This data was derived from "1: 100,000 Land Use Data of China". Based on Landsat MSS, TM and ETM remote sensing data, 1: 100,000 Land Use Data of China was compiled within three years by a remote sensing scientific and technological team of 19 research institutes affiliated to the Chinese Academy of Sciences, which was organized by the “Remote Sensing Macroinvestigation and Dynamic Research on the National Resources and Environment", one of the major application programs in Chinese Academy of Sciences during the "Eighth Five-year Plan". This data adopts a hierarchical land cover classification system, which divides the country into 6 first-class categories (cultivated land, forest land, grassland, water area, urban and rural areas, industrial and mining areas, residential land and unused land) and 31 second-class categories. This is the most accurate land use data product in our country at present. It has already played an important role in national land resources survey, hydrology and ecological research.
2020-06-10
This data was derived from "1: 100,000 Land Use Data of China". Based on Landsat MSS, TM and ETM remote sensing data, 1: 100,000 Land Use Data of China was compiled within three years by a remote sensing scientific and technological team of 19 research institutes affiliated to the Chinese Academy of Sciences, which was organized by the “Remote Sensing Macroinvestigation and Dynamic Research on the National Resources and Environment", one of the major application programs in Chinese Academy of Sciences during the "Eighth Five-year Plan". This data adopts a hierarchical land cover classification system, which divides the country into 6 first-class categories (cultivated land, forest land, grassland, water area, urban and rural areas, industrial and mining areas, residential land and unused land) and 31 second-class categories. This is the most accurate land use data product in our country at present. It has already played an important role in national land resources survey, hydrology and ecological research.
2020-06-10
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
2020-06-09
This data is digitized from the "Naiman Banner Desertification Types and Land Consolidation Zoning Map" of the drawing. The specific information of this map is as follows: * Editors: Zhu Zhenda and Qiu Xingmin * Editor: Feng Yushun * Re-photography and Mapping: Feng Yushun, Liu Yangxuan, Wen Zi Xiang, Yang Taiyun, Zhao Aifen, Wang Yimou, Li Weimin, Zhao Yanhua, Wang Jianhua * Field trips: Qiu Xingmin and Zhang Jixian * Cartographic unit: compiled by Desert Research Office of Chinese Academy of Sciences * Publishing House: Shanghai China Printing House * Scale: 1: 150000 * Published: May 1984 * Legend: Severe Desertification Land, Intensely Developed Desertification Land, Developing Desertification Land, Potential Desertification Land, Non-desertification Land, Fluctuating Sandy Loess Plain, Forest and Shrub, Saline-alkali Land, Mountain Land, Cultivated Land and Midian Land 2. File Format and Naming Data is stored in ESRI Shapefile format, including the following layers: Naiman banner desertification type map, rivers, roads, reservoirs, railways, zoning 3. Data Attributes Desertification Class Vegetation Background Class Desertified land and cultivated sand dunes under development. Midland in Saline-alkali Land Severely desertified land Reservoir Trees and shrubbery Mountain Strongly developing desertified land Potential desertified land Lakes Non-desertification land Undulating sand-loess plain 2. 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
2020-06-09
In 2007 and 2008, Landsat data set 49 scenes, covering the entire black river basin. The acquisition time is:2007-08-12, 2007-09-23, 2008-01-05, 2008-02-06, 2008-03-17, 2008-03-25, 2008-05-10, 2008-05-19, 2008-05-28, 2008-06-04, 2008-07-07, 2008-07-15, 2008-07-22, 2008-07-23, 2008-08-16, 2008-08-30,2008-09-08, 2008-09-15, 2008-09-17, 2008-10-01, 2008-10-10, 2008-10-19, 2008-10-26, 2008-11-02, 2008-11-04, 2008-11-18, 2008-11-20, 2008-11-27, 2008-12-06, 2008-12-13, 2008-12-14. The product is class L1 and has been geometrically corrected.It includes 4 scenes of TM image and 45 scenes of ETM+ image. The Landsat satellite remote sensing data set of heihe integrated remote sensing joint experiment was obtained through free download.
