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RISS 인기검색어
- 검색키워드
- 저자 : Cogliati, Sergio (검색결과 1 건)
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Tagliabue, Giulia,Panigada, Cinzia,Dechant, Benjamin,Baret, Fré,dé,ric,Cogliati, Sergio,Colombo, Roberto,Migliavacca, Mirco,Rademske, Patrick,Schickling, Anke,Schü,ttemeyer, Dirk,Verre Elsevier 2019 Remote sensing of environment Vol.231 No.-
<P><B>Abstract</B></P> <P>Terrestrial gross primary productivity (GPP) plays an essential role in the global carbon cycle, but the quantification of the spatial and temporal variations in photosynthesis is still largely uncertain. Our work aimed to investigate the potential of remote sensing to provide new insights into plant photosynthesis at a fine spatial resolution. This goal was achieved by exploiting high-resolution images acquired with the FLuorescence EXplorer (FLEX) airborne demonstrator <I>HyPlant</I>. The sensor was flown over a mixed forest, and the images collected were elaborated to obtain two independent indicators of plant photosynthesis. First, maps of sun-induced chlorophyll fluorescence (F), a novel indicator of plant photosynthetic activity, were successfully obtained at both the red and far-red peaks (r<SUP>2</SUP> = 0.89 and <I>p</I> < 0.01, r<SUP>2</SUP> = 0.77 and p < 0.01, respectively, compared to top-of-canopy ground-based measurements acquired synchronously with the overflight) over the forested study area. Second, maps of GPP and absorbed photosynthetically active radiation (APAR) were derived using a customised version of the coupled biophysical model Breathing Earth System Simulator (BESS). The model was driven with airborne-derived maps of key forest traits (i.e., leaf chlorophyll content (LCC) and leaf area index (LAI)) and meteorological data providing a high-resolution snapshot of the variables of interest across the study site. The LCC and LAI were accurately estimated (RMSE = 5.66 μg cm<SUP>−2</SUP> and RMSE = 0.51 m<SUP>2</SUP> m<SUP>−2</SUP>, respectively) through an optimised Look-Up-Table-based inversion of the PROSPECT-4-INFORM radiative transfer model, ensuring the accurate representation of the spatial variation of these determinants of the ecosystem's functionality. The spatial relationships between the measured F and modelled BESS outputs were then analysed to interpret the variability of ecosystem functioning at a regional scale. The results showed that far-red F is significantly correlated with the GPP (r<SUP>2</SUP> = 0.46, <I>p</I> < 0.001) and APAR (r<SUP>2</SUP> = 0.43, p < 0.001) in the spatial domain and that this relationship is nonlinear. Conversely, no statistically significant relationships were found between the red F and the GPP or APAR (<I>p</I> > 0.05). The spatial relationships found at high resolution provide valuable insight into the critical role of spatial heterogeneity in controlling the relationship between the far-red F and the GPP, indicating the need to consider this heterogeneity at a coarser resolution.</P> <P><B>Highlights</B></P> <P> <UL> <LI> High-resolution LCC and LAI maps were obtained from <I>HyPlant</I> through RTM inversion. </LI> <LI> High-resolution GPP and APAR maps were obtained driving BESS with <I>HyPlant</I> data. </LI> <LI> High-resolution F<SUB>687</SUB> and F<SUB>760</SUB> maps were obtained from <I>HyPlant</I> using SFM in a forest. </LI> <LI> F<SUB>687</SUB> showed a non-significant relation with GPP and APAR in the spatial domain. </LI> <LI> F<SUB>760</SUB> showed a positive nonlinear relation with GPP and APAR in the spatial domain. </LI> </UL> </P>
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