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SAR Oil Spill Detection System through Random Forest Classifiers

A set of open-source routines capable of identifying possible oil-like spills based on two random forest classifiers were developed and tested with a Sentinel-1 SAR image dataset. The first random forest model is an ocean SAR image classifier where the labeling inputs were oil spills, biological fil...

Deskribapen osoa

Gorde:
Egile Nagusiak: Marcos Reinan Assis Conceição, Luis Felipe Ferreira de Mendonça, Carlos Alessandre Domingos Lentini, André Telles da Cunha Lima, José Marques Lopes, Rodrigo Nogueira de Vasconcelos, Mainara Biazati Gouveia, Milton José Porsani
Formatua: Artigo
Hizkuntza:Inglês
Argitaratua: MDPI AG 2021-05-01
Saila:Remote Sensing
Gaiak:
oil spills
image segmentation
random forest
synthetic aperture radar
feature selection
Sarrera elektronikoa:https://www.mdpi.com/2072-4292/13/11/2044
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