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MICLCover land cover map of the Heihe river basin (2000)

1 km land cover map of heihe river basin is ran youhua et al. (2009;2011) develop a subset of China's 1 km land cover map (MICLCover) incorporating multi-source local information.The MICLCover land cover map adopts the IGBP land cover classification system, based on the evidence theory, which integrates the 1:100,000 land use data of China in 2000, the vegetation pattern of China vegetation atlas (1:100,000), the 1:100,000 glacier distribution map of China, the 1:100,000 swamp wetland map of China and the land cover product of MODIS in 2001 (MOD12Q1).The verification results of MICLCover showed that the overall consistency of MICLCover and China's land use map reached 88.84% on the level of 7 categories. Among them, the consistency of cultivated land, city, wetland and water type reached more than 95%.Through visual comparison with the land cover data product of MODIS2001 and IGBPDISCover land cover map in three typical areas, MICLCover keeps the overall accuracy of China's land use map and increases the leaf attribute and leaf shape information of China's vegetation map, while reflecting more detailed local land cover details.Using the national forest resources survey data, the verification results in gansu, yunnan, zhejiang, heilongjiang and jilin provinces showed that the accuracy of forest types of MICLCover was significantly improved compared with that of MODIS land cover products.The forest type of MICLCover was verified with the forest resource survey data of qilian mountain national nature reserve administration of gansu province. The results showed that the accuracy of MICLCover forest type in this area was 82.94%. Anyhow, MICLCover land cover map while maintaining the overall precision of the Chinese land use data condition, supplement the vegetation map of China on vegetation types and vegetation season phase information, update the Chinese wetland figure, Chinese ice figure the latest information, the accuracy of China's land cover data is greatly improved, more general classification system, the data can provide higher precision for land surface process model of land cover information.

2020-07-30

Estimated evapotranspiration data of the Heihe River Basin by remote sensing (2000-2014)

Images: MODIS images Preparation method: Tsinghua redraw remote sensing evapotranspiration model calculation Spatial scope: Heihe River Basin Time range: data from 2001 to 2014

2020-07-30

The duration of water withdraw in the midstream of the Heihe River Basin (2000-2011)

"Coupling and evolution of hydrological, ecological and economic processes in Heihe basin management under the framework of water rights" (91125018) project data collection - 2000~2011 of the middle reaches of Heihe. 1. summary of data: the time of centralized water transfer in the middle reaches of Heihe in 2000~2011; 2. data content: Statistics on the specific date of the centralized discharge of the whole line every year since the unified water dispatch in the middle reaches of Heihe.

2020-07-28

Inventory dataset of glacial lakes in the Sikkim Region, India (2000)

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.

2020-06-09

Glacier inventory dataset of Nepal (2000)

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.

2020-06-09

Inventory of glacial lakes in Bhutan (2000)

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.

2020-06-09

Inventory of glacial lakes in Nepal (2000)

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.

2020-06-09

1:1,000,000 Geomrphological map of the Heihe River basin (2000)

The geomorphic data of Heihe River are from the geomorphic Atlas of the people's Republic of China (1:1 million). This data is based on remote sensing image and other multi-source data integration and update. The main data used and referenced include: 1) remote sensing image data: TM and 2000's around 1990's nationwide About ETM image; 2) historical geomorphic map: 15 published 1 million geomorphic maps, two sets of 1:4 million geomorphic maps in China, 500000 or 1 million geomorphic sketches in all provinces and cities in China; 3) basic geographic data: 1:250000 basic geographic data and 250000 DEM data in China; 4) geological data: 1:500000 geological map in China; 5) relevant thematic maps: land use map, vegetation map and land resource map And so on. The interpretation method adopts the human-computer interaction method based on ArcGIS, and is carried out according to the interpretation sequence of hierarchical classification: the first layer: plain and mountain; the second layer: basic geomorphic types (28); the third layer: 10 genetic types; the fourth layer: secondary genetic types; the fifth layer: morphological difference classification types; the sixth layer: secondary morphological difference classification types; the seventh layer: slope, slope The eighth layer is the type of geomorphic material determined by material composition or lithology; the ninth layer is the combination of 1-7 layers of map spots. There are 441 geomorphic types and codes. Data fields include: fenfu (view frame number), name (attribute), class (code), sname (administrative division).

