19 September 2016 Application of vegetation isoline equations for simultaneous retrieval of leaf area index and leaf chlorophyll content using reflectance of red edge band
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Abstract
The remotely sensed reflectance spectra of vegetated surfaces contain information relating to the leaf area index (LAI) and the chlorophyll-a and -b concentrations (Cab) in a leaf. Difficulties associated with the retrieval of these two biophysical parameters from a single reflectance spectrum arise mainly from the choice of a suitable set of observation wavelengths and the development of a retrieval algorithm. Efforts have been applied toward the development of new algorithms, such as the numerical inversion of radiative transfer models, in addition to the development of simple approaches based on the spectral vegetation indices. This study explored a different approach: An equation describing band-to-band relationships (vegetation isoline equation) was used to retrieve the LAI and Cab simultaneously from a reflectance spectrum. The algorithm used three bands, including the red edge region, and an optimization cost function was constructed from two vegetation isoline equations in the red-NIR and red edge-NIR reflectance subspaces. A series of numerical experiments was conducted using the PROSPECT model to explore the numerical challenges associated with the use of the vegetation isoline equation during the parameter retrieval of the LAI and Cab. Overall, our results indicated the existence of a global minimum (and no local minima) over a wide swath of the LAI-Cab parameter subspace in most simulation cases. These results suggested that the use of the vegetation isoline equation in the simultaneous retrieval of the LAI and the Cab provides a viable alternative to the spectral vegetation index algorithms and the direct inversion of the canopy radiative transfer models.
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Kakuya Okuda, Kenta Taniguchi, Munenori Miura, Kenta Obata, Hiroki Yoshioka, "Application of vegetation isoline equations for simultaneous retrieval of leaf area index and leaf chlorophyll content using reflectance of red edge band", Proc. SPIE 9975, Remote Sensing and Modeling of Ecosystems for Sustainability XIII, 99750C (19 September 2016); doi: 10.1117/12.2236811; https://doi.org/10.1117/12.2236811
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