ellipsoid: WGS 84 Datum: WGS 1984 False easting: 0.0000000 False northing: 0.0000000 Central meridian: 82° 30’E Central parallel: 0° 0’ N Latitude of first parallel: 20° N Latitude of second parallel: 35° N For a detailed data description, please refer to the data file and report.
International Centre for Integrated Mountain Development (ICIMOD)
This glacier inventory is supported by the International Centre for Integrated Mountain Development (ICIMOD) and the United Nation Environment Programme/Regional Resources Centre, Asia and The Pacific (UNEP/RRC-AP)。 1、The glacier inventory uses the remote sensing data of Landsat,reflecting the current status of glaciers in Nepal in 2000. 2、The spatial coverage of the glacier inventory: Nepal 3、Contents of the glacier inventory: glacier location, glacier code, glacier name, glacier area, glacier length, glacier thickness, glacier stocks, glacier type, glacier orientation, etc. 4、Data Projection: Grid Zone IIA Projection: Lambert conformal conic Ellipsoid: Everest (India 1956) Datum: India (India, Nepal) False easting: 2743196.40 False northing: 914398.80 Central meridian: 90°00'00"E Central parallel: 26°00'00"N Scale factor: 0.998786 Standard parallel 1: 23°09'28.17"N Standard parallel 2: 28°49'8.18"N Minimum X Value: 1920240 Maximum X Value: 2651760 Minimum Y Value: 914398 Maximum Y Value: 1188720 Grid Zone IIB Projection: Lambert conformal conic Ellipsoid: Everest (India 1956) Datum: India (India, Nepal) False easting: 2743196.40 False northing: 914398.80 Central meridian: 90°00'00"E Central parallel: 26°00'00"N Scale factor: 0.998786 Standard parallel 1: 21°30'00"N Standard parallel 2: 30°00'00"N Minimum X Value: 1823188 Maximum X Value: 2000644 Minimum Y Value: 1306643 Maximum Y Value: 1433476 For a detailed data description, please refer to the data file and report.
Samjwal Ratna Bajracharya Samjwal Ratna Bajracharya, Sharad Prasad Joshi
This glacial lake inventory is supported by the International Centre for Integrated Mountain Development (ICIMOD) and the United Nation Environment Programme/Regional Resources Centre, Asia and The Pacific (UNEP/RRC-AP). 1. The glacial lake inventory uses the remote sensing data of Landsat,reflecting the current status of glacial lakes larger than 0.01 square kilometers in Nepal in 2000. 2. The spatial coverage of the glacial lake inventory: Nepal 3. Contents of the glacial lake inventory: glacial lake code, glacial lake types, glacial lake area, distance between glacial lakes and the glaciers, related glaciers, etc. 4. Data Projection: Grid Zone IIA Projection: Lambert conformal conic Ellipsoid: Everest (India 1956) Datum: India (India, Nepal) False easting: 2743196.40 False northing: 914398.80 Central meridian: 90°00'00"E Central parallel: 26°00'00"N Scale factor: 0.998786 Standard parallel 1: 23°09'28.17"N Standard parallel 2: 28°49'8.18"N Minimum X Value: 1920240 Maximum X Value: 2651760 Minimum Y Value: 914398 Maximum Y Value: 1188720 Grid Zone IIB Projection: Lambert conformal conic Ellipsoid: Everest (India 1956) Datum: India (India, Nepal) False easting: 2743196.40 False northing: 914398.80 Central meridian: 90°00'00"E Central parallel: 26°00'00"N Scale factor: 0.998786 Standard parallel 1: 21°30'00"N Standard parallel 2: 30°00'00"N Minimum X Value: 1823188 Maximum X Value: 2000644 Minimum Y Value: 1306643 Maximum Y Value: 1433476 For a detailed data description, please refer to the data file and report.
Sharad Prasad Joshi, Samjwal Ratna Bajracharya Samjwal Ratna Bajracharya
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.
International Centre for Integrated Mountain Development (ICIMOD) , United Nationenvironment Programme/Regional Resourc Centre, Asia and The Pacific (UNEP/RRC-AP)
This glacial lake inventory receives joint support from International Centre for Integrated Mountain Development (ICIMOD) and United Nations Environment Programme/Regional Resource Centre, Asia and the Pacific (UNEP/RRC-AP). 1. This glacial lake inventory referred to Landsat 4/5 (MSS, TM/1984/1999), Landsat 7 (TM & ETM+), IRS-1C, LISS-III (1995 IRS-1C), (1997 IRS-1D) and other remote sensing data. It reflects the current situation of glacial lakes with areas larger than 0.01 km2 in 2000. 2. Glacial Lake Inventory Coverage: Tista Basin, Sikkim Region 3. Glacial Lake Inventory 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 parameter: Projection: Lambert conformal conic Ellipsoid: Everest (India 1956) Datum: India (India, Sikkim) False easting: 2743196.40 False northing: 914398.80 Central meridian: 90°00’00” E Central parallel: 26°00’00” N Scale factor: 0.998786 Standard parallel 1: 23°09’28.17” N Standard parallel 2: 28°49’8.18” N Minimum X Value: 2545172 Maximum X Value: 2645240 Minimum Y Value: 1026436 Maximum Y Value: 1163523 For a detailed data description, please refer to the data file and report.
