收稿日期: 2009-05-06
修回日期: 2009-09-22
网络出版日期: 2010-03-23
基金资助
国家自然科学基金(40876092); 国家高技术研究发展计划项目(2006AA09Z155); 广东省科技计划项目(2008B030303026); 广东
省自然科学基金团队项目(8351030101000002); 中国科学院南海海洋研究所知识创新工程领域前沿项目(LYQY200701)
Hyperspectral recognition of seagrass in optically shallow water
Received date: 2009-05-06
Revised date: 2009-09-22
Online published: 2010-03-23
Supported by
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杨超宇,杨顶田,赵俊, . 光学浅水海草高光谱识别[J]. 热带海洋学报, 2010 , 29(2) : 74 -79 . DOI: 10.11978/j.issn.1009-5470.2010.02.074
The authors use the spectrum of Thalassia to analyze the optical properties of seagrass substrates. The results show that in the range of 450?780nm, the derivative spectral reflectance of seaweed can reflect the variability of leaf area index with high accuracy. Red edge calculated by the first order derivative spectrometry is a good indicator for chlorophyll concentration. In the derivative spectra, there are two obvious peaks at 625nm and 675nm, and the difference between the two peak values is large for seagrass. Other dominated peaks appear at 550nm, 700nm, and 750?780nm. Combining with the relationship between seagrass coverage rate and the spectral properties, the properties of peak distribution can be utilized to classify plenty of re-mote sensing data sets in order to monitor large scale spatio-temporal dynamic patterns.
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