ABD: A machine intelligent-based algal bloom detector for remote sensing images[Formula presented]
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Data
2023-03-01
Autores
Ananias, Pedro Henrique M. [UNESP]
Negri, Rogério G. [UNESP]
Bressane, Adriano [UNESP]
Colnago, Marilaine [UNESP]
Casaca, Wallace [UNESP]
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Resumo
This paper presents a new approach for detecting algal insurgence in water environments by using remote sensing image series. The designed methodology provides a robust and accurate algorithm as an alternative to typical algal bloom detection methods. In more technical terms, by only assuming as input an image time series, a fully automatic data-driven scheme involving pre-processing and feature extraction procedures is derived, which models a machine intelligent-based classifier capable of detecting algal blooms. Lastly, algal insurgence maps are then produced by passing to the classifier an image taken at an instant of interest.
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Algal bloom, Machine learning, Remote sensing, Spectral index
Como citar
Software Impacts, v. 15.