Species identification of wetland vegetation based on spectral characteristics
CHAI Ying1, RUAN Renzong1, CHAI Guowu2, FU Qiaoni1
1. School of Earth Sciences and Engineering, Hohai University, Nanjing 210098, China;
2. Hydrology and Water Resources Rureau of Henan Province, Nanyang 474500, China
Certain spectral characteristics have a direct impact on accuracy and efficiency of identifying the wetland vegetation. In this paper, the authors mapped wetland vegetation with 3 m spatial resolution for HyMap image data from Sherman Island of California's Sacramento-San Joaquin delta. The first-derivative spectral features and spectral absorption features of different species were analyzed by the method of stepwise discriminate analysis, and the spectral characteristic parameters with better classification accuracy were screened to identify species of wetland vegetation in C4.5 decision tree classifier. The results showed that the absorption features of four plants have larger differences than first-derivative spectral features. The results also showed that C4.5 decision tree classifier in combination with the first-derivative spectral characteristics and spectral absorption characteristics could be effective in distinguishing wetland vegetation and allowing for species-level detection.
柴颖, 阮仁宗, 柴国武, 傅巧妮. 基于光谱特征的湿地植物种类识别[J]. 国土资源遥感, 2016, 28(3): 86-90.
CHAI Ying, RUAN Renzong, CHAI Guowu, FU Qiaoni. Species identification of wetland vegetation based on spectral characteristics. REMOTE SENSING FOR LAND & RESOURCES, 2016, 28(3): 86-90.
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2016, Vol. 28 
