A simple approach to enhance the TROPOMI solar-induced chlorophyll fluorescence product by combining with canopy reflected radiation at near-infrared band

[EN] Satellite-based data of solar-induced chlorophyll fluorescence (SIF) and the near-infrared radiation reflected by vegetation (NIRvP) are being increasingly used for the estimation of vegetation gross primary product (GPP) at the global scale. Although SIF contains more physiological information...

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Autores: Liu, Xinjie, Liu, Liangyun, Bacour, Cédric, Chen, Jidai, Ma, Yan, Chen, Ruonan, Du, Shanshan, Guanter-Palomar, Luis María|||0000-0002-8389-5764
Tipo de recurso: artículo
Fecha de publicación:2023
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/208614
Acceso en línea:https://riunet.upv.es/handle/10251/208614
Access Level:acceso abierto
Palabra clave:Solar-induced chlorophyll fluorescence (SIF)
Near-infrared radiation reflected by vegetation (NIRvP)
Gross primary productivity (GPP)
Multi-source data combination
FISICA APLICADA
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repository_id_str
spelling A simple approach to enhance the TROPOMI solar-induced chlorophyll fluorescence product by combining with canopy reflected radiation at near-infrared bandLiu, XinjieLiu, LiangyunBacour, CédricChen, JidaiMa, YanChen, RuonanDu, ShanshanGuanter-Palomar, Luis María|||0000-0002-8389-5764Solar-induced chlorophyll fluorescence (SIF)Near-infrared radiation reflected by vegetation (NIRvP)Gross primary productivity (GPP)Multi-source data combinationFISICA APLICADA[EN] Satellite-based data of solar-induced chlorophyll fluorescence (SIF) and the near-infrared radiation reflected by vegetation (NIRvP) are being increasingly used for the estimation of vegetation gross primary product (GPP) at the global scale. Although SIF contains more physiological information than NIRvP, NIRvP can have higher data quality and spatio-temporal resolution. Therefore, the two variables can be considered complementary for GPP monitoring. Here, we propose a simple framework to combine SIF and NIRvP data from different data sources to generate an enhanced SIF product (eSIF). The original SIF data comes from the TROPOMI instrument onboard the Sentinel-5P mission, whereas NIRvP data are derived from MODIS spectral reflectance and ERA5 reanalysis data. The resulting eSIF product has a spatial resolution of 0.05 degrees and a temporal resolution of 8 days, as well as a higher signal-to-noise ratio and a lower angular dependency than the original TROPOMI SIF data. Our results demonstrate that eSIF has similar spatial patterns to the original SIF but is more spatially continuous and less noisy. Comparisons with the FLUXCOM global GPP product show that eSIF has a more universal relationship with GPP than NIRvP for different grass/crop plant functional types (the coefficients of variation are 18.9% for slopes of GPP to eSIF and 27.3% for slopes of GPP to NIRvP), but NIRvP outperforms eSIF for tracking GPP for forest PFTs exclude BoENF. Moreover, eSIF is able to better track the seasonal variations in GPP related to environmental stresses. This study highlights that our methodology based on the combination of SIF and NIRvP is a promising approach for better monitoring of GPP.This research was funded by the Innovative Research Program of the International Research Center of Big Data for Sustainable Development Goals (CBAS2022ORP03) , and the National Natural Science Foundation of China (42071310, 41825002) . We thank Dr. Martin Jung and Ulrich Weber for providing the FLUXCOM GPP products, and we thank Prof. Guijun Yang, Prof. Shaomin Liu, and Dr. Ziwei Xu for providing the in situ GPP datasets.ElsevierDepartamento de Física AplicadaEscuela Técnica Superior de Ingeniería de TelecomunicaciónInstituto Universitario de Ingeniería del Agua y del Medio AmbienteChinese Academy of SciencesNational Natural Science Foundation of ChinaRepositorio Institucional de la Universitat Politècnica de València Riunet20232023-01-01journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfapplication/pdfhttps://riunet.upv.es/handle/10251/208614reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valénciainstname:Universitat Politècnica de València (UPV)InglésengNational Natural Science Foundation of China https://doi.org/10.13039/501100001809 42071310National Natural Science Foundation of China https://doi.org/10.13039/501100001809 41825002Chinese Academy of Sciences https://doi.org/10.13039/501100002367 CBAS2022ORP03open accesshttp://purl.org/coar/access_right/c_abf2Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) http://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:riunet.upv.es:10251/2086142026-06-13T07:49:27Z
dc.title.none.fl_str_mv A simple approach to enhance the TROPOMI solar-induced chlorophyll fluorescence product by combining with canopy reflected radiation at near-infrared band
title A simple approach to enhance the TROPOMI solar-induced chlorophyll fluorescence product by combining with canopy reflected radiation at near-infrared band
spellingShingle A simple approach to enhance the TROPOMI solar-induced chlorophyll fluorescence product by combining with canopy reflected radiation at near-infrared band
