During the last decade, a growing interest has arisen in the Solar Induced Fluorescence (SIF) emitted by terrestrial plants, with particular reference to the development of new methods for its retrieval from satellite data. This could pave the way to the monitoring of vegetation SIF at a global scale and its exploitation as a key parameter of dynamical global vegetation models used for carbon cycle studies. Besides, SIF retrieval from satellite could greatly contribute to the monitoring of the health status of vegetation with relation to several environmental stress factors. In this PhD thesis, a new method for the retrieval of the SIF of vegetation is proposed. The method is based on a statistical approach and it was developed in order to overcome some limits that typically affect the methods proposed up to now and that can affect the accuracy of the retrieved SIF. Specifically, this method provides as output both the SIF spectrum and the in-band averaged or integrated SIF intensity from the top of atmosphere radiance spectra measured by means of a passive remote sensing technique. In detail, in this PhD thesis the fundamentals of the proposed method have been discussed from a mathematical point of view and the implementation has been accurately described. Besides, performance assessment and robustness analysis of the ML-SIF method have been also carried out. The lack of both spectra of reflectance and SIF at canopy level for several vegetation species and the related SIF radiance spectra prevented the direct implementation of the learning procedure with actual measurements. As a consequence, this study relied on the use of a tool Soil Canopy Observation, Photochemistry and Energy Balance (SCOPE) and an in-house developed radiance image simulator. The latter has been specifically implemented during this work to simulate realistic radiance spectra containing SIF contributions.

DI NINNI, P. (2017). A statistical method for the retrieval of the Solar Induced Fluorescence of vegetation by means of radiance spectra from space: fundamentals, performance and robustness analysis.

A statistical method for the retrieval of the Solar Induced Fluorescence of vegetation by means of radiance spectra from space: fundamentals, performance and robustness analysis

DI NINNI, PAOLA
2017-01-01

Abstract

During the last decade, a growing interest has arisen in the Solar Induced Fluorescence (SIF) emitted by terrestrial plants, with particular reference to the development of new methods for its retrieval from satellite data. This could pave the way to the monitoring of vegetation SIF at a global scale and its exploitation as a key parameter of dynamical global vegetation models used for carbon cycle studies. Besides, SIF retrieval from satellite could greatly contribute to the monitoring of the health status of vegetation with relation to several environmental stress factors. In this PhD thesis, a new method for the retrieval of the SIF of vegetation is proposed. The method is based on a statistical approach and it was developed in order to overcome some limits that typically affect the methods proposed up to now and that can affect the accuracy of the retrieved SIF. Specifically, this method provides as output both the SIF spectrum and the in-band averaged or integrated SIF intensity from the top of atmosphere radiance spectra measured by means of a passive remote sensing technique. In detail, in this PhD thesis the fundamentals of the proposed method have been discussed from a mathematical point of view and the implementation has been accurately described. Besides, performance assessment and robustness analysis of the ML-SIF method have been also carried out. The lack of both spectra of reflectance and SIF at canopy level for several vegetation species and the related SIF radiance spectra prevented the direct implementation of the learning procedure with actual measurements. As a consequence, this study relied on the use of a tool Soil Canopy Observation, Photochemistry and Energy Balance (SCOPE) and an in-house developed radiance image simulator. The latter has been specifically implemented during this work to simulate realistic radiance spectra containing SIF contributions.
2017
DI NINNI, P. (2017). A statistical method for the retrieval of the Solar Induced Fluorescence of vegetation by means of radiance spectra from space: fundamentals, performance and robustness analysis.
DI NINNI, Paola
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11365/1013500