首页> 外文会议>International Conference on Signal Processing(ICSP'06); 20061116-20; Guilin(CN) >Simulated Hyperspectral Data Analysis using Continuum Removal: Case Study on Leaf Chlorophyll Prediction
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Simulated Hyperspectral Data Analysis using Continuum Removal: Case Study on Leaf Chlorophyll Prediction

机译:使用连续去除法的高光谱模拟数据分析:以叶绿素预测为例

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Vegetation spectrum is a very complicated curve caused by its biochemical and biophysical properties. The development of hyperspectral technology makes it possible to obtain a continuous spectral curve from visible to shortwave infrared rather than several isolated broad bands. Inversion of biochemical information from it is an important and practically valuable research. In this paper, we compared two area-based vegetation indices, TVI and ABNC, in 3 aspects: (l)sensitivity to chlorophyll concentrations, (2)insensitivity to dry matters concentrations and (3)insensitivity to mesophyll structure. Results show that ABNC, which is based on continuum removed spectra, is much better than TVI. Continuum removal is good at elimination of the influence of dry matters and mesophyll structure in visible region and near infrared reflectance peak with our model simulated leaf spectral data.
机译:植被光谱是由其生化和生物物理特性引起的非常复杂的曲线。高光谱技术的发展使得有可能获得从可见光到短波红外的连续光谱曲线,而不是几个孤立的宽带。从中提取生化信息是一项重要且实用的研究。在本文中,我们在三个方面比较了两个基于区域的植被指数:TVI和ABNC:(1)对叶绿素浓度的敏感性,(2)对干物质浓度的敏感性和(3)对叶肉结构的敏感性。结果表明,基于连续谱去除光谱的ABNC比TVI更好。利用我们的模型模拟叶片光谱数据,连续去除有利于消除可见区域和近红外反射峰中的干物质和叶肉结构的影响。

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