TR32-Database: Database of Transregio 32

[1086] - Modeling the impact of spectral sensor configurations on the FLD retrieval accuracy of sun-induced chlorophyll fluorescence

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Damm, A., Erler, A., Hillen, W., Meroni, M., Schaepman, M., Verhoef, W., Rascher, U., 2011. Modeling the impact of spectral sensor configurations on the FLD retrieval accuracy of sun-induced chlorophyll fluorescence. Remote Sensing of Environment, 115 (8), 1882 - 1892. DOI: 10.1016/j.rse.2011.03.011.
Title(s):Main Title: Modeling the impact of spectral sensor configurations on the FLD retrieval accuracy of sun-induced chlorophyll fluorescence
Description(s):Abstract: Chlorophyll fluorescence is related to photosynthesis and can serve as a remote sensing proxy for estimating photosynthetic energy conversion and carbon uptake. Recent advances in sensor technology allow remote measurements of the sun-induced chlorophyll fluorescence signal (Fs) at leaf and canopy scale. The commonly used Fraunhofer Line Depth (FLD) principle exploits spectrally narrow atmospheric oxygen absorption bands and relates Fs to the difference of the absorption feature depth of a fluorescensing and a non-fluorescensing surface. However, due to the nature of these narrow bands, Fs retrieval results depend not only on vegetation species type or environmental conditions, but also on instrument technology and processing algorithms. Thus, an evaluation of all influencing factors and their separate quantification is required to further improve Fs retrieval and to allow a reproducible interpretation of Fs signals. Here we present a modeling study that isolates and quantifies the impacts of sensor characteristics, such as spectral sampling interval (SSI), spectral resolution (SR), signal to noise ratio (SNR), and spectral shift (SS) on the accuracy of Fs measurements in the oxygen A band centered at 760 nm (O2-A). Modeled high resolution radiance spectra associated with known Fs were spectrally resampled, taking into consideration the various sensor properties. Fs was retrieved using the three most common FLD retrieval methods, namely the original FLD method (sFLD), the modified FLD (3FLD) and the improved FLD (iFLD). The analysis investigates parameter ranges, which are representative for field and airborne instruments currently used in Fs research (e.g., ASD FieldSpec, OceanOptics HR, AirFLEX, AISA, APEX, CASI, and MERIS). Our results show that the most important parameter affecting the retrieval accuracy is SNR, SR accounts for≤40% of the error, the SSI for≤12%, and SS for≤7% of the error. A trade-off study revealed that high SR can partly compensate for low SNR. There is a strong interrelation between all parameters and the impact of specific parameters can compensate or amplify the influence of others. Hence, the combination of all parameters must be considered by the evaluation of sensors and their potential for Fs retrieval. In general, the standard FLD method strongly overestimates Fs, while 3FLD and iFLD provide a more accurate estimation of Fs. We conclude that technical sensor specifications and the retrieval methods cause a significant variability in retrieved Fs signals. Results are intended to be one relevant component of the total uncertainty budget of Fs retrieval and have to be considered in the interpretation of retrieved Fs signals.
Identifier(s):DOI: 10.1016/j.rse.2011.03.011
Responsible Party
Creator(s):Author: Alexander Damm
Author: André Erler
Author: Walter Hillen
Author: Michele Meroni
Author: Michael Schaepman
Author: Wout Verhoef
Author: Uwe Rascher
TR32 Topic:Vegetation
Subject(s):CRC/TR32 Keywords: Chlorophyll Fluorescence
File Details
File Name:1-s2.0-S0034425711000885-main.pdf
Data Type:Text
File Size:1131 kB (1.104 MB)
Date(s):Available: 2011-04-13
Mime Type:application/pdf
Download Permission:OnlyTR32
General Access and Use Conditions:According to the TR32DB data policy agreement.
Access Limitations:According to the TR32DB data policy agreement.
North:-no map data
Measurement Region:None
Measurement Location:--None--
Specific Informations - Publication
Source:Remote Sensing of Environment
Page Range:1882 - 1892
Metadata Details
Metadata Creator:Sandra Steinke
Metadata Created:2014-09-21
Metadata Last Updated:2014-09-21
Funding Phase:2
Metadata Language:English
Metadata Version:V40
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