Liu, Xinjie
Solar-induced chlorophyll fluorescence (SIF)
Near-infrared radiation reflected by vegetation (NIRvP)
Gross primary productivity (GPP)
Multi-source data combination
FISICA APLICADA
title_short A simple approach to enhance the TROPOMI solar-induced chlorophyll fluorescence product by combining with canopy reflected radiation at near-infrared band
title_full A simple approach to enhance the TROPOMI solar-induced chlorophyll fluorescence product by combining with canopy reflected radiation at near-infrared band
title_fullStr A simple approach to enhance the TROPOMI solar-induced chlorophyll fluorescence product by combining with canopy reflected radiation at near-infrared band
title_full_unstemmed A simple approach to enhance the TROPOMI solar-induced chlorophyll fluorescence product by combining with canopy reflected radiation at near-infrared band
title_sort A simple approach to enhance the TROPOMI solar-induced chlorophyll fluorescence product by combining with canopy reflected radiation at near-infrared band
dc.creator.none.fl_str_mv Liu, Xinjie
Liu, Liangyun
Bacour, Cédric
Chen, Jidai
Ma, Yan
Chen, Ruonan
Du, Shanshan
Guanter-Palomar, Luis María|||0000-0002-8389-5764
author Liu, Xinjie
author_facet Liu, Xinjie
Liu, Liangyun
Bacour, Cédric
Chen, Jidai
Ma, Yan
Chen, Ruonan
Du, Shanshan
Guanter-Palomar, Luis María|||0000-0002-8389-5764
author_role author
author2 Liu, Liangyun
Bacour, Cédric
Chen, Jidai
Ma, Yan
Chen, Ruonan
Du, Shanshan
Guanter-Palomar, Luis María|||0000-0002-8389-5764
author2_role author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Departamento de Física Aplicada
Escuela Técnica Superior de Ingeniería de Telecomunicación
Instituto Universitario de Ingeniería del Agua y del Medio Ambiente
Chinese Academy of Sciences
National Natural Science Foundation of China
Repositorio Institucional de la Universitat Politècnica de València Riunet
dc.subject.none.fl_str_mv Solar-induced chlorophyll fluorescence (SIF)
Near-infrared radiation reflected by vegetation (NIRvP)
Gross primary productivity (GPP)
Multi-source data combination
FISICA APLICADA
topic Solar-induced chlorophyll fluorescence (SIF)
Near-infrared radiation reflected by vegetation (NIRvP)
Gross primary productivity (GPP)
Multi-source data combination
FISICA APLICADA
description [EN] Satellite-based data of solar-induced chlorophyll fluorescence (SIF) and the near-infrared radiation reflected by vegetation (NIRvP) are being increasingly used for the estimation of vegetation gross primary product (GPP) at the global scale. Although SIF contains more physiological information than NIRvP, NIRvP can have higher data quality and spatio-temporal resolution. Therefore, the two variables can be considered complementary for GPP monitoring. Here, we propose a simple framework to combine SIF and NIRvP data from different data sources to generate an enhanced SIF product (eSIF). The original SIF data comes from the TROPOMI instrument onboard the Sentinel-5P mission, whereas NIRvP data are derived from MODIS spectral reflectance and ERA5 reanalysis data. The resulting eSIF product has a spatial resolution of 0.05 degrees and a temporal resolution of 8 days, as well as a higher signal-to-noise ratio and a lower angular dependency than the original TROPOMI SIF data. Our results demonstrate that eSIF has similar spatial patterns to the original SIF but is more spatially continuous and less noisy. Comparisons with the FLUXCOM global GPP product show that eSIF has a more universal relationship with GPP than NIRvP for different grass/crop plant functional types (the coefficients of variation are 18.9% for slopes of GPP to eSIF and 27.3% for slopes of GPP to NIRvP), but NIRvP outperforms eSIF for tracking GPP for forest PFTs exclude BoENF. Moreover, eSIF is able to better track the seasonal variations in GPP related to environmental stresses. This study highlights that our methodology based on the combination of SIF and NIRvP is a promising approach for better monitoring of GPP.
publishDate 2023
dc.date.none.fl_str_mv 2023
2023-01-01
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://riunet.upv.es/handle/10251/208614
url https://riunet.upv.es/handle/10251/208614
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv National Natural Science Foundation of China https://doi.org/10.13039/501100001809 42071310
National Natural Science Foundation of China https://doi.org/10.13039/501100001809 41825002
Chinese Academy of Sciences https://doi.org/10.13039/501100002367 CBAS2022ORP03
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reconocimiento - No comercial - Sin obra derivada (by-nc-nd)
http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reconocimiento - No comercial - Sin obra derivada (by-nc-nd)
http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
instname:Universitat Politècnica de València (UPV)
instname_str Universitat Politècnica de València (UPV)
reponame_str RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
collection RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,811543

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