CHARACTERIZATION OF MASS DYNAMICS OF Sargassum spp. THROUGH MULTIFRACTAL ANALYSIS IN SEGMENTED ORBITAL PRODUCTS
Remote sensing; OLCI, Segmented images, Singularity spectrum.
Brown algae, known as Sargassum spp., are native to the North Atlantic and play a fundamental role in ocean dynamics. However, since 2011, large and exacerbated aggregations have been reported outside their region of origin. This dissertation sought to study these aggregations using segmented products from Sentinel 3 satellite images of the OLCI sensor with 300 meters of spatial resolution of the Mid-Atlantic region (CWA), using multifractal analysis, in 166 images for the dates 2020/01/02 to 2020/02/08, for the year 2020; 2021/04/01 to 2021/06/14, for the year 2021; 2023/06/01 to 2023/06/30, for the year 2023; and 2024/03/01 to 2024/03/30, for the year 2024. We also partitioned each image into 289 parts and applied multifractal analysis in order to extract the multifractal parameters of the singularity spectrum, width (∆α), dominant singularity (α0) and asymmetry index (f (∆α)), as well as lacunarity (Λ) and to make spatial distribution maps. The results show that the segmented images are multifractal, with Dq following D0> D1> D2 and a parabolic curve for the singularity spectrum, reflecting the interactions of Sargassum spp. over time, from low coverage in 2020 to high coverage in 2024, expressing the flowering phenomenon of these individuals. The partitions were also found to be multifractal, expressing different values in each portion of the images, allowing us to draw up the distribution of their parameters, where we could see a structure very similar to vortices, with a smaller spectral width, less lacunarity, an asymmetry to the left and greater dominant singularity, indicating that it is possible to identify the influence of the phenomena that govern the processes of ocean dynamics on different scales, even in segmented and binarized images.