Abstract
Wetland monitoring is of great significance to wetland protection. In this paper, multiscale segmentation object-oriented method is used to extract information from multispectral data and tilt image data acquired by UAV. Then, a method of multicondition difference merging based on super-pixel segmentation is proposed to extract information at a single level. The experimental results show that the overall accuracy of multilevel information extraction after multiscale segmentation is 88.03%, kappa coefficient is 86.12%, while the overall accuracy of single-level information extraction is 86.32%, and kappa coefficient is 84.12%, which shows that the improved single-level method can also achieve the accuracy of multilevel information extraction. It can solve the disadvantages of multiscale segmentation and classification time-consuming and complex inheritance relationship.
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The study was supported by the National Natural Science Foundation of China (No. 41671100).
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This article is part of the Topical Collection on Geological Modeling and Geospatial Data Analysis
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Du, Y., Bai, Y. & Wan, L. Wetland information extraction based on UAV multispectral and oblique images. Arab J Geosci 13, 1241 (2020). https://doi.org/10.1007/s12517-020-06205-w
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DOI: https://doi.org/10.1007/s12517-020-06205-w