This data mainly reflects the current situation of land use in Xinjiang around 2000. According to the construction of national resource and environment information system database, the land use classification system of Chinese Academy of Sciences established by TM satellite image interpretation mark of land use in Xinjiang area, the land in Xinjiang is divided into 6 first-class and 24 second-class categories, with more than 100000 map spots and all land classification elements All in one layer (xj2000td).
|collect time||2000/01/01 - 2000/12/31|
|collect place||Xinjiang Uygur Autonomous Region|
|data size||87.6 MB|
The data comes from Landsat TM and ETM image data downloaded from the website of the University of Maryland around the 2000s in Xinjiang and 1:100000 topographic map published in the 1970s in the collection of the Xinjiang branch of the Chinese Academy of Sciences.
Firstly, the TM data is screened, and the cloud coverage ratio is less than 4%, or the main ground objects are less covered. Combined with 1:100000 topographic map, the selected image is geometrically corrected, then spliced, and leveled. Finally, it becomes a vectorized product, and each TM data is visually interpreted and manually vectorized by professionals according to the interpretation mark and classification system to generate a coverage grid Then, ArcGIS software is used to convert coverage data into SHP data, and cost data is generated through projection conversion.
This data is processed by the geographic information and cartography professionals of Xinjiang Institute of ecology and geography, Chinese Academy of Sciences. From the scanning of paper data, screening of image data, precise geometric correction, splicing, color equalization to digital vectorization and manual interpretation, the whole operation process complies with the relevant national standards, and the digital error is controlled within 2 pixels, ensuring the vectorization boundary The boundary between the line and the topographic map is exactly the same. The vector data truly reflects the shape and attribute information of the features, and the accuracy of the data is as high as 99%.
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