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	Flower Species Identification and Coverage Estimation Based on Hyperspectral Remote Sensing Data in Hulunbeier Grassland
	Gai Y. Y. ; Fan W. J. ; Xu X. R. ; Yan B. Y. ; Wang H. J. ; Liu Y.
	2011
关键词	Hulunbeier grassland Species diversity Florescense Spectral characteristics extraction Mixed spectra unmixing
英文摘要	Monitoring grassland species and area real-timely and accurately is of great significance in species diversity research, as well as in sustainable development of ecosystem. Flowers have their own unique spectral characteristics. Compared with the nutrient stage, species are more easily identified by florescence. So, florescence is a critical period for identification. In the present paper, spectral differences among such flowers as Galium verum Linn., Hemerocallis citrina Baroni, Serratula centauroides Linn., Clematis hexupetala Pall., Lilium concolor var. pulchellum, Lilium pumilum and Artemisia frigida Willd. Sp. Pl. were found, along with identification methods, by analyzing canopies spectra and parametrizing characteristics. Verification results showed that when the coverage of flowers was greater than 10%, the accuracy of identification methods would be higher than 90%. On this basis, linear unmixing model was adopted to calculate the area of flowers in quadrates. Results showed that linear unmixing model was an effective method for estimating the coverage of flowers in grassland because the accuracy was about 4%.
出处	Spectroscopy and Spectral Analysis
卷	31
期	10
页	2778-2783
收录类别	SCI
语种	英语
ISSN号	1000-0593
内容类型	SCI/SSCI论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/24006]
专题	地理科学与资源研究所_历年回溯文献
推荐引用方式 GB/T 7714	Gai Y. Y.,Fan W. J.,Xu X. R.,et al. Flower Species Identification and Coverage Estimation Based on Hyperspectral Remote Sensing Data in Hulunbeier Grassland. 2011.

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