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

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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Bibliographic Details
Main Authors: José Roberto Lomelí-Huerta, Juan Pablo Rivera-Caicedo, Miguel De-la-Torre, Brenda Acevedo-Juárez, Jushiro Cepeda-Morales, Himer Avila-George
Format: Article
Language:English
Published: PeerJ Inc. 2022-05-01
Series:PeerJ Computer Science
Subjects:
Satellite imagery
Missing data
DINEOF
MODIS
VIIRS
Online Access:https://peerj.com/articles/cs-979.pdf

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