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Open AccessArticle

Hyplant-Derived Sun-Induced Fluorescence—A New Opportunity to Disentangle Complex Vegetation Signals from Diverse Vegetation Types

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Department of Meteorology, Poznań University of Life Sciences, 60649 Poznan, Poland
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Institute of Biogeosciences, IBG2, Forschungszentrum Juelich GmbH, 52425 Juelich, Germany
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Department of Earth and Environmental Sciences, University of Milano-Bicocca, 20126 Milano, Italy
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School of Geosciences, University of Edinburgh, Edinburgh EH9 3FF, UK
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Department of Geography, University of Zurich, Winterthurerstrasse 190, 8057 Zurich, Switzerland
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Faculty of Science and Technology, Free University of Bolzano, 39100 Bozen-Bolzano, Italy
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JB Hyperspectral Devices, Am Botanischen Garten 33, 40225 Düsseldorf, Germany
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Institute of Ecology, University of Innsbruck, Sternwartestrasse 15, 6020 Innsbruck, Austria
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Department of Hydrobiology, Faculty of Biology, Adam Mickiewicz University, 61614 Poznan, Poland
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Department of Land Improvement, Env. Development and Geodesy, Poznań University of Life Sciences, 60649 Poznan, Poland
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Center for Remote Sensing and Earth Observation Processes (VITO-TAP), BE-2400 Mol, Belgium
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Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, P.O. Box 217, AE Enschede 7500, The Netherlands
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Eawag, Swiss Federal Institute of Aquatic Science and Technology, Überlandstrasse 133, 8600 Dübendorf, Switzerland
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European Space Agency, ESTEC; 2201 AZ Noordwijk, The Netherlands
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(14), 1691; https://doi.org/10.3390/rs11141691
Received: 5 June 2019 / Revised: 9 July 2019 / Accepted: 15 July 2019 / Published: 17 July 2019
Hyperspectral remote sensing (RS) provides unique possibilities to monitor peatland vegetation traits and their temporal dynamics at a fine spatial scale. Peatlands provide a vital contribution to ecosystem services by their massive carbon storage and wide heterogeneity. However, monitoring, understanding, and disentangling the diverse vegetation traits from a heterogeneous landscape using complex RS signal is challenging, due to its wide biodiversity and distinctive plant species composition. In this work, we aim to demonstrate, for the first time, the large heterogeneity of peatland vegetation traits using well-established vegetation indices (VIs) and Sun-Induced Fluorescence (SIF) for describing the spatial heterogeneity of the signals which may correspond to spatial diversity of biochemical and structural traits. SIF originates from the initial reactions in photosystems and is emitted at wavelengths between 650–780 nm, with the first peak at around 687 nm and the second peak around 760 nm. We used the first HyPlant airborne data set recorded over a heterogeneous peatland area and its surrounding ecosystems (i.e., forest, grassland) in Poland. We deployed a comparative analysis of SIF and VIs obtained from differently managed and natural vegetation ecosystems, as well as from diverse small-scale peatland plant communities. Furthermore, spatial relationships between SIF and VIs from large-scale vegetation ecosystems to small-scale peatland plant communities were examined. Apart from signal variations, we observed a positive correlation between SIF and greenness-sensitive VIs, whereas a negative correlation between SIF and a VI sensitive to photosynthesis was observed for large-scale vegetation ecosystems. In general, higher values of SIF were associated with higher biomass of vascular plants (associated with higher Leaf Area Index (LAI)). SIF signals, especially SIF760, were strongly associated with the functional diversity of the peatland vegetation. At the peatland area, higher values of SIF760 were associated with plant communities of high perennials, whereas, lower values of SIF760 indicated peatland patches dominated by Sphagnum. In general, SIF760 reflected the productivity gradient on the fen peatland, from Sphagnum-dominated patches with the lowest SIF and fAPAR values indicating lowest productivity to the Carex-dominated patches with the highest SIF and fAPAR values indicating highest productivity. View Full-Text
Keywords: HyPlant; Sun-Induced Fluorescence (SIF); peatland; spectral vegetation indices; NDVI; SR; EVI; PRI; fAPAR; LAI; spectral fitting method; airborne campaign HyPlant; Sun-Induced Fluorescence (SIF); peatland; spectral vegetation indices; NDVI; SR; EVI; PRI; fAPAR; LAI; spectral fitting method; airborne campaign
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Bandopadhyay, S.; Rastogi, A.; Rascher, U.; Rademske, P.; Schickling, A.; Cogliati, S.; Julitta, T.; Mac Arthur, A.; Hueni, A.; Tomelleri, E.; Celesti, M.; Burkart, A.; Stróżecki, M.; Sakowska, K.; Gąbka, M.; Rosadziński, S.; Sojka, M.; Iordache, M.-D.; Reusen, I.; Van Der Tol, C.; Damm, A.; Schuettemeyer, D.; Juszczak, R. Hyplant-Derived Sun-Induced Fluorescence—A New Opportunity to Disentangle Complex Vegetation Signals from Diverse Vegetation Types. Remote Sens. 2019, 11, 1691.

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