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

This page lists all metadata that was entered for this dataset. Only registered users of the TR32DB may download this file.

Feature
Request downloadRequest download
Full Name:
Affiliation:
eMail:
Purpose of use:
 
Bot check:
Type all characters with this
color
.
 
It is case sensitive.
 
 
 
Submit
Citation
Citation Options
Identification
Title:Main Title: Modeling the impact of spectral sensor configurations on the FLD retrieval accuracy of sun-induced chlorophyll fluorescence
Description: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:10.1016/j.rse.2011.03.011 (DOI)
Responsible Party
Creators:Alexander Damm (Author), André Erler (Author), Walter Hillen (Author), Michele Meroni (Author), Michael Schaepman (Author), Wouter Verhoef (Author), Uwe Rascher (Author)
Publisher:Elsevier
Publication Year:2014
Topic
TR32 Topic:Vegetation
Related Subproject:D2
Subject:Keyword: Chlorophyll Fluorescence
File Details
Filename:1-s2.0-S0034425711000885-main.pdf
Data Type:Text - Article
File Size:1.1 MB
Date:Available: 13.04.2011
Mime Type:application/pdf
Language:English
Status:Completed
Constraints
Download Permission:Only Project Members
General Access and Use Conditions:According to the TR32DB data policy agreement.
Access Limitations:According to the TR32DB data policy agreement.
Licence:[TR32DB] Data policy agreement
Geographic
Specific Information - Publication
Publication Status:Published
Review Status:Peer reviewed
Publication Type:Article
Source:Remote Sensing of Environment
Source Website:http://www.sciencedirect.com/science/article/pii/S0034425711000885
Issue:8
Volume:115
Number of Pages:11 (1882 - 1892)
Metadata Details
Metadata Creator:Sandra Steinke
Metadata Created:21.09.2014
Metadata Last Updated:21.09.2014
Subproject:D2
Funding Phase:2
Metadata Language:English
Metadata Version:V50
Metadata Export
Metadata Schema:
Dataset Statistics
Page Visits:1044
Metadata Downloads:0
Dataset Downloads:1
Dataset Activity
Feature
A download is not possibleDownload