Sun-Induced Chlorophyll Fluorescence III: Benchmarking Retrieval Methods and Sensor Characteristics for Proximal Sensing

Abstract

The interest of the scientific community on the remote observation of sun‐induced chlorophyll fluorescence (SIF) has increased in the recent years. In this context, hyperspectral ground measurements play a crucial role in the calibration and validation of future satellite missions. For this reason, the European cooperation in science and technology (COST) Action ES1309 OPTIMISE has compiled three papers on instrument characterization, measurement setups and protocols, and retrieval methods (current paper). This study is divided in two sections; first, we evaluated the uncertainties in SIF retrieval methods (e.g., Fraunhofer line depth (FLD) approaches and spectral fitting method (SFM)) for a combination of off-the-shelf commercial spectrometers. Secondly, we evaluated how an erroneous implementation of the retrieval methods increases the uncertainty in the estimated SIF values. Results show that the SFM approach applied to high-resolution spectra provided the most reliable SIF retrieval with a relative error (RE) ≤6% and <5% for F687 and F760, respectively. Furthermore, although the SFM was the least affected by an inaccurate definition of the absorption spectral window (RE = 5%) and/or interpolation strategy (RE = 15%–30%), we observed a sensitivity of the SIF retrieval for the simulated training data underlying the SFM model implementation.

A Review of Current and Potential Applications of Remote Sensing to Study the Water Status of Horticultural Crops

“…Spectral sensors provide the capability to capture broader physiological properties of the crop, such as greenness (related to leaf chlorophyll content and health) and biomass, that generally correlate with crop water status [82,108]. Narrower band spectral sensors provide direct insight into specific biophysical and biochemical properties of crops, such as via photochemical reflectance index (PRI) and solar-induced chlorophyll fluorescence (SIF), which reflects a plant's photosynthetic efficiency [109,110]. Thermal-based sensors capture the temperature of the crop's surface, which indicates the plant's stress (both biotic and abiotic) [53].…”

“…A quantitative product, such as SIF, derived from hyperspectral data will have the potential for direct quantification of water stress [204,205,304]. In this regard, the upcoming FLEX satellite mission [305,306] and recent advances in aerial spectroradiometry [109,132,137,[307][308][309][310] dedicated for observation of SIF may be unique and powerful tools for high-value horticultural crops.…”

Sun-Induced Chlorophyll Fluorescence I: Instrumental Considerations for Proximal Spectroradiometers

“…This work has included instrumentation; measurement protocols; and retrieval techniques. To make the results of these efforts available to a wider audience, the OPTIMISE community has compiled three papers summarizing their shared experience on instrumental characterization (this article), measurement setups and protocols [12] and retrieval methods [13]. These review articles aim to summarize the state-of-the-art, guidelines, current needs, and future directions concerning spectroradiometric measurements for SIF retrieval.…”

“…Sources of error in the proximal sensing of SIF can be separated into three groups, as they are related to: (1) instrumentation-sensors introduce biases and noise in the recorded signal; (2) measurement procedure-this can induce significant errors in observations or assist avoiding them (in addition inadequate measurement procedures can limit or prevent the integration of SIF estimates with other variables in space and time and through different scales); (3) retrieval; different retrieval algorithms can lead to different values and each varies in sensitivity to uncertainties. These topics are addressed in the three related articles arising from the cooperation run in the context of the COST Action OPTIMISE in this special issue: the current paper, and references [12] and [13], respectively.…”

“…Traceability and uncertainty propagation are rarely considered in proximal sensing applications, both in the laboratory and especially in the field. However, since SIF is a weak signal sensitive to several sources of error [13,34], in this paper the propagation of uncertainties is necessary to determine which observations can provide reliable SIF retrievals that can be understood according to the precision and accuracy requirements of each application or scientific question.…”