Mapping dissolved organic carbon and organic iron by comparing deep learning and linear regression techniques using sentinel-2 and worldview-2 imagery (byers Peninsula, maritime Antarctica)

Fernández Menéndez, Susana del Carmen; Muñiz Sánchez, Rubén; Peón García, Juan José; Rodríguez Cielos, R.; Ruiz Fernández, Jesús; Fernández Calleja, Javier Jesús

doi:10.3390/rs16071192

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Mapping dissolved organic carbon and organic iron by comparing deep learning and linear regression techniques using sentinel-2 and worldview-2 imagery (byers Peninsula, maritime Antarctica)

dc.contributor.author	Fernández Menéndez, Susana del Carmen
dc.contributor.author	Muñiz Sánchez, Rubén
dc.contributor.author	Peón García, Juan José
dc.contributor.author	Rodríguez Cielos, R.
dc.contributor.author	Ruiz Fernández, Jesús
dc.contributor.author	Fernández Calleja, Javier Jesús
dc.date.accessioned	2024-10-22T06:07:47Z
dc.date.available	2024-10-22T06:07:47Z
dc.date.issued	2024
dc.identifier.citation	Remote Sensing, 16(7), (2024); doi:10.3390/rs16071192
dc.identifier.issn	2072-4292
dc.identifier.uri	https://hdl.handle.net/10651/75254
dc.description.sponsorship	This research and the APC were funded by Ministerio de Ciencia e Innovación: PID2021-127060OB-I00, PID2020-113051RB-C31, PID2020-115269GB-I00, and PTDC/CTE-GIX/119582/2010.
dc.language.iso	eng
dc.relation.ispartof	Remote Sensing
dc.rights	© 2024 by the authors
dc.rights	CC Reconocimiento 4.0 Internacional
dc.rights.uri	http://creativecommons.org/licenses/by/4.0/
dc.source	Scopus
dc.source.uri	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85190304345&doi=10.3390%2frs16071192&partnerID=40&md5=cdc74f5956cc6c7d5cfe2732dc62aec6
dc.title	Mapping dissolved organic carbon and organic iron by comparing deep learning and linear regression techniques using sentinel-2 and worldview-2 imagery (byers Peninsula, maritime Antarctica)
dc.type	journal article
dc.identifier.doi	10.3390/rs16071192
dc.relation.projectID	PID2021-127060OB-I00
dc.relation.projectID	PID2020-113051RB-C31
dc.relation.projectID	PID2020-115269GB-I00
dc.relation.projectID	PTDC/CTE-GIX/119582/2010
dc.relation.publisherversion	http://dx.doi.org/10.3390/rs16071192
dc.rights.accessRights	open access
dc.type.hasVersion	VoR

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