Spectroscopic determination of leaf water content using continuous wavelet analysis
Spectroscopic determination of leaf water content using continuous wavelet analysis
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DOI：
10.1109/igarss.2010.5654453
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发表时间：
2010-07
期刊：
影响因子：
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通讯作者：
T. Cheng;B. Rivard;A. Sánchez-Azofeifa
中科院分区：
文献类型：
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作者：
T. Cheng;B. Rivard;A. Sánchez-Azofeifa
叶片水分占干质量的百分比(LWCD)，也称为燃料水分含量，是火灾风险建模的关键变量。到目前为止，由于叶片水分和干质量对光谱响应的混合影响，光谱反射率与LWCD之间的关系还知之甚少。很少有研究报道从叶片反射光谱中充分估计LWCD，特别是对于各种物种。在这项研究中，我们提出了一种有效的方法，利用连续小波分析从巴拿马47种热带森林树种的反射光谱中确定LWCD。该方法为选择对LWCD变化敏感的少量小波特征(小波系数)提供了一种新的途径。用这种新方法提取的小波特征与常用的谱指数进行了比较，分析了它们与LWCD的关系。结果表明，LWCD与水指数的相关性较差，但与提取的小波特征具有较强的相关性。对一系列物种的LWCD的准确估计是使用这些小波特征中的任何一个来实现的，并且可以使用它们的组合来略微改进。
Leaf water content as a percentage of dry mass (LWCD), also termed fuel moisture content, is a critical variable for fire risk modeling. To date, the relationship between spectral reflectance and LWCD is poorly understood due to the mixed effect of leaf water and dry mass on spectral response. Few studies have reported an adequate estimation of LWCD from leaf reflectance spectra, in particular for a variety of species. In this study, we propose an effective approach, using continuous wavelet analysis, to determine LWCD from reflectance spectra for 47 tropical forest species in Panama. The proposed method provides a new way to select a small number of wavelet features (wavelet coefficients) that are sensitive to changes in LWCD. Wavelet features derived using this new method are compared with common spectral indices in terms of their relationship with LWCD. Results demonstrate that LWCD is poorly correlated to the water indices but strongly correlated to the derived wavelet features. Accurate estimates of LWCD across a range of species are achieved using any of those wavelet features and can be slightly improved using a combination of them.