Sargassum transport prediction through the Dominican Republic using artificial intelligence

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dc.creatorSánchez-Camilo, Edwin
dc.creatorJiménez-Durán, Iván
dc.creatorLorenzo, Janna
dc.creatorSanlley, Carlos
dc.date.accessioned2024-04-08T14:30:04Z
dc.date.available2024-04-08T14:30:04Z
dc.date.issued2023
dc.description.abstractThe abnormal influxes of sargassum in the Caribbean have shown to be growing in coverage area and mass since 2011. Several efforts have been made for the detection, monitoring, tracking and prediction of the arrival of sargassum to the marine region and coasts in the Greater and Lesser Antilles. Within the regional studies, monitoring and prediction tests have been carried out in the Lesser Antilles, Jamaica, Puerto Rico, and the Mexican Caribbean. However, studies carried out in the Dominican Republic are unknown in the literature. The ideal parameters to detect sargassum using satellite images have already been established. However, there is uncertainty in the prediction, especially in real time, due to the dynamic cloud coverage and low temporal resolution of the satellite systems used and due to the properties of the natural markers (current, sea wind, marine geography, among others) that affect the predictions. The high volume of data from these variables open the doors to investigate which automated methodologies can best serve for effective analysis. This ongoing work proposes the evaluation of the historical pattern of sargassum on the Dominican marine region using a random forest algorithm that will serve to predict the path of future clusters of sargassum, thus creating an early warning system for the country.
dc.formatapplication/pdf
dc.format.extent1 página
dc.identifier.urihttps://repositoriobiblioteca.intec.edu.do/handle/123456789/6887
dc.language.isoInglés
dc.publisherSanto Domingo : Instituto Tecnológico de Santo Domingo
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United Statesen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/
dc.titleSargassum transport prediction through the Dominican Republic using artificial intelligence
dc.typeImagen
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