{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,20]],"date-time":"2026-04-20T21:53:12Z","timestamp":1776721992497,"version":"3.51.2"},"reference-count":67,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2013,7,9]],"date-time":"2013-07-09T00:00:00Z","timestamp":1373328000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>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 \ufb01eld   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   in\ufb02uences the accuracy of the retrievals. Here,   best LCC retrievals were obtained using   a normalized \u201cL1 -estimate\u201d function with   a relative error of 17.6% (r2 : 0.73), while best   LAI retrievals were obtained through non-normalized   \u201cleast-squares estimator\u201d (LSE) with a relative error of 15.3% (r2 : 0.74).<\/jats:p>","DOI":"10.3390\/rs5073280","type":"journal-article","created":{"date-parts":[[2013,7,9]],"date-time":"2013-07-09T11:22:00Z","timestamp":1373368920000},"page":"3280-3304","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":132,"title":["Multiple Cost Functions and Regularization Options for Improved Retrieval of Leaf Chlorophyll Content and LAI through Inversion of the PROSAIL Model"],"prefix":"10.3390","volume":"5","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3188-1448","authenticated-orcid":false,"given":"Juan","family":"Rivera","sequence":"first","affiliation":[{"name":"Image Processing Laboratory (IPL), Parc Cient\u00edfic, Universitat de Val\u00e8ncia, E-46980 Paterna, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6313-2081","authenticated-orcid":false,"given":"Jochem","family":"Verrelst","sequence":"additional","affiliation":[{"name":"Image Processing Laboratory (IPL), Parc Cient\u00edfic, Universitat de Val\u00e8ncia, E-46980 Paterna, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ganna","family":"Leonenko","sequence":"additional","affiliation":[{"name":"Department Psychological Med., Cardiff University, Cardiff CF14 4XN, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jos\u00e9","family":"Moreno","sequence":"additional","affiliation":[{"name":"Image Processing Laboratory (IPL), Parc Cient\u00edfic, Universitat de Val\u00e8ncia, E-46980 Paterna, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2013,7,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Whittaker, R.H., and Marks, P.L. 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