Impact of Atmospheric Inversion Effects on Solar-Induced Chlorophyll Fluorescence: Exploitation of the Apparent Reflectance as a Quality Indicator

Abstract

Abstract:In the last decade, significant progress has been made in estimating Solar-Induced chlorophyll Fluorescence (SIF) by passive remote sensing techniques that exploit the oxygen absorption spectral regions. Although the O 2 -B and the deep O 2 -A absorption bands present a high sensitivity to detect SIF, these regions are also largely influenced by atmospheric effects. Therefore, an accurate Atmospheric Correction (AC) process is required to measure SIF from oxygen bands. In this regard, the suitability of a two-step approach, i.e., first an AC and second a Spectral Fitting technique to disentangle SIF from reflected light, has been evaluated. One of the advantages of the two-step approach resides in the derived intermediate products provided prior to SIF estimation, such as surface apparent reflectance. Results suggest that errors introduced in the AC, e.g., related to the characterization of aerosol optical properties, are propagated into systematic residual errors in the apparent reflectance. However, of interest is that these errors can be easily detected in the oxygen bands thanks to the high spectral resolution required to measure SIF. To illustrate this, the predictive power of the apparent reflectance spectra to detect and correct inaccuracies in the aerosols characterization is assessed by using a simulated database with SCOPE and MODTRAN radiative transfer models. In 75% of cases, the aerosol optical thickness, the Angstrom coefficient and the scattering asymmetry factor are corrected with a relative error below of 0.5%, 8% and 3%, respectively. To conclude with, and in view of future SIF monitoring satellite missions such as FLEX, the analysis of the apparent reflectance can entail a valuable quality indicator to detect and correct errors in the AC prior to the SIF estimation.

The High-Performance Airborne Imaging Spectrometer HyPlant—From Raw Images to Top-of-Canopy Reflectance and Fluorescence Products: Introduction of an Automatized Processing Chain

“…The series expansion is assumed here to avoid the division with the convolved spherical albedo term S (t 3 in Equation 3and ρ λ dd in Equation 4. See more details of this approximation in [59].…”

Quantitative Remote Sensing at Ultra-High Resolution with UAV Spectroscopy: A Review of Sensor Technology, Measurement Procedures, and Data Correction Workflows

“…Additionally, ARTMs are widely used for correcting multispectral and hyperspectral imagery satellite and airborne data [102,159] and high-altitude UAV images [125,126] for atmospheric influence on the path from the object to the sensor. Recent modeling studies suggest that atmospheric correction is important for very precise radiometric measurements, e.g., to estimate solar-induced chlorophyll fluorescence [160]. For reflectance studies, a detailed analysis is still missing.…”

Atmospheric Correction for Tower-Based Solar-Induced Chlorophyll Fluorescence Observations at O2-A Band

“…respectively, where T ↑ and T ↓ are the upward and downward atmospheric total transmittance (including the effects of absorption and scattering) from the TOC to height of the tower-based sensor, respectively, and <> represents convolution with the instrument spectral response function (ISRF). As the radiance or irradiance spectra by observed by spectrometers are already convolved with the ISRF, for the atmospheric absorption bands where the transmittance is spectrally unsmooth, it is not possible to calculate the top-of-canopy radiance or irradiance precisely using a fully physical approach due to the mathematical inequality between <a·b> and <a>·<b> [32], especially for data with high spectral resolution (as shown in Figure 1). the ISRF, for the atmospheric absorption bands where the transmittance is spectrally unsmooth, it is not possible to calculate the top-of-canopy radiance or irradiance precisely using a fully physical approach due to the mathematical inequality between <a·b> and <a>·<b> [32], especially for data with high spectral resolution (as shown in Figure 1).…”