Abstract
A method for canopy Fluorescence Spectrum Reconstruction (FSR) is proposed in this study, which can be used to retrieve the solar-induced canopy fluorescence spectrum over the whole chlorophyll fluorescence emission region from 640–850 nm. Firstly, the radiance of the solar-induced chlorophyll fluorescence (Fs) at five absorption lines of the solar spectrum was retrieved by a Spectral Fitting Method (SFM). The Singular Vector Decomposition (SVD) technique was then used to extract three basis spectra from a training dataset simulated by the model SCOPE (Soil Canopy Observation, Photochemistry and Energy fluxes). Finally, these basis spectra were linearly combined to reconstruct the Fs spectrum, and the coefficients of them were determined by Weighted Linear Least Squares (WLLS) fitting with the five retrieved Fs values. Results for simulated datasets indicate that the FSR method could accurately reconstruct the Fs spectra from hyperspectral measurements acquired by instruments of high Spectral Resolution (SR) and Signal to Noise Ratio (SNR). The FSR method was also applied to an experimental dataset acquired in a diurnal experiment. The diurnal change of the reconstructed Fs spectra shows that the Fs radiance around noon was higher than that in the morning and afternoon, which is consistent with former studies. Finally, the potential and limitations of this method are discussed.
Highlights
Hyperspectral remote sensing has been used for detecting solar-induced chlorophyll fluorescence (Fs) of vegetation [1,2]
Spectral Fitting Method (SFM) assumes that the canopy reflectance and Fs can be described by smooth mathematical functions around the absorption line, which overcomes the unrealistic assumption made by the Fraunhofer Line Discriminator (FLD) method [12]
We proposed a Fluorescence Spectrum Reconstruction (FSR) method to reconstruct the solar-induced chlorophyll fluorescence spectrum over the whole fluorescence emission bands of 640–850 nm with hyperspectral measurements
Summary
Hyperspectral remote sensing has been used for detecting solar-induced chlorophyll fluorescence (Fs) of vegetation [1,2]. Retrieval of Fs from hyperspectral remote sensing data needs to decouple two contributions of the canopy up-welling radiance: the reflected solar radiation and the emitted fluorescence signal (Fs) [1]. The Fraunhofer Line Discriminator (FLD) method [8] for Fs estimation utilizes the Fraunhofer lines or telluric oxygen absorption lines of the solar spectrum (hereafter referred to as the absorption lines), where the Fs accounts for a relatively larger portion of the total up-welling radiance of canopy [9]. The FLD method assumes that canopy reflectance and Fs are constant in and out of the absorption line considered, which is unrealistic and makes the retrieved values of Fs less accurate [10]. SFM assumes that the canopy reflectance and Fs can be described by smooth mathematical functions (e.g., polynomial functions) around the absorption line, which overcomes the unrealistic assumption made by the FLD method [12]. A statistical method for Fs estimation has been proposed, which is based on a linear forward model derived from the results of the Singular
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