2020-06-08

SRTM DEM data of the Heihe River Basin (2000)

SRTM (Shuttle Radar Topography Mission) is by NASA and the national geospatial intelligence agency (NGA) cooperation to build the global 3 d graphics data project.In February 2000, the SRTM system mounted on the U.S. space shuttle endeavour collected radar image data between latitude 60 ° north and latitude 57 ° south, and acquired radar image data covering more than 80% of the world's land surface.After more than two years of processing, the digital terrain elevation model was made. This data set including the heihe river basin SRTM points picture and Mosaic two kinds of data, and the points of the graph is SRTM version 4 data by the CGIAR - CSI (international centre for tropical agriculture, http://srtm.csi.cgiar.org/) treatment, compared with the previous version has greatly improved, including: 1) use a lot of interpolation algorithm, 2) use more auxiliary DEM data to fill the blank spots and blank area, 3) compared with the third version of the data and migration half a yuan.The Mosaic map is obtained by splicing on the basis of sub-map. The sub-charts include srtm_56_04,srtm_56_05,srtm_57_04 and srtm_57_054. The data are 16 bit values representing the elevation value (-/+/32767 m). The maximum positive elevation is 9000 m and the maximum negative elevation is 12,000 m below sea level.Null data is identified by -32767.Divide the file into 24 rows (-60 to 60 degrees) and 72 columns (-180 to 180 degrees) per 5 latitude and longitude squares.

2020-06-05

The frozen soil type map of Kazakhstan (1:10,000,000) (2000)

The frozen soil type map of Kazakhstan (1:10,000,000) includes three .shp vector layers: 1, Polyline ranges.shp, indicating the extent of frozen soil; 2, Polygon kaz_perm.shp, frozen soil; 3, An attribute description Word file. The kaz_perm attribute table includes four fields: ID, REGION, SUBREGION, M_RANGE. Comparison of the main attributes: First, Area I. Altai-TienShan Second, Region: High mountains I.1. Altai, I.2. Saur-Tarbagatai, I.3.Dzhungarskyi, I.4. Northern Tien Shan, I.5. Western Tien Shan Intermountain depressions I.6. Zaysanskyi, I.7. Alakulskyi, I.8. Iliyskyi II. Western Siberian Second, Region: Planes II.1. Northern Kazakhstanskyi V. Western Kazakhstanskaya III. Kazakh small hills area IV. Turanskaya: IV.1. Turgayskyi IV.2. Near Aaralskyi IV.3. Chuysko-Syrdaryinskyi IV.4. South-Balkhashskyi V. Western Kazakhstanskaya: V.1. Mugodzhar-Uralskyi V.2. Near Caspian V.3. manghyshlak-Ustyrtskyi Third, Sub-region: I.1.1. Western Altai I.1.2. South Altai I.1.3. Kalbinskyi I.2.1. Tarbagatayskyi I.2.2. Saurskyi I.3.1. Nortern Dzhungarskyi I.3.2. Western Dzhungarskyi I.3.3. Southern Dzhungarskyi I.4.1. Kirgizskyi Alatau I.4.2. Zailiyskyi-Kungeyskyi I.4.3. Ketmenskyi I.4.4. Bayankolskyi I.5.1. Karatauskyi I.5.2. Talaso-Ugamskyi The layer projection information is as follows: GEOGCS["GCS_WGS_1984", DATUM["WGS_1984", SPHEROID["WGS_1984", 6378137.0, 298.257223563]], PRIMEM["Greenwich", 0.0], UNIT["Degree",0.0174532925199433]] Different regions feature different frozen soil attributes, and the specific attribute information can be found in the Word file.

2020-06-04