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 coverage time of glacier runoff data set in the five major river source areas of the Qinghai Tibet Plateau is from 1971 to 2015, and the time resolution is year by year, covering the source areas of five major rivers (Yellow River source, Yangtze River source, Lancang River source, Nu River source, Yarlung Zangbo River source). The data is based on multi-source remote sensing and measured data. The glacier runoff data is simulated by using the daily scale meteorological data of five major river source areas and their surrounding meteorological stations, the global vegetation products of umd-1km, the igbp-dis soil database, the first and second glacier catalogue data, and the distributed hydrological model vic-cas coupled with the glacier module is used to simulate the glacier runoff data. The simulation results are verified by the site measured data to enhance the quality control. Data indicators include: Glacier runoff (rate of glacier runoff:%), total runoff (mm / a), snow runoff (rate of snow runoff:%), and rainfall runoff rate (rainfall runoff rate:%).
WANG Shijin
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
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
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
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
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
Snow is a significant component of the ecosystem and water resources in high-mountain Asia (HMA). Therefore, accurate, continuous, and long-term snow monitoring is indispensable for the water resources management and economic development. The present study improves the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Terra and Aqua satellites 8 d (“d” denotes “day”) composite snow cover Collection 6 (C6) products, named MOD10A2.006 (Terra) and MYD10A2.006 (Aqua), for HMA with a multistep approach. The primary purpose of this study was to reduce uncertainty in the Terra–Aqua MODIS snow cover products and generate a combined snow cover product. For reducing underestimation mainly caused by cloud cover, we used seasonal, temporal, and spatial filters. For reducing overestimation caused by MODIS sensors, we combined Terra and Aqua MODIS snow cover products, considering snow only if a pixel represents snow in both the products; otherwise it is classified as no snow, unlike some previous studies which consider snow if any of the Terra or Aqua product identifies snow. Our methodology generates a new product which removes a significant amount of uncertainty in Terra and Aqua MODIS 8 d composite C6 products comprising 46 % overestimation and 3.66 % underestimation, mainly caused by sensor limitations and cloud cover, respectively. The results were validated using Landsat 8 data, both for winter and summer at 20 well-distributed sites in the study area. Our validated adopted methodology improved accuracy by 10 % on average, compared to Landsat data. The final product covers the period from 2002 to 2018, comprising a combination of snow and glaciers created by merging Randolph Glacier Inventory version 6.0 (RGI 6.0) separated as debris-covered and debris-free with the final snow product MOYDGL06*. We have processed approximately 746 images of both Terra and Aqua MODIS snow containing approximately 100 000 satellite individual images. Furthermore, this product can serve as a valuable input dataset for hydrological and glaciological modelling to assess the melt contribution of snow-covered areas. The data, which can be used in various climatological and water-related studies, are available for end users at https://doi.org/10.1594/PANGAEA.901821 (Muhammad and Thapa, 2019).
SHER Muhammad
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 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 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 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)
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
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
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 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)
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)
The Randolph Glacier Inventory (RGI) is a complete inventory of global glacier outlines published by GLIMS (Global Land Ice Measurements from Space). It is currently available in six versions: Version 1.0 was published in February 2012, version 2.0 was published in June 2012, version 3.0 was published in April 2013, version 4.0 was published in December 2014, version 5.0 was published in July 2015, and version 6.0 was published in July 2017. The data sets include four versions, which are 6.0, 5.0, 4.0 and 3.2 (revision, August 2013). The data are organized according to different regions. In each region, each glacier record includes a shape file (.shp file and its corresponding .dbf, .prj, and .shx files) and a .csv file of height measurement data. The data are from GLIMS: Global Land Ice Measurements from Space (http://www.glims.org/RGI/) Data quality checks include geometry, topology, and certain attributes, and the following checks were performed: 1) All polygons were checked by the ArcGIS Repair Geometry tool. 2) Glaciers with areas less than 0.01 square kilometres were removed. 3) The topology was checked with the Does Not Overlap rule. 4) The attribute sheet was checked by Fortran subroutines and Python scripts for data quality.
Global Land Ice Measurements from Space
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
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