Integrating Solar Induced Fluorescence and the Photochemical Reflectance Index for Estimating Gross Primary Production in a Cornfield

dc.contributor.authorCheng, Yen-Ben
dc.contributor.authorMiddleton, Elizabeth M.
dc.contributor.authorZhang, Qingyuan
dc.contributor.authorHuemmrich, Karl
dc.contributor.authorCampbell, Petya Entcheva
dc.contributor.authorCorp, Lawrence A.
dc.contributor.authorCook, Bruce D.
dc.contributor.authorKustas, William P.
dc.contributor.authorDaughtry, Craig S.
dc.date.accessioned2023-07-11T17:31:13Z
dc.date.available2023-07-11T17:31:13Z
dc.date.issued2013-12-09
dc.description.abstractThe utilization of remotely sensed observations for light use efficiency (LUE) and tower-based gross primary production (GPP) estimates was studied in a USDA cornfield. Nadir hyperspectral reflectance measurements were acquired at canopy level during a collaborative field campaign conducted in four growing seasons. The Photochemical Reflectance Index (PRI) and solar induced chlorophyll fluorescence (SIF), were derived. SIF retrievals were accomplished in the two telluric atmospheric oxygen absorption features centered at 688 nm (O₂-B) and 760 nm (O₂-A). The PRI and SIF were examined in conjunction with GPP and LUE determined by flux tower-based measurements. All of these fluxes, environmental variables, and the PRI and SIF exhibited diurnal as well as day-to-day dynamics across the four growing seasons. Consistent with previous studies, the PRI was shown to be related to LUE (r² = 0.54 with a logarithm fit), but the relationship varied each year. By combining the PRI and SIF in a linear regression model, stronger performances for GPP estimation were obtained. The strongest relationship (r² = 0.80, RMSE = 0.186 mg CO₂/m²/s) was achieved when using the PRI and SIF retrievals at 688 nm. Cross-validation approaches were utilized to demonstrate the robustness and consistency of the performance. This study highlights a GPP retrieval method based entirely on hyperspectral remote sensing observations.en
dc.description.sponsorshipThis study was supported by a NASA ROSES project (PI, E.M. Middleton) funded through the Terrestrial Ecology Program (Diane Wickland, Program Manager). The authors gratefully acknowledge Andrew Russ and Wayne Dulaney (USDA-ARS Hydrology and Remote Sensing Lab) for assisting field campaign and data processing. The authors thank the anonymous reviewers for their very valuable suggestions and critiques.en
dc.description.urihttps://www.mdpi.com/2072-4292/5/12/6857en
dc.format.extent23 pagesen
dc.genrejournal articlesen
dc.identifierdoi:10.13016/m2wbj3-asei
dc.identifier.citationCheng, Yen-Ben, Elizabeth M. Middleton, Qingyuan Zhang, Karl F. Huemmrich, Petya K. E. Campbell, Lawrence A. Corp, Bruce D. Cook, William P. Kustas, and Craig S. Daughtry. 2013. "Integrating Solar Induced Fluorescence and the Photochemical Reflectance Index for Estimating Gross Primary Production in a Cornfield" Remote Sensing 5, no. 12: 6857-6879. https://doi.org/10.3390/rs5126857en
dc.identifier.urihttps://doi.org/10.3390/rs5126857
dc.identifier.urihttp://hdl.handle.net/11603/28582
dc.language.isoenen
dc.publisherMDPIen
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Joint Center for Earth Systems Technology
dc.relation.ispartofUMBC Faculty Collection
dc.relation.ispartofUMBC Geography and Environmental Systems Department
dc.relation.ispartofUMBC GESTAR II
dc.rightsPublic Domain Mark 1.0*
dc.rightsThis work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.en
dc.rights.urihttp://creativecommons.org/publicdomain/mark/1.0/*
dc.titleIntegrating Solar Induced Fluorescence and the Photochemical Reflectance Index for Estimating Gross Primary Production in a Cornfielden
dc.typeTexten
dcterms.creatorhttps://orcid.org/0000-0003-4148-9108en
dcterms.creatorhttps://orcid.org/0000-0002-0505-4951en

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