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Erschienen in:
28.02.2018
Remote sensing image land type data mining based on QUEST decision tree
Erschienen in: Cluster Computing | Sonderheft 4/2019
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Abstract
remote sensing image land type data mining was studied based on QUEST decision tree with Dongting Lake area as the research object. First of all, the texture feature of gray level co-occurrence matrix was expounded, and the texture size was selected to construct the QUEST decision tree model; secondly, through spectrum and texture feature of remote sensing data with different resolutions and combining with other auxiliary data, Dongting land information was explored, and land type was classified. Finally, the following conclusions were reached: multi-scale texture can better describe the texture feature of land, more effectively solve with the phenomenon of “same image for different object” in the classification results, and help to improve classification accuracy of high resolution image.