TR32-Database: Database of Transregio 32

[1502] - Airborne based spectroscopy of red and far-red sun-induced chlorophyll fluorescence: Implications for improved estimates of gross primary productivity

All available metadata of the dataset are listed below. Some features are available, e.g. download of dataset or additional description file.

Features
Citation
Wieneke, S., Ahrends, H., Damm, A., Pinto, F., Stadler, A., Rossini, M., Rascher, U., 2016. Airborne based spectroscopy of red and far-red sun-induced chlorophyll fluorescence: Implications for improved estimates of gross primary productivity. Remote Sensing of Environment, 184, 654 - 667. DOI: 10.1016/j.rse.2016.07.025.
Identification
Title(s):Main Title: Airborne based spectroscopy of red and far-red sun-induced chlorophyll fluorescence: Implications for improved estimates of gross primary productivity
Description(s):Abstract: Remote sensing (RS) approaches commonly applied to constrain estimates of gross primary production (GPP) employ greenness-based vegetation indices derived from surface reflectance data. Such approaches cannot capture dynamic changes of photosynthesis rates as caused by environmental stress. Further, applied vegetation indices are often affected by background reflectance or saturation effects. Sun. induced chlorophyll fluorescence (F) provides the most direct measure of photosynthesis and has been recently proposed as a new RS approach to improve estimates of GPP and tracing plant stress reactions. This work aims to provide further evidence on the complementary information content of F and its relation to changes in photosynthetic activity compared to traditional RS approaches. We use the airborne imaging spectrometer HyPlant to obtain several F products including red fluorescence (F687), far-red fluorescence (F760), F760 yield (F760yield) and the ration between F687 and F760 (Fratio). We calculate several vegetation indices indicative for vegetation greenness. We apply a recently proposed F-based semi-mechanistic approach to improve the forward modeling of GPP using F760 and compare this approach with a traditional one based on vegetation greenness and ground measurements of GPP derived from chamber measurements. In addition, we assess the sensitivity of F760yield and Fratio for environmental stress. Our results show an improved predictive capability of GPP when using F760 compared to greenness-based vegetation indices. F760yield and Fratio show a strong variability in time and between different crop types suffering from different levels of water shortage, indicating a strong sensitivity of F products for plant stress reactions. We conclude that the new RS approach of F provides complements to the set of commonly applies RS: The use of F760 improves constraining estimates of GPP while the ratio of red and far-red F shows large potential for tracking spatio-temporal plant adaptation in response to environmental stress conditions.
Identifier(s):DOI: 10.1016/j.rse.2016.07.025
Citation Advice:Wieneke, S., et al., Airborne based spectroscopy of red and far-red sun-induced chlorophyll fluorescence: Implications for improved estimates of gross ..., Remote Sensing of Environment (2016), http://dx.doi.org/10.1016/j.rse.2016.07.025
Responsible Party
Creator(s):Author: Sebastian Wieneke
Author: Hella Ahrends
Author: Alexander Damm
Author: Francisco Pinto
Author: Anja Stadler
Author: Micol Rossini
Author: Uwe Rascher
Publisher:Elsevier Science
Topic
TR32 Topic:Vegetation
Related Sub-project(s):D2, C3
Subject(s):CRC/TR32 Keywords: Fluorescence, GPP
Topic Category:Enviroment
File Details
File Name:Wieneke_et_al_2016.pdf
Data Type:Text
File Size:4126 kB (4.029 MB)
Date(s):Available: 2016-08-01
Mime Type:application/pdf
Data Format:PDF
Language:English
Status:Completed
Constraints
Download Permission:Free
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
North:-no map data
East:-
South:-
West:-
Measurement Region:Ellebach
Measurement Location:Selhausen
Specific Informations - Publication
Status:Published
Review:PeerReview
Year:2016
Type:Article
Article Type:Journal
Source:Remote Sensing of Environment
Volume:184
Number Of Pages:14
Page Range:654 - 667
Metadata Details
Metadata Creator:Sebastian Wieneke
Metadata Created:2016-08-04
Metadata Last Updated:2016-08-04
Subproject:D2
Funding Phase:2
Metadata Language:English
Metadata Version:V41
Dataset Metrics
Page Visits:256
Metadata Downloads:0
Dataset Downloads:3
Dataset Activity
Features