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| Hauptseite > Publikationsdatenbank > Airborne based spectroscopy of red and far-red sun-induced chlorophyll fluorescence: Implications for improved estimates of gross primary productivity |
| Hauptseite > Publikationsdatenbank > Airborne based spectroscopy of red and far-red sun-induced chlorophyll fluorescence: Implications for improved estimates of gross primary productivity |
| Journal Article | FZJ-2016-05130 |
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2016
Elsevier Science
Amsterdam [u.a.]
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Please use a persistent id in citations: http://hdl.handle.net/2128/12474 doi:10.1016/j.rse.2016.07.025
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.
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