Samjwal Ratna Bajracharya Samjwal Ratna Bajracharya
This glacial lake inventory receives joint support from the International Centre for Integrated Mountain Development (ICIMOD) and the United Nations Environment Programme/Regional Resources Centre for Asia and the Pacific (UNEP/RRC-AP), Cold and Arid Region Environmental and Engineering Research Institute (CAREERI). 9. This glacial lake cataloging uses Landsat (TM and ETM), Aster and other remote sensing data. It reflects the current situation of glacial lakes with areas larger than 0.01 km2 in the Himalayas in 2004. 10. Glacial lake catalogue coverage: the Himalayan region, Pumqu (Arun), Rongxer (Tama Koshi), Poiqu (Bhote-Sun Koshi), Jilongcangbu (Trishuli), Zangbuqin (Budhigandaki), Majiacangbu (Humla Karnali) and others. 11. Glacial Lake cataloging includes glacial lake cataloging, glacial lake type, glacial lake orientation, glacial lake width, glacial lake area, glacial lake depth, glacial lake length and other attributes. 12. Data projection information: Projection: Transverse_Mercator False_Easting: 500000.000000 False_Northing: 0.000000 Central_Meridian: 87.000000 Scale_Factor: 0.999600 Latitude_Of_Origin: 0.000000 Linear Unit: Meter (1.000000) Geographic Coordinate System: GCS_WGS_1984 Angular Unit: Degree (0.017453292519943299) Prime Meridian: Greenwich (0.000000000000000000) Datum: D_WGS_1984 Spheroid: WGS_1984 Semimajor Axis: 6378137.000000000000000000 Semiminor Axis: 6356752.314245179300000000 Inverse Flattening: 298.257223563000030000 For a detailed data description, please refer to the data file and report.
International Centre for Integrated Mountain Development (ICIMOD)
This glacial lake inventory is supported by the International Centre for Integrated Mountain Development (ICIMOD) and the United Nations Environment Programme/Regional Resource Centre, Asia and The Pacific (UNEP/RRC-AP). 1. The glacial lake inventory incorporates topographic map data and reflects the status of glacial lakes in the region in 2000. 2. The spatial coverage of the glacial lake inventory is as follows: Pa Chu Sub-basin, Mo Chu Sub-basin, Thim Chu Sub-basin, Pho Chu Sub-basin, Mangde Chu Sub-basin, Chamkhar Chu Sub-basin, Kuri Chu Sub-basin, Dangme Chu Sub-basin, Northern Basin, etc. 3. The glacial lake inventory includes the following data fields: glacial lake code, glacial lake types, glacial lake orientation, glacial lake width, glacial lake area, glacial lake depth, glacial lake length, etc. 4. Data projection: Projection: Polyconic Ellipsoid: Everest (India 1956) Datum: Indian (India, Nepal) False easting: 2,743,196.4 False northing: 914,398.80 Central meridian: 90°0'00'' E Central parallel: 26°0'00'' N Scale factor: 0.998786 For a detailed description of the data, please refer to the data file and report.
International Centre for Integrated Mountain Development (ICIMOD)
This glacial lake inventory is supported by the International Centre for Integrated Mountain Development (ICIMOD) and the United Nations Environment Programme/Regional Resource Centre, Asia and The Pacific (UNEP/RRC-AP). 1. The glacial lake inventory adopts the Landsat remote sensing data and reflects the status of glacial lakes in the Pakistan region from 2003 to 2004. 2. In terms of spatial coverage, the glacial lake inventory covers the Swat, Chitral, Gilgit, Hunza, Shigar, Shyok, Upper, Indus, Shingo, Astor and Jhelum river basins in the upper reaches of the Indus River. 3. The glacial lake inventory data include the glacial lake code, glacial lake type, glacial lake area, distance between the glacier and the glacial lake, glaciers related to the glacial lake, etc. For detailed descriptions of the data, please refer to the data file and report.
Samjwal Ratna Bajracharya Samjwal Ratna Bajracharya, Basanta Shrestha, Sharad Prasad Joshi
This glacier inventory is supported by the International Centre for Integrated Mountain Development (ICIMOD) and the United Nations Environment Programme/Regional Resource Centre, Asia and The Pacific (UNEP/RRC-AP). 1.The glacier inventory incorporates topographic map data, and reflects the status of glaciers in the region in 2000. 2.The spatial coverage of the glacier inventory includes the following: Pa Chu Sub-basin,Mo Chu Sub-basin,Thim Chu Sub-basin,Pho Chu Sub-basin,Mangde Chu Sub-basin, Chamkhar Chu Sub-basin,Kuri Chu Sub-basin,Dangme Chu Sub-basin,Northern Basin, etc. 3.The glacier inventory includes the following data fields: glacier location, glacier code, glacier name, glacier area, glacier length, glacier thickness, glacier stocks, glacier type, glacier orientation, etc. 4.Data projection: Projection: Polyconic Ellipsoid: Everest (India 1956) Datum: Indian (India, Nepal) False easting: 2,743,196.4 False northing: 914,398.80 Central meridian: 90°0'00'' E Central parallel: 26°0'00' N Scale factor: 0.998786 For a detailed description of the data, please refer to the data file and report.
International Centre for Integrated Mountain Development (ICIMOD)
Chinese Cryospheric Information System is a comprehensive information system for the management and analysis of Chinese cryospheric data. 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 contains three basic databases of different research regions. The basic database of Urumqi river basin is one of three basic databases, which covers the Urumqi river basin in tianshan mountain, east longitude 86-89 °, and north latitude 42-45 °, mainly containing the following data: 1. Cryospheric data.Include: Distribution of glacier no. 1 and glacier no. 2; 2. Natural environment and resources.Include: Terrain digital elevation: elevation, slope, slope direction; Hydrology: current situation of water resource utilization;Surface water; Surface characteristics: vegetation type;Soil type;Land resource evaluation map;Land use status map; 3. Social and economic resources: a change map of human action; Please refer to the documents (in Chinese): "Chinese Cryospheric Information System design. Doc" and "Chinese Cryospheric Information System data dictionary. Doc".
LI Xin
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