An approach to fill in missing data from satellite imagery using data-intensive computing and DINEOF

This paper proposes an approach to fill in missing data from satellite images using data-intensive computing platforms. The proposed approach merges satellite imagery from diverse sources to reduce the impact of the holes in images that result from acquisition conditions: occlusion, the satellite tr...

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Detalles Bibliográficos
Autores principales: Lomelí-Huerta, José Roberto, Rivera-Caicedo, Juan Pablo, De-la-Torre, Miguel, Acevedo-Juárez, Brenda, Cepeda-Morales, Jushiro, Avila-George, Himer
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2022
Materias:
Spatial and Geographic Information Systems
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9138164/
https://www.ncbi.nlm.nih.gov/pubmed/35634099
http://dx.doi.org/10.7717/peerj-cs.979

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9138164/
https://www.ncbi.nlm.nih.gov/pubmed/35634099
http://dx.doi.org/10.7717/peerj-cs.979

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