Who’s better at spotting? A comparison between aerial photography and observer-based methods to monitor floating marine litter and marine mega-fauna

Last modified: 
December 13, 2019 - 11:50am
Type: Journal Article
Year of publication: In Press
Authors: Odei Garcia-Garin, Alex Aguilar, Asuncion Borrell, Patricia Gozalbes, Agustín Lobo, Jaime Penadés-Suay, Juan Raga, Ohiana Revuelta, Maria Serrano, Morgana Vighi
Journal title: Environmental Pollution
Pages: 113680
ISSN: 02697491

Pollution by marine litter is raising major concerns due to its potential impact on marine biodiversity and, above all, on endangered mega-fauna species, such as cetaceans and sea turtles. The density and distribution of marine litter and mega-fauna have been traditionally monitored through observer-based methods, yet the advent of new technologies has introduced aerial photography as an alternative monitoring method. However, to integrate results produced by different monitoring techniques and consider the photographic method a viable alternative, this ‘new’ methodology must be validated. This study aims to compare observations obtained from the concurrent application of observer-based and photographic methods during aerial surveys. To do so, a Partenavia P-68 aircraft equipped with an RGB sensor was used to monitor the waters off the Spanish Mediterranean coast along 12 transects (941 km). Over 10000 images were collected and checked manually by a photo-interpreter to detect potential targets, which were classified as floating marine macro-litter, mega-fauna and seabirds. The two methods allowed the detection of items from the three categories and proved equally effective for the detection of cetaceans, sea turtles and large fish on the sea surface. However, the photographic method was more effective for floating litter detection and the observer-based method was more effective for seabird detection. These results provide the first validation of the use of aerial photography to monitor floating litter and mega-fauna over the marine surface.

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