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Evaluation of Seagrass Restoration Actions Through A Photogrammetric Survey Approach (Italy, Mediterranean Sea)

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Underwater photogrammetry, if correctly applied, can provide very high resolution and very accurate models for mapping and monitoring the restoration actions of degraded seafloor through the reforestation of seagrasses. Object-Based Image Analysis (OBIA) image analysis performs advanced classification capable of incorporating spectral data, color, texture, shape and other contextual information to identify thematic classes in images derived from optical and acoustic data. In particular, the OBIA classification uses a multi-resolution segmentation of the image to identify homogeneous objects (note: the term "object" in this case means a contiguous group of spatial data, such as pixels in a bathymetric grid). The segmentation process is based on predefined parameters, such as compactness, shape and scale, derived from real knowledge of the characteristics to be identified and classified. S Y S D E C O I T A L I A P A G I N A | 0 1 In this study, photogrammetric surveys were conducted on sites reforested with Posidonia oceanica located in five different areas, four of which in Italy (central and southern Tyrrhenian Sea and Strait of Sicily) and one in France (central Tyrrhenian Sea). Specifically, the results of the analysis of the processing of two orthomosaics of the Capo Feto site (Sicily) are reported Orthomosaics were classified using an OBIA approach with Trimble's eCognition suite and applying a supervised k-NN classification algorithm.

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