1. 基于无人机图像分形特征的油松受灾级别判定.
- Author
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费运巧, 刘文萍, 陆鹏飞, and 骆有庆
- Abstract
The unmanned aerial vehicle (UAV) is useful in taking remotely sensed images for forestry applications. It used the UAV to acquire images of Chinese-pine field and then segmented the individual sample pine-tree from images. It extracted the texture features for each individual sample pine-tree. Based on the calculated texture features and the leaf loss rate,the degree of disaster could be classified and compared with the ground survey results to exploring the most appropriate texture features for this study. Experimental results show that three fractal texture features including fractal dimension,lacunarity and Fractal Dimension Gradient can be used for predicting the leaf loss rate of individual tree accurately. The experiment shows that this approach can be applied to the disaster classification issue of the Chinese-pine field for images obtained by the UAV. [ABSTRACT FROM AUTHOR]
- Published
- 2017
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