基于无人机影像的荒漠地表类型信息提取

doi:10.13866/j.azr.2019.03.29

Abstract

Abstract: Based on the images of unmanned aerial vehicle (UAV),in this study the surface type information of the Gurbantunggut Desert was extracted,and the object-oriented multi-scale segmentation was used to extract the information of the sample plots of surface types from the spectrum,shape,texture and vegetation index.The results showed that:① The best segmentation scale for the different desert surface types was different;② The features of surface types with different desertification levels were similar and could not be distinguished by single characteristics;③ Compared with the pixel-based maximum likelihood method,the object-oriented multi-scale segmentation method was improved significantly.The overall classification accuracies of the object-oriented slightly,moderately and seriously desertified areas were 93.00%,91.83% and 93.50% respectively,and they were 10.34%,11.86% and 12.50% higher than those of the pixel-based maximum likelihood method.The results revealed that the object-oriented multi-scale segmentation method could be used to extract the desert surface type information with high accuracy for the UAV visible image.

Key words: UAV image, desert, land surface type, information extraction, the Gurbantonggut desert

PENG Jia-yi, WANG Xin-jun, ZHU Lei, ZHAO Chen-yi, XU Xiao-long. Information Extraction of Desert Surface Types Based on UAV Image[J].Arid Zone Research, 2019, 36(3): 771-780.

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Information Extraction of Desert Surface Types Based on UAV Image

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