{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,14]],"date-time":"2026-02-14T02:51:51Z","timestamp":1771037511951,"version":"3.50.1"},"reference-count":54,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2021,10,29]],"date-time":"2021-10-29T00:00:00Z","timestamp":1635465600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100010663","name":"European Research Council","doi-asserted-by":"publisher","award":["755617"],"award-info":[{"award-number":["755617"]}],"id":[{"id":"10.13039\/100010663","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The retrieval of sun-induced fluorescence (SIF) from hyperspectral radiance data grew to maturity with research activities around the FLuorescence EXplorer satellite mission FLEX, yet full-spectrum estimation methods such as the spectral fitting method (SFM) are computationally expensive. To bypass this computational load, this work aims to approximate the SFM-based SIF retrieval by means of statistical learning, i.e., emulation. While emulators emerged as fast surrogate models of simulators, the accuracy-speedup trade-offs are still to be analyzed when the emulation concept is applied to experimental data. We evaluated the possibility of approximating the SFM-like SIF output directly based on radiance data while minimizing the loss in precision as opposed to SFM-based SIF. To do so, we implemented a double principal component analysis (PCA) dimensionality reduction, i.e., in both input and output, to achieve emulation of multispectral SIF output based on hyperspectral radiance data. We then evaluated systematically: (1) multiple machine learning regression algorithms, (2) number of principal components, (3) number of training samples, and (4) quality of training samples. The best performing SIF emulator was then applied to a HyPlant flight line containing at sensor radiance information, and the results were compared to the SFM SIF map of the same flight line. The emulated SIF map was quasi-instantaneously generated, and a good agreement against the reference SFM map was obtained with a R2 of 0.88 and NRMSE of 3.77%. The SIF emulator was subsequently applied to 7 HyPlant flight lines to evaluate its robustness and portability, leading to a R2 between 0.68 and 0.95, and a NRMSE between 6.42% and 4.13%. Emulated SIF maps proved to be consistent while processing time was in the order of 3 min. In comparison, the original SFM needed approximately 78 min to complete the SIF processing. Our results suggest that emulation can be used to efficiently reduce computational loads of SIF retrieval methods.<\/jats:p>","DOI":"10.3390\/rs13214368","type":"journal-article","created":{"date-parts":[[2021,11,1]],"date-time":"2021-11-01T22:24:22Z","timestamp":1635805462000},"page":"4368","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Emulation of Sun-Induced Fluorescence from Radiance Data Recorded by the HyPlant Airborne Imaging Spectrometer"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0537-6803","authenticated-orcid":false,"given":"Miguel","family":"Morata","sequence":"first","affiliation":[{"name":"Image Processing Laboratory (IPL), Parc Cient\u00edfic, Universitat de Val\u00e8ncia, 46980 Paterna, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1232-7102","authenticated-orcid":false,"given":"Bastian","family":"Siegmann","sequence":"additional","affiliation":[{"name":"Institute of Bio- and Geosciences, Plant Sciences (IBG-2), Forschungszentrum J\u00fclich GmbH, 52428 J\u00fclich, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0970-9492","authenticated-orcid":false,"given":"Pablo","family":"Morcillo-Pallar\u00e9s","sequence":"additional","affiliation":[{"name":"Image Processing Laboratory (IPL), Parc Cient\u00edfic, Universitat de Val\u00e8ncia, 46980 Paterna, Spain"},{"name":"Institute ITACA, Universitat Polit\u00e8cnica de Val\u00e8ncia, 46022 Valencia, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3188-1448","authenticated-orcid":false,"given":"Juan Pablo","family":"Rivera-Caicedo","sequence":"additional","affiliation":[{"name":"CONACyT-UAN, Secretar\u00eda de Investigaci\u00f3n y Posgrado, Universidad Aut\u00f3noma de Nayarit, Ciudad de la Cultura Amado Nervo, Tepic 63155, Mexico"}]},{"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, 46980 Paterna, Spain"}]}],"member":"1968","published-online":{"date-parts":[[2021,10,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Mohammed, G., Colombo, R., Middleton, E., Rascher, U., van der Tol, C., Nedbal, L., Goulas, Y., P\u00e9rez-Priego, O., Damm, A., and Meroni, M. 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