Can Vegetation Indices Serve as Proxies for Potential Sun-Induced Fluorescence (SIF)? A Fuzzy Simulation Approach on Airborne Imaging Spectroscopy Data

• Main Authors: Subhajit Bandopadhyay, Anshu Rastogi, Sergio Cogliati, Uwe Rascher, Maciej Gąbka, Radosław Juszczak
• Format: Article
• Language: English
• Published: MDPI AG 2021-06-01
• Series: Remote Sensing
• Subjects: sun-induced fluorescence; SIF_fuzzy; SIF_fuzzy-APAR; spectral vegetation indices; HyPlant; fuzzy logic modelling
• Online Access: https://www.mdpi.com/2072-4292/13/13/2545

In this study, we are testing a proxy for red and far-red Sun-induced fluorescence (SIF) using an integrated fuzzy logic modelling approach, termed as SIF_fuzzy and SIF_fuzzy-APAR. The SIF emitted from the core of the photosynthesis and observed at the top-of-canopy is regulated by three major controlling factors: (1) light interception and absorption by canopy plant cover; (2) escape fraction of SIF photons (fesc); (3) light use efficiency and non-photochemical quenching (NPQ) processes. In our study, we proposed and validated a fuzzy logic modelling approach that uses different combinations of spectral vegetation indices (SVIs) reflecting such controlling factors to approximate the potential SIF signals at 760 nm and 687 nm. The <i>HyPlant</i> derived and field validated SVIs (i.e., SR, NDVI, EVI, NDVIre, PRI) have been processed through the membership transformation in the first stage, and in the next stage the membership transformed maps have been processed through the Fuzzy Gamma simulation to calculate the SIF_fuzzy. To test whether the inclusion of absorbed photosynthetic active radiation (APAR) increases the accuracy of the model, the SIF_fuzzy was multiplied by APAR (SIF_fuzzy-APAR). The agreement between the modelled SIF_fuzzy and actual SIF airborne retrievals expressed by R² ranged from 0.38 to 0.69 for SIF₇₆₀ and from 0.85 to 0.92 for SIF₆₈₇. The inclusion of APAR improved the R² value between SIF_fuzzy-APAR and actual SIF. This study showed, for the first time, that a diverse set of SVIs considered as proxies of different vegetation traits, such as biochemical, structural, and functional, can be successfully combined to work as a first-order proxy of SIF. The previous studies mainly included the far-red SIF whereas, in this study, we have also focused on red SIF along with far-red SIF. The analysis carried out at 1 m spatial resolution permits to better infer SIF behaviour at an ecosystem-relevant scale.