Articolo in rivista, 2022, ENG, 10.1134/S1054661822030336

An automated analysis tool for the classification of sea surface temperature imagery

Reggiannini M.; Papini O.; Pieri G.

CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy

Sea observation through remote sensing technologies plays an essential role in understanding the health status of the marine coastal environment, its fauna species and their future behavior. Accurate knowledge of the marine habitat and the factors affecting faunal variations allows us to perform predictions and adopt proper decisions. This paper concerns the proposal of a classification system devoted to recognizing marine mesoscale events. These phenomena are studied and monitored by analyzing sea surface temperature imagery. Currently, the standard way to perform such analysis relies on experts manually visualizing, analyzing, and tagging large imagery datasets. Nowadays, the availability of remote sensing data has increased so much that it is desirable to replace the labor-intensive, time-consuming, and subjective manual interpretation with automated analysis tools. The results presented in this work have been obtained by applying the proposed approach to images captured over the southwestern region of the Iberian Peninsula.

Pattern recognition and image analysis 32 (3), pp. 631–635

Keywords

Image processing, Remote sensing, Mesoscale patterns, Sea surface temperature, Machine learning, Climate change

CNR authors

Papini Oscar, Pieri Gabriele, Reggiannini Marco

CNR institutes

ISTI – Istituto di scienza e tecnologie dell'informazione "Alessandro Faedo"

ID: 471436

Year: 2022

Type: Articolo in rivista

Creation: 2022-09-29 11:52:16.000

Last update: 2022-11-02 10:00:00.000

External IDs

CNR OAI-PMH: oai:it.cnr:prodotti:471436

DOI: 10.1134/S1054661822030336

Scopus: 2-s2.0-85140260896

ISI Web of Science (WOS): 000869886400029