A Method to Reconstruct the Solar-Induced Canopy Fluorescence Spectrum from Hyperspectral Measurements

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 OPEN ACCESSRemote Sens. 2014, 6 10172 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.

New Spectral Fitting Method for Full-Spectrum Solar-Induced Chlorophyll Fluorescence Retrieval Based on Principal Components Analysis

“…Some recent studies have been proposed focusing on the full-spectrum SIF retrieval based on the SFM algorithm [30,31]. The reconstruction of reflectance and SIF spectra is a major problem in full-spectrum SIF retrieval.…”

“…There are four absorption bands in this spectral region that have the potential for SIF retrieval, including the Hα line centered at 656.5 nm, the O2-B band at 687.1 nm, the water vapor band at 718.8 nm and the O2-A band at 760.7 nm. However, as the water vapor absorption band is quite unstable when used with field-measured data [31], it was excluded in this study. Three absorption bands (Hα, O2-B and O2-A) were, therefore, employed.…”

“…However, for full-spectrum SIF retrieval, it is difficult to model the reflectance and SIF spectra accurately using simple mathematical functions, as was commonly done in earlier research. Inspired by earlier studies [31,32], PCA, a commonly used method for feature extraction, was employed in this study for the accurate estimation of both reflectance and SIF spectra.…”

“…Inspired by the earlier studies of SIF retrieval based on feature extraction (PCA or SVD) [31,32], here we propose a new Full-spectrum Spectral Fitting Method (F-SFM) for the retrieval of SIF. The main objectives of this paper are: (1) to present a new PCA-based full-spectrum SIF retrieval method (F-SFM); (2) to assess the accuracy of F-SFM under different SR and SNR conditions using a simulated dataset; (3) to test the performance of F-SFM using field-measured data.…”

“…To deal with these problems, Principal Components Analysis (PCA), which is widely used in the decomposition and reconstruction of signals, can serve as an alternative method for the SIF retrieval because both the canopy reflectance and SIF have some unique spectral characteristics that can be extracted from a proper training dataset. Zhao et al [31] proposed a Fluorescence Spectrum Reconstruction (FSR) method to reconstruct the full-spectrum SIF based on the Singular Vector Decomposition (SVD) technique, which is also a method for feature extraction similar to PCA. This method uses the SIF values from within five absorption bands-these values having been retrieved by the SFM (with the reflectance and SIF spectra around each band being modeled by polynomials).…”