NDLI: Flower species identification and coverage estimation based on hyperspectral remote sensing data

Content Provider	IEEE Xplore Digital Library
Author	Gai Yingying Fan Wenjie Xu Xiru Zhang Yuanzhen
Copyright Year	2011
Description	Author affiliation: China Meteorological Administration Training Centre, Beijing, China, 100081 (Zhang Yuanzhen) \|\| Institute of RS and GIS, Peking University, Beijing, China, 100871 (Gai Yingying; Fan Wenjie; Xu Xiru)
Abstract	Monitoring grass species and coverage accurately makes a significant contribution to species diversity research and sustainable development of grassland ecosystem. Plants grown in grassland usually own unique spectral characteristics in florescence. Compared with the nutrient stage, species are more easily identified during florescence. In this study, flowers such as Galium verum Linn., Hemerocallis citrina Baroni, Serratula centauroides Linn., Clematis hexapetala Pall., Lilium concolor var. pulchellum, Lilium pumilum and Artemisia frigida Willd. Sp. Pl. were identified, using some canopies spectra analysis and feature extraction methods. Validation shows that when the coverage of flowers is greater than 10%, the accuracy of identification methods will be higher than 90%. Based on this result, linear unmixing model is adopted to calculate the area ratios of flowers in quadrates. Results show that linear unmixing model is an effective method for estimating the coverage of grassland flowers with the mean retrieval error of about 4%.
Starting Page	1243
Ending Page	1246
File Size	393515
Page Count	4
File Format	PDF
ISBN	9781457710032
ISSN	21537003
e-ISBN	9781457710056
DOI	10.1109/IGARSS.2011.6049424
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-07-24
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Reactive power Wavelet transforms Reflectivity Filtering Soil Hyperspectral imaging Mixed spectra unmixing Hulunbeier grassland Species diversity Flower Spectral characteristics extraction
Content Type	Text
Resource Type	Article

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