This data set is a digital elevation model of the Tibetan Plateau and can be used to assist in analysis and research of basic geographic information for the Tibetan Plateau. The raw data were the Shuttle Radar Topography Mission (SRTM) data, which were provided by Global Land Cover Network (GLCN), and the raw data were framing data , using the WGS84 coordinate system, including latitude and longitude, with a spatial resolution of 3″. After the mosaic processing, the Nodata (null data) generated in the mosaic process were interpolated and filled. After filling, the projection conversion process was performed to generate data as Albers equal area conical projection. After the conversion projection, the spatial resolution of the data was 90 m. Finally, the boundary of the Tibetan Plateau was used for cutting to obtain DEM data. This data table has two fields. Field 1: value Data type: long integer Interpretation: altitude elevation Unit: m Field 2: count Data type: long integer Interpretation: The number of map spots corresponding to the altitude elevation Data accuracy: spatial resolution: 90 m
These data contain two data files: GLOBELAND30 TILES (raw data) and TIBET_ GLOBELAND30_MOSAIC (mosaic data). The raw data were downloaded from the Global Land Cover Data website (GlobalLand3) (http://www.globallandcover.com) and cover the Tibetan Plateau and surrounding areas. The raw data were stored in frames, and for the convenience of using the data, we use Erdas software to splice and mosaic the raw data. The Global Land Cover Data (GlobalLand30) is the result of the “Global Land Cover Remote Sensing Mapping and Key Technology Research”, which is a key project of the National 863 Program. Using the American Landsat images (TM5, ETM+) and Chinese Environmental Disaster Reduction Satellite images (HJ-1), the data were extracted by a comprehensive method based on pixel classification-object extraction-knowledge checks. The data include 10 primary land cover types—cultivated land, forest, grassland, shrub, wetland, water body, tundra, man-made cover, bare land, glacier and permanent snow—without extracting secondary types. In terms of accuracy assessment, nine types and more than 150,000 test samples were evaluated. The overall accuracy of the GlobeLand30-2010 data is 80.33%. The Kappa indicator is 0.75. The GlobeLand30 data use the WGS84 coordinate system, UTM projection, and 6-degree banding, and the reference ellipsoid is the WGS 84 ellipsoid. According to different latitudes, the data are organized into two types of framing. In the regions of 60° north and south latitudes, the framing is carried out according to a size of 5° (latitude) × 6° (longitude); in the regions of 60° to 80° north and south latitudes, the framing is carried out according to a size of 5° (latitude) × 12° (longitude). The framing is projected according to the central meridian of the odd 6° band. GLOBELAND30 TILES: The original, unprocessed raw data are retained. TIBET_ GLOBELAND30_MOSAIC: The Erdas software is used to mosaic the raw data. The parameter settings use the default value of the raw data to retain the original, and the accuracy is consistent with that of the downloading site.
Data investigation method: investigation and collection of Heihe River Basin Authority. The data include: the water distribution plan of the main stream of Heihe River (including Liyuan River) prepared by the Yellow River Water Conservancy Commission of the Ministry of water resources in 1996; the brief report on the water conservancy planning of the main stream of Heihe River prepared by Lanzhou survey and Design Institute of the Ministry of water resources in 1992; the short term management plan of Heihe River Basin approved by the State Council in 2001; the compilation of historical documents of water regulation of Heihe River by the administration of Heihe River Basin in 2008 》In 2014, the research on the reasonable allocation scheme of water resources in Jiuquan Basin of the Taolai River Basin was compiled by the Taolai River Basin Authority.
Data source: survey data of Heihe River Basin Authority; Data introduction: in 2010, Sunan County, Ganzhou District, Minle County, Linze County, Gaotai County, Shandan County, Jinta County, Ejina, Suzhou District and Jiayuguan used water for living, industry, agriculture, urban and rural ecology.
This data mainly includes the distribution of city, county, township and village level residential areas in the Heihe River Basin, and the data base year is 2009. The data is based on the existing data of residential areas in Heihe River Basin, the latest Google electronic map and the atlas of Gansu Province. There are two main attributes of the data, i.e. residential area classification and total name. The residential area classification is classified according to level 1 - City, level 2 - County, level 3 - Township and level 4 - village.
Data overview: this set of data mainly includes the spatial distribution of major roads in the heihe river basin, the attributes include road classification and road coding, and the data base year is 2010. Data preparation process: this set of data is based on the topographic map, remote sensing image and the latest road traffic map updated by the transportation department of gansu province in 2009. Data description: there are two important attributes of the data, namely, road classification and road code. The road classification is divided into national road, provincial road, county road, township road and private road. The road code is defined in accordance with the highway grade code of the traffic department.
Ⅰ. Overview This data set is based on Landsat MSS, TM and ETM Remote sensing data by means of satellite remote sensing. Using a hierarchical land cover classification system, the data divides the whole region into six first-class classifications (cultivated land, forest land, grassland, water area, urban and rural areas, industrial and mining land, residential land and unused land), and 31 second-class classifications. Ⅱ. Data processing description The data set is based on Landsat MSS, TM and ETM Remote sensing data as the base map, the data set projection is set as Alberts equal product projection, the scale is set at 1:24,000 for human-computer interactive visual interpretation, and the data set storage form is ESRI coverage format. Ⅲ. Data content description The data set adopts a hierarchical land cover classification system, which is divided into 6 first-class classifications (cultivated land, forest land, grassland, water area, urban and rural areas, industrial and mining land, residential land and unused land), and 31 second-class classifications. Ⅳ. Data use description The data can be mainly used in national land resources survey, climate change, hydrology and ecological research.
Field survey data of ecological vegetation sample in ejin delta during the project implementation period. A sample of ecological vegetation survey near 31 groundwater salinity observation points in ejin delta.The main investigation items include: plant species, plant structure, number, height, base diameter, crown width, coverage, frequency, etc.Time: 2010 and 2011 (july-august).
"Heihe River Basin Ecological hydrological comprehensive atlas" is supported by the key project of Heihe River Basin Ecological hydrological process integration research. It aims at data arrangement and service of Heihe River Basin Ecological hydrological process integration research. The atlas will provide researchers with a comprehensive and detailed background introduction and basic data set of Heihe River Basin. The boundary map of the Heihe River Basin in 2010 is one of the basic geographic part of the atlas, with a scale of 1:2500000, positive axis equal product conic projection and standard latitude of 25 47。 Data sources: 2010 Heihe River basin boundary data, 2010 Heihe River Basin road data, 2008 1 million Heihe River basin administrative boundary data, 2009 Heihe River Basin residential area data, 2009 100000 river data
Taking Landsat series data as the main data source, including KH in 1965 (only including Gurinai and Guaizi Lake), MSS in 1975, TM in 1990, 1995, 2006 and 2010, and ETM in 2000. Before information extraction, remote sensing images are preprocessed by image synthesis, mosaic, fusion, geometric correction and image enhancement. In the process of correction, ETM + image in 2000 is corrected by 1:100000 topographic map and used as reference image. The 4, 3 and 2 band standard pseudocolor synthesis scheme is selected for image synthesis; during correction, 7 × 8 control points are evenly selected on each image, and the average positioning error is less than 1 pixel, that is, the ground distance is less than 30m. In other years, the datum image of 2000 is used as the reference image for image registration, so that the pixels with the same name on different images have the same geographical coordinates. After correction and registration, the whole image maintains the 30 m spatial resolution of TM. Through field correction, the accuracy of qualitative analysis can be ensured to be over 95%.