Multiple cost functions and regularization options for improved retrieval of leaf chlorophyll content and LAI through inversion of the PROSAIL model

Rivera, Juan Pablo, Verrelst, Jochem, Leonenko, Ganna M. ORCID: https://orcid.org/0000-0001-8025-661X and Moreno, José 2013. Multiple cost functions and regularization options for improved retrieval of leaf chlorophyll content and LAI through inversion of the PROSAIL model. Remote Sensing 5 (7) , pp. 3280-3304. 10.3390/rs5073280

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Abstract

Lookup-table (LUT)-based radiative transfer model inversion is considered a physically-sound and robust method to retrieve biophysical parameters from Earth observation data but regularization strategies are needed to mitigate the drawback of ill-posedness. We systematically evaluated various regularization options to improve leaf chlorophyll content (LCC) and leaf area index (LAI) retrievals over agricultural lands, including the role of (1) cost functions (CFs); (2) added noise; and (3) multiple solutions in LUT-based inversion. Three families of CFs were compared: information measures, M-estimates and minimum contrast methods. We have only selected CFs without additional parameters to be tuned, and thus they can be immediately implemented in processing chains. The coupled leaf/canopy model PROSAIL was inverted against simulated Sentinel-2 imagery at 20 m spatial resolution (8 bands) and validated against field data from the ESA-led SPARC (Barrax, Spain) campaign. For all 18 considered CFs with noise introduction and opting for the mean of multiple best solutions considerably improved retrievals; relative errors can be twice reduced as opposed to those without these regularization options. M-estimates were found most successful, but also data normalization influences the accuracy of the retrievals. Here, best LCC retrievals were obtained using a normalized “L1 -estimate” function with a relative error of 17.6% (r2 : 0.73), while best LAI retrievals were obtained through non-normalized “least-squares estimator” (LSE) with a relative error of 15.3% (r2 : 0.74).

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Mathematics Medicine MRC Centre for Neuropsychiatric Genetics and Genomics (CNGG)
Subjects:	Q Science > QA Mathematics
Uncontrolled Keywords:	Biophysical parameters; LUT-based inversion; cost functions; radiative transfer models; PROSAIL; Sentinel-2.
Publisher:	MDPI
ISSN:	2072-4292
Date of First Compliant Deposit:	18 April 2017
Date of Acceptance:	26 June 2013
Last Modified:	23 May 2023 22:45
URI:	https://orca.cardiff.ac.uk/id/eprint/64172

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