Quantifying Marine Macro Litter Abundance on a Sandy Beach Using Unmanned Aerial Systems and Object-Oriented Machine Learning Methods

Quantifying Marine Macro Litter Abundance on a Sandy Beach Using Unmanned Aerial Systems and Object-Oriented Machine Learning Methods

Unmanned aerial systems (UASs) have recently been proven to be valuable remote sensing tools for detecting marine macro litter (MML), with the potential of supporting pollution monitoring programs on coasts. Very low altitude images, acquired with a low-cost RGB camera onboard a UAS on a sandy beach...

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Bibliographic Details
Main Authors: Gil Gonçalves, Umberto Andriolo, Luísa Gonçalves, Paula Sobral, Filipa Bessa
Format: Article
Language:English
Published: MDPI AG 2020-08-01
Series:Remote Sensing
Subjects:
drone
anthropogenic debris
OBIA
random forest
support vector machine
k-nearest neighbor
Online Access:https://www.mdpi.com/2072-4292/12/16/2599

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