基于连续小波分析的植物理化参数反演中光谱分辨率影响分析

基于一套由PROSPECT模型模拟的包含叶绿素含量(Cab)、类胡萝卜素含量(Car)和叶片水含量(LWC)等重要植物生理生化参数及其光谱的数据,通过对光谱进行系列梯度的重采样和CWA分析,详细研究了光谱分辨率对植物生理生化参数反演的影响.结果表明:(1)采用CWA能够成功提取对Cab,Car和LWC等参数敏感的特征并建立具有较高精度的反演模型;(2)随着光谱分辨率的降低,敏感小波特征的数量、相关性以及反演精度总体均呈下降趋势,但下降的幅度、拐点均不相同,体现出分辨率对不同参数影响的差异性;(3)采用CWA反演建模时,不同植物生理生化参数对光谱分辨率敏感性差异较大,LWC敏感性较低,Cab次之,Car敏感性较高.根据这一结果,采用CWA反演Car,Cab和LWC时光谱数据在分辨率不低于8nm,32nm和64nm时能够得到较理想的结果.上述研究能够为实际中进行植被生理生化参数监测时的传感器选择提供依据.

Impact analysis of spectral resolution on retrieving plant biophysical and biochemical parameters based on continuous wavelet analysis

In this study, a simulated foliar spectral dataset based on the empirical PROSPECT model was generated according to variations of chlorophyll content (Cab) , carotenoid content (Car) , and leaf water content (LWC) .The spectra data were then resampled to a gradient of spectral resolutions and conducted a CWA analysis.The analysis of the spectral resolution impact on retrieving the plant biophysical and biochemical parameters was then performed.The results showed that: (1) CWA can be used to successfully extract sensitive features and to establish retrieving models of parameters including Cab, Car and LWC with high accuracy. (2) With decline of spectral resolution, the number of sensitive features, their correlation, and retrieving accuracy tend to decrease.However, the decline amplitude and the inflection point of the decline curves are all different, which reflected the different impact of the spectral resolution different for different parameters. (3) A significant difference on the sensitivity of spectral resolution was found among different plant biophysical and biochemical parameters, with the LWC appeared to be the most insensitive, followed by Cab, and Car.Based on this result, in retrieving Car, Cab and LWC with CWA, a reasonable result is expected only if the spectral resolution is no lower than 8 nm, 32 nm and 64 nm, respectively.The present study provides a basic understanding in selection of hyperspectral sensors for retrieving and monitoring of plant biophysical and biochemical parameters with the CWA method.