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Exploring the spatial relationship between airborne-derived red and far-red sun-induced fluorescence and process-based GPP estimates in a forest ecosystem.

Authors :
Tagliabue, Giulia
Panigada, Cinzia
Dechant, Benjamin
Baret, Frédéric
Cogliati, Sergio
Colombo, Roberto
Migliavacca, Mirco
Rademske, Patrick
Schickling, Anke
Schüttemeyer, Dirk
Verrelst, Jochem
Rascher, Uwe
Ryu, Youngryel
Rossini, Micol
Source :
Remote Sensing of Environment. Sep2019, Vol. 231, p111272-111272. 1p.
Publication Year :
2019

Abstract

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 HyPlant. 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 (r2 = 0.89 and p < 0.01, r2 = 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−2 and RMSE = 0.51 m2 m−2, 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 (r2 = 0.46, p < 0.001) and APAR (r2 = 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 (p > 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. • High-resolution LCC and LAI maps were obtained from HyPlant through RTM inversion. • High-resolution GPP and APAR maps were obtained driving BESS with HyPlant data. • High-resolution F 687 and F 760 maps were obtained from HyPlant using SFM in a forest. • F 687 showed a non-significant relation with GPP and APAR in the spatial domain. • F 760 showed a positive nonlinear relation with GPP and APAR in the spatial domain. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00344257
Volume :
231
Database :
Academic Search Index
Journal :
Remote Sensing of Environment
Publication Type :
Academic Journal
Accession number :
137775934
Full Text :
https://doi.org/10.1016/j.rse.2019.111272