WAFER: A new method to retrieve sun-induced fluorescence based on spectral wavelet decompositions

Abstract

Sun-induced fluorescence (SIF) as a close remote sensing based proxy for photosynthesis is accepted as a useful measure to remotely monitor vegetation health and gross primary productivity. It is therefore important to develop methods that allow for its precise and reliable retrieval from radiance measurements with spectral resolutions that have been increasing over the past few years. Retrieval methods are catching up to the increasing complexity of the available datasets making use of their whole information extent (spectral, spatial and temporal) but the comparability of different SIF retrievals and consistency across scales is still limited.In this work we present the new retrieval method WAFER (WAvelet decomposition FluorEscence Retrieval) based on wavelet decompositions of the measured spectra of reflected radiance as well as a reference radiance not containing fluorescence. By comparing absolute absorption line depths by means of the corresponding wavelet coefficients, a relative reflectance is retrieved independently of the fluorescence, i.e. without introducing a coupling between reflectance and fluorescence. The fluorescence can then be derived as the remaining offset. This method can be applied to arbitrary chosen wavelength windows in the whole spectral range, such that all the spectral data available is exploited, including the separation into several frequency (i.e. width of absorption lines) levels and without the need of extensive training datasets.At the same time, the assumptions about the reflectance shape are minimal and no spectral shape assumptions are imposed on the fluorescence, which not only avoids biases arising from wrong or differing fluorescence models across different spatial scales and retrieval methods but also allows for the exploration of this spectral shape for different measurement setups.WAFER is tested on a synthetic dataset as well as several diurnal datasets acquired with a field spectrometer (FloX) over an agricultural site. We compare the WAFER method to two established retrieval methods, namely the improved Fraunhofer line discrimination (iFLD) method and spectral fitting method (SFM) and find a good agreement with the added possibility of exploring the true spectral shape of the offset signal and free choice of the retrieval window. On our synthetic dataset, WAFER seems to outperform the SFM and works best in a spectral window only containing solar Fraunhofer lines where we achieve a relative retrieval error of 10% on average. Applied to the real dataset, the method returns reasonable diurnal cycles for SIF and can, due to the decoupling of reflectance and fluorescence retrieval, reveal interesting trends at times when vegetation canopies may experience a midday depression that remain largely unobserved with current methods.