2020-06-08
ASAR (Advanced Synthetic Aperture Radar) is a Synthetic Aperture Radar sensor mounted on ENVISAT satellite. It operates in c-band with a wavelength of 5.6 cm and features multi-polarization, variable observation Angle and wide-range imaging. Heihe river basin of ENVISAT ASAR remote sensing data sets mainly through central Europe "dragon plan" project, the data to the Image mode, cross polarization (Alternating Polarisation) model with wide is given priority to, the spatial resolution of 30 meters. ENVISAT ASAR data 404 scenes are currently available in heihe river basin, including 82 scenes in APP mode, 7 scenes in IMP mode and 315 scenes in WSM mode. The acquisition time is: APP can choose the polarization mode, the time range is from 2007-08-15 to 2007-12-23, 2008-01-02 to 2008-12-20, 2009-02-15 to 2009-09-06; IMP imaging mode, time range from 2009-06-19 to 2009-07-12; WSM wide format, time range from 2005-12-05 to 2005-12-31,2006-01-06 to 2006-12-31, 2007-01-01 to 2007-12-30, 2008-01-01 to 2008-12-28, 2009-03-13 to 2009-05-22. Product level is L1B, without geometric correction, is amplitude data.
2020-06-08
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
The dataset is the HWSD soil texture dataset of the Qinghai Lake Basin. The data comes from the Harmonized World Soil Database (HWSD) constructed by the Food and Agriculture Organization of the United Nations (FAO) and the Vienna International Institute for Applied Systems (IIASA). Version 1.1 was released on March 26, The data resolution is 1km. The soil classification system used is mainly FAO-90. The main fields of the soil attribute table include: SU_SYM90 (soil name in FAO90 soil classification system) SU_SYM85 (FAO85 classification) T_TEXTURE (top soil texture) DRAINAGE (19.5); ROOTS: String (depth classification of obstacles to the bottom of the soil); SWR: String (soil moisture characteristics); ADD_PROP: Real (a specific soil type related to agricultural use in the soil unit); T_GRAVEL: Real (gravel volume percentage); T_SAND: Real (sand content); T_SILT: Real (silt content); T_CLAY: Real (clay content); T_USDA_TEX: Real (USDA soil texture classification); T_REF_BULK: Real (soil bulk density); T_OC: Real (organic carbon content); T_PH_H2O: Real (pH) T_CEC_CLAY: Real (cation exchange capacity of cohesive layer soil); T_CEC_SOIL: Real (cation exchange capacity of soil) T_BS: Real (basic saturation); T_TEB: Real (exchangeable base); T_CACO3: Real (carbonate or lime content) T_CASO4: Real (sulfate content); T_ESP: Real (exchangeable sodium salt); T_ECE: Real (conductivity). The attribute field beginning with T_ indicates the upper soil attribute (0-30cm), and the attribute field beginning with S_ indicates the lower soil attribute (30-100cm) (FAO 2009). The data can provide model input parameters for modelers of the Earth system, and the agricultural perspective can be used to study eco-agricultural zoning, food security, and climate change.
2020-06-08
The integration of geomorphological information in western China was completed by a team led by Dr. Xie Chuanjie, Institute of Geography, Resources and Environment, Chinese Academy of Sciences. These include the national geomorphological database of 1: 4 million and the western geomorphological database of 1: 1 million. The geomorphological data of 1: 4 million are tracked, collected and collated by the Geography Department of the National Planning Commission of the Chinese Academy of Sciences, "China Geomorphological Map (1: 4 million)" edited by Li Bingyuan and "Geomorphological Map of China and Its Adjacent Areas (1: 4 million)" edited by Chen Zhiming. Scan and register the data, vectorize all registered maps by ArcMap software, and establish their own classification and code systems. Geomorphological types are divided into basic geomorphological types and morphological structure types (point, line and surface representation) according to map spots (common staining) and symbols. Data are divided into structural geomorphology and morphological geomorphology. Projection information: Projection: Albers False_Easting: 0.000000 False_Northing: 0.000000 Central_Meridian: 105.000000 Standard_Parallel_1: 25.000000 Standard_Parallel_2: 47.000000 Latitude_Of_Origin: 0.000000 Linear Unit: Meter (1.000000) Geographic Coordinate System: datumg Angular Unit: Degree (0.017453292519943299) Prime Meridian: <custom> (0.000000000000000000) Datum: D_Krasovsky_1940 Spheroid: Krasovsky_1940 Semimajor Axis: 6378245.000000000000000000 Semiminor Axis: 6356863.018773047300000000 Inverse Flattening: 298.300000000000010000
2020-06-08
The data includes the county-level data of characteristic agriculture distribution in the Qinghai Tibet Plateau, which lays the foundation for the spatial distribution and development of characteristic agriculture in the Qinghai Tibet Plateau.
2020-06-07
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