Solar-induced chlorophyll fluorescence (SIF) is a weak optical signal emitted by chlorophyll under natural illumination. SIF ranges from 600 nm to 800 nm and is assumed as a direct proxy for actual photosynthesis. Due to recent advances in spectroscopy and retrieval techniques, SIF can be retrieved from hyperspectral remote sensing data. Statistical-based approach, typically the singular value decomposition (SVD) method, is one of the two practical strategies for SIF retrieval. A statistical-based approach collects SIF-free measurements of Fraunhofer Lines as training dataset, extracts their spectral features by a statistical approach and then applies the extracted features in the forward SIF retrieval model. In this paper, we first evaluated the performance of the SVD approach in SIF retrieval at proximal scale. Good consistency was found between diurnal SIF cycles given by the SVD method and a 3-FLD method, with SVD-based SIF values higher than those given by 3-FLD. We then applied the SVD method on HyPlant imaging spectroscopy airborne data. Spatial distribution of SIF was successfully depicted using the SVD method. SIF was in a good spatial accordance with NDVI, but the former exhibited a stronger heterogeneity. For both proximal and airborne scales, the in-filling of the Fraunhofer Lines by SIF was successfully detected by the SVD method. However, whether SVD could induce a systematic error should be further studied. It can be concluded that a statistical-based SIF retrieval method is a reasonable alternative to traditional O2-lines-based methods, especially when synchronous SIF-free spectrum or pixelwise atmospheric correction is unavailable.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.