Computational methods and machine learning for Oceans
摘要截稿:
全文截稿: 2025-02-15
影响因子: 2.511
期刊难度:
CCF分类: 无
中科院JCR分区:
• 大类 : 环境科学与生态学 - 3区
• 小类 : 生态学 - 3区
Overview
Oceans play a crucial role in maintaining global ecological balance and climate regulation, making them a focal point in the UN's 2030 Agenda for Sustainable Development (Goal 14). However, understanding ocean dynamics is challenging due to the intricate nature of these expansive ecosystems and the complexity of managing, integrating and analysing diverse datasets. Consequently, the ever increasing need of advanced computational methods, ecosystem modeling approaches, and computer vision technologies, driven by machine learning, has become evident.
This Special Issue delves into extensive studies with the aim of deepening ecological knowledge about our oceans, in order to ensure the conservation and sustainable use of them and their resources. The focus is to address the vulnerability of the oceans to a spectrum of environmental risks, including anthropogenic pressures, such as overfishing, oil spills, microplastics, chemical and physical pollutants and climate change. Through a combination of traditional and next-generation computational methods in the acquisition and/or analysis of data pertinent to marine-related tasks, this special issue endeavors to explore profound insights into the intricate dynamics of marine environment.
Oceans play a crucial role in maintaining global ecological balance and climate regulation, making them a focal point in the UN's 2030 Agenda for Sustainable Development (Goal 14). However, understanding ocean dynamics is challenging due to the intricate nature of these expansive ecosystems and the complexity of managing, integrating and analysing diverse datasets. Consequently, the ever increasing need of advanced computational methods, ecosystem modeling approaches, and computer vision technologies, driven by machine learning, has become evident.
This Special Issue delves into extensive studies with the aim of deepening ecological knowledge about our oceans, in order to ensure the conservation and sustainable use of them and their resources. The focus is to address the vulnerability of the oceans to a spectrum of environmental risks, including anthropogenic pressures, such as overfishing, oil spills, microplastics, chemical and physical pollutants and climate change. Through a combination of traditional and next-generation computational methods in the acquisition and/or analysis of data pertinent to marine-related tasks, this special issue endeavors to explore profound insights into the intricate dynamics of marine environment.
Guest editors:
Dr. Rosalia MagliettaInstitute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing (CNR-STIIMA)rosalia.maglietta@cnr.it
Dr. Simone FranceschiniUniversity of Hawaiʻi at Mānoasimonefr@hawaii.edu
Dr. Pasquale RicciUniversity of Bari. Baripasquale.ricci@uniba.it
Manuscript submission information:
Submission Deadline: Feb 15, 2025