Retrieval of sun-induced fluorescence using advanced spectral fitting methods

Cogliati, Sergio; Verhoef, W.; Kraft, Stefan; Sabater, Neus; Alonso, Luis; Vicent, Jorge; Moreno, José; Drusch, Matthias; Colombo, R.

doi:10.1016/j.rse.2015.08.022

Cited by 128 publications

(109 citation statements)

References 37 publications

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“…The first three indices can be easily calculated from the reflectance signature, while SIF retrieval requires more complex techniques. The SIF retrieval methods are generally based on the analysis of the radiance spectra at the oxygen absorption bands located at 760 nm (O 2 -A) and 687 nm (O 2 -B) [62,64]. In particular, we computed the far-red fluorescence comparing L inc (λ) and L ref (λ) spectral radiance inside and outside the O 2 -A band, according to the widely-used 3FLD (Fraunhofer Line Depth) approach [8,63].…”

Section: Retrieval Of Surface Reflectance and Fluorescencementioning

confidence: 99%

“…The analysis was carried out based on surface-atmosphere-coupled radiative transfer simulations by means of atmospheric MODerate resolution TRANsmission (MODTRAN5) code [66] and the Soil Canopy Observation Photosynthesis Energy balance (SCOPE) model [67]. The 4-flux coupled surface-atmosphere scheme has been implemented as described in [64,68], considering a Lambertian surface. This approach includes direct and diffuse target radiance, atmospheric path radiance and contribution from the surroundings (adjacency).…”

Section: Retrieval Of Surface Reflectance and Fluorescencementioning

confidence: 99%

“…We considered a restricted number of atmospheric and canopy parameters to limit the total number of simulations. The "standard" case of 19 described in [64] was used as the baseline; thus, we considered different O 2 -A band depths and fluorescence values to compare a wider range of environmental conditions. In particular, Aerosol Optical Thickness (AOT) varying between 0.1 and 0.4, ground-altitude between sea surface level to 0.15 km (proxy of surface pressure) and solar zenith angles of 30 • , 45 • and 60 • were considered in MODTRAN.…”

Section: Retrieval Of Surface Reflectance and Fluorescencementioning

confidence: 99%

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Surface Reflectance and Sun-Induced Fluorescence Spectroscopy Measurements Using a Small Hyperspectral UAS

et al. 2017

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This study describes the development of a small hyperspectral Unmanned Aircraft System (HyUAS) for measuring Visible and Near-Infrared (VNIR) surface reflectance and sun-induced fluorescence, co-registered with high-resolution RGB imagery, to support field spectroscopy surveys and calibration and validation of remote sensing products. The system, namely HyUAS, is based on a multirotor platform equipped with a cost-effective payload composed of a VNIR non-imaging spectrometer and an RGB camera. The spectrometer is connected to a custom entrance optics receptor developed to tune the instrument field-of-view and to obtain systematic measurements of instrument dark-current. The geometric, radiometric and spectral characteristics of the instruments were characterized and calibrated through dedicated laboratory tests. The overall accuracy of HyUAS data was evaluated during a flight campaign in which surface reflectance was compared with ground-based reference measurements. HyUAS data were used to estimate spectral indices and far-red fluorescence for different land covers. RGB images were processed as a high-resolution 3D surface model using structure from motion algorithms. The spectral measurements were accurately geo-located and projected on the digital surface model. The overall results show that: (i) rigorous calibration enabled radiance and reflectance spectra from HyUAS with RRMSE < 10% compared with ground measurements; (ii) the low-flying UAS setup allows retrieving fluorescence in absolute units; (iii) the accurate geo-location of spectra on the digital surface model greatly improves the overall interpretation of reflectance and fluorescence data. In general, the HyUAS was demonstrated to be a reliable system for supporting high-resolution field spectroscopy surveys allowing one to collect systematic measurements at very detailed spatial resolution with a valuable potential for vegetation monitoring studies. Furthermore, it can be considered a useful tool for collecting spatially-distributed observations of reflectance and fluorescence that can be further used for calibration and validation activities of airborne and satellite optical images in the context of the upcoming FLEX mission and the VNIR spectral bands of optical Earth observation missions (i.e., Landsat, Sentinel-2 and Sentinel-3).

