Authors:
Marco Reggiannini
1
;
João Janeiro
2
;
Flávio Martins
3
;
Oscar Papini
1
and
Gabriele Pieri
1
Affiliations:
1
Institute of Information Science and Technologies, National Research Council of Italy, Via G. Moruzzi, Pisa, Italy
;
2
University of Algarve, Centre for Marine and Environmental Research – CIMA, Campus de Gambelas, Faro, Portugal
;
3
University of Algarve, Centre for Marine and Environmental Research – CIMA, Institute of Engineering ISE, Campus de Gambelas, Faro, Portugal
Keyword(s):
Image Processing, Remote Sensing, Mesoscale Patterns, Sea Surface Temperature.
Abstract:
Mesoscale marine phenomena represent important features to understand and include within predictive models, which provide valuable information for proper environmental policy making. For example the rearrangement of the organic substances, consequent to the dynamics of the water masses affected by the mentioned phenomena, meaningfully modifies the actual condition of local habitats. Indeed it may facilitate the onset of non resident living species at the expense of resident ones, eventually affecting related human activity, such as commercial fishery. Objective of this work is the detection and identification of mesoscale events, in terms of specific marine surface patterns that are observed throughout such events, e.g. water filaments, counter-currents, meanders due to upwelling wind actions stress. These phenomena can be studied and monitored through the analysis of Sea Surface Temperature images captured by satellite missions, such as Metop, and MODIS Terra/Aqua. A quantitative de
scription of such events is proposed, based on dedicated algorithms that extract temporal and spatial features from the images, and exploit them to provide a signature discriminating different observed scenarios. Preliminary results of the application of the proposed approach to a dataset related to the southwestern region of the Iberian Peninsula are presented.
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