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OBIA classification using, among others, machine learning algorithms can correctly extract the
main features from data of orthomosaics, point clouds and various types of inputs. Considering
that images can have GSD values between 0.3 cm/pixel and 2.2 cm/pixel, this information is useful
to correctly determine the area and coverage and to evaluate the expansion or regression rate of
P. oceanica in the recovery interventions. In the light of the results obtained, we believe that the
proposed photogrammetric methodology constitutes a tool that has now become necessary for
an accurate verification of the successful placement and analysis of the medium and long-term
evolution of the reforestation interventions of the P. oceanica meadows.
The complete article "Assessing Seagrass Restoration Actions through a
Micro-Bathymetry Survey Approach (Italy, Mediterranean Sea)" is available
at the link:
https://www.mdpi.com/2073-4441/14/8/1285
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