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Section: Retrieval Of Surface Reflectance and Fluorescencementioning

confidence: 99%

Section: Retrieval Of Surface Reflectance and Fluorescencementioning

confidence: 99%

Section: Retrieval Of Surface Reflectance and Fluorescencementioning

confidence: 99%

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Surface Reflectance and Sun-Induced Fluorescence Spectroscopy Measurements Using a Small Hyperspectral UAS

et al. 2017

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“…Therefore, the SFM algorithm has the potential to retrieve the full-spectrum SIF. Recently, the SFM algorithm was used by Cogliati et al [30] for the retrieval of full-spectrum SIF from airborne HyPlant imagery and the performance of different fitting functions for reflectance and SIF was tested.…”

Section: Introductionmentioning

confidence: 99%

“…This means that it is quite difficult to simulate the reflectance spectra accurately at the O2-B band. The SIF spectra were often modeled using double Gaussian or Voigt functions [29,30] but this meant that a lot of parameters needed to be determined and thus the algorithm was not so robust. 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.…”

Section: Introductionmentioning

confidence: 99%

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

Liu

Zhang

et al. 2015

Remote Sensing

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Abstract:The full-spectrum Solar-Induced chlorophyll Fluorescence (SIF) within the 650800 nm spectral region can provide important information regarding physiological and biochemical activities in vegetation. This paper proposes a new Full-spectrum Spectral Fitting Method (F-SFM) for the retrieval of SIF spectra based on Principal Components Analysis (PCA). Using F-SFM, both the full-spectrum reflectance and SIF within the 650800 nm region were modeled by PCA based on a training dataset simulated by the Soil Canopy Observation, Photochemistry and Energy fluxes (SCOPE) model, and the weighting coefficients of the principal components were estimated by the least-squares fitting method. An iterative process was employed to improve the accuracy of the estimation of the reflectance. In each iteration, the SIF spectra retrieved from the last run were removed from the total upwelling radiance to minimize the small contribution of the SIF to the apparent reflectance outside the absorption bands. Then, the F-SFM algorithm was tested using both simulated and field-measured data with different Spectral Resolutions (SRs) and Signal-to-Noise Ratios (SNRs). For data with an SR of 0.3 nm and without noise, the Relative Root Mean Square Error (RRMSE) was less than 14% within the spectral region that was studied, and the peak-value ratio (SIF735/SIF685) was accurately estimated with an RRMSE of 3.56%. In addition, the F-SFM algorithm proved less sensitive to the SR than the three-band Fraunhofer Line Discrimination (3 FLD) and improved FLD (iFLD) methods. In OPEN ACCESSRemote Sens. 2015, 7 10627 the case of the field spectral data with SRs of 3 nm and 0.3 nm, the double-peak shape and the diurnal variation trend of the SIF spectra could be reasonably reconstructed by F-SFM, and the retrieved SIF values at the O2-A and O2-B bands were consistent with those retrieved by 3FLD from data with a high SR (0.3 nm) and SNR (1000). Therefore, the F-SFM method can provide full-spectrum SIF information with high accuracy even at relatively low SRs and SNRs, and shows promise for use in applications involving the SIF shape information.

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Assessment of SMAP soil moisture for global simulation of gross primary production

Chen

Liu

et al. 2017

J. Geophys. Res. Biogeosci.

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In this study, high‐quality soil moisture data derived from the Soil Moisture Active Passive (SMAP) satellite measurements are evaluated from a perspective of improving the estimation of the global gross primary production (GPP) using a process‐based ecosystem model, namely, the Boreal Ecosystem Productivity Simulator (BEPS). The SMAP soil moisture data are assimilated into BEPS using an ensemble Kalman filter. The correlation coefficient (r) between simulated GPP from the sunlit leaves and Sun‐induced chlorophyll fluorescence (SIF) measured by Global Ozone Monitoring Experiment‐2 is used as an indicator to evaluate the performance of the GPP simulation. Areas with SMAP data in low quality (i.e., forests), or with SIF in low magnitude (e.g., deserts), or both are excluded from the analysis. With the assimilated SMAP data, the r value is enhanced for Africa, Asia, and North America by 0.016, 0.013, and 0.013, respectively (p < 0.05). Significant improvement in r appears in single‐cropping agricultural land where the irrigation is not considered in the model but well captured by SMAP (e.g., 0.09 in North America, p < 0.05). With the assimilation of SMAP, areas with weak model performances are identified in double or triple cropping cropland (e.g., part of North China Plain) and/or mountainous area (e.g., Spain and Turkey). The correlation coefficient is enhanced by 0.01 in global average for shrub, grass, and cropland. This enhancement is small and insignificant because nonwater‐stressed areas are included.

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Retrieval of sun-induced fluorescence using advanced spectral fitting methods

Cited by 128 publications

References 37 publications

Surface Reflectance and Sun-Induced Fluorescence Spectroscopy Measurements Using a Small Hyperspectral UAS

Surface Reflectance and Sun-Induced Fluorescence Spectroscopy Measurements Using a Small Hyperspectral UAS

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

Assessment of SMAP soil moisture for global simulation of gross primary production

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