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Predictive models for abundance estimation and distribution maps of the striped dolphin Stenella coeruleoalba and the bottlenose dolphin Tursiops truncatus in the Northern Ionian Sea (North-eastern Central Mediterranean)
Author(s): V. Renò; C. Fanizza; G. Dimauro; V. Telesca; P. Dibari; G. Gala; N. Mosca; G. Cipriano; R. Carlucci; R. Maglietta
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Paper Abstract

Algorithms based on a clever exploitation of artificial intelligence (AI) techniques are the key for modern multidisciplinary applications that are being developed in the last decades. AI approaches’ ability of extracting relevant information from data is essential to perform comprehensive studies in new multidisciplinary topics such as ecological informatics. For example, improving knowledge on cetaceans’ distribution patterns enables the acquisition of a strategic expertise for developing tools aimed to the preservation of the marine environment. In this paper we present an innovative approach, based on Random Forest and RUSBoost, aimed to define predictive models for presence/absence and abundance estimation of two classes of cetaceans: the striped dolphin Stenella coeruleoalba and the common bottlenose dolphin Tursiops truncatus. Sightings data from 2009 to 2017 have been collected and enriched by geo-morphological and meteorological data in order to build a comprehensive dataset of real observations used to train and validate the proposed algorithms. Results in terms of classification and regression accuracy demonstrate the feasibility of the proposed approach and suggest the application of such artificial intelligence based techniques to larger datasets, with the aim of enabling large scale studies as well as improving knowledge on data deficient species.

Paper Details

Date Published: 21 June 2019
PDF: 8 pages
Proc. SPIE 11059, Multimodal Sensing: Technologies and Applications, 1105917 (21 June 2019); doi: 10.1117/12.2527534
Show Author Affiliations
V. Renò, Sistemi e Tecnologie Industriali Intelligenti per iil Manifattuiero Avanzato (Italy)
C. Fanizza, Jonian Dolphin Conservation (Italy)
G. Dimauro, Univ. degli Studi di Bari Aldo Moro (Italy)
V. Telesca, Univ. degli Studi della Basilicata (Italy)
P. Dibari, Univ. degli Studi di Bari Aldo Moro (Italy)
G. Gala, Univ. degli Studi di Bari Aldo Moro (Italy)
N. Mosca, Consiglio Nazionale delle Ricerche (Italy)
G. Cipriano, Univ. degli Studi di Bari Aldo Moro (Italy)
CoNISMa (Italy)
R. Carlucci, Univ. degli Studi di Bari Aldo Moro (Italy)
CoNISMa (Italy)
R. Maglietta, Consiglio Nazionale delle Ricerche (Italy)


Published in SPIE Proceedings Vol. 11059:
Multimodal Sensing: Technologies and Applications
Ettore Stella, Editor